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BibTeX:
@inproceedings{Falkenstern2011,
  author = {Kristyn Falkenstern and Nicolas Bonnier and Marius Pedersen and Hans Brettel and Francoise Vienot},
  title = {Using Metrics to Assess the ICC Perceptual Rendering Intent},
  booktitle = {Image Quality and System Performance},
  address = {San Francisco, CA},
  month = {Jan},
  year = {2011},
  series = {Proceedings for SPIE}
}
BibTeX:
@inproceedings{Pedersen2011,
  author = {Marius Pedersen and Nicolas Bonnier and Jon Y. Hardeberg and Fritz Albregtsen},
  title = {Image quality metrics for the evaluation of print quality},
  booktitle = {Image Quality and System Performance},
  address = {San Francisco, CA},
  month = {Jan},
  year = {2011},
  series = {Proceedings for SPIE}
}
BibTeX:
@article{,
  author = {Peter Nussbaum and Jon Y. Hardeberg},
  title = {Print Quality Evaluation and Applied Colour Management in Coldset Offset Newspaper Print},
  journal = {Color Research and Application},
  year = {2011}
}
BibTeX:
@article{Nussbaum2011,
  author = {Peter Nussbaum and Aditya Sole and Jon Y. Hardeberg},
  title = {Analysis of color measurement uncertainty in a color managed printing workflow},
  journal = {Journal of Print and Media Technology Research},
  year = {2011}
}
BibTeX:
@inproceedings{Falkenstern2010,
  author = {Kristyn Falkenstern and Nicolas Bonnier and Hans Brettel and Marius Pedersen and Francoise Vienot},
  title = {Using Image Quality Metrics to Evaluate an ICC Printer Profile},
  booktitle = {Color and Imaging Conference},
  address = {San Antonio, TX},
  month = {Nov},
  publisher = {IS\&T and SID},
  year = {2010},
  pages = {244--249},
  url = {http://colorlab.no/content/download/30330/362122/file/Falkenstern2010_poster.pdf}
}
BibTeX:
@inproceedings{Gerhardt2010,
  author = {Jeremie Gerhardt and Jean-Baptiste Thomas},
  title = {Toward an automatic color calibration for 3D displays},
  booktitle = {Color and Imaging Conference},
  address = {San Antonio, TX},
  month = {Nov},
  publisher = {IS\&T and SID},
  year = {2010},
  pages = {5--10}
}
Abstract: We propose a new method for the visualization of spectral images. It involves a perception-based spectrum segmentation using an adaptable thresholding of the stretched CIE standard observer colormatching functions. This allows for an underlying removal of irrelevant channels, and, consequently, an alleviation of the computational burden of further processings. Principal Components Analysis is then used in each of the three segments to extract the Red, Green and Blue primaries for final visualization. A comparison framework using two different datasets shows the efficiency of the proposed method.
BibTeX:
@inproceedings{Moan2010b,
  author = {Steven Le Moan and Alamin Mansouri and Yvon Voisin and Jon Y. Hardeberg},
  title = {An Efficient Method for the Visualization of Spectral Images Based on a Perception-Oriented Spectrum Segmentation},
  booktitle = {Advances in Visual Computing - 6th International Symposium},
  address = {Las Vegas, NV},
  month = {Nov},
  publisher = {Springer},
  year = {2010},
  series = {Lecture Notes in Computer Science},
  pages = {361-370}
}
Abstract: The CIELAB based CIEDE2000 colour difference formula to measure small to medium colour differences is the latest standard formula of today which incorporates different corrections for the non uniformity of CIELAB space. It also takes account of parametric factors. In this paper, we present a mathematical formulation of the CIEDE2000 by the line element to derive a Riemannian metric tensor in a color space. The coefficients of this metric give Just Noticeable Difference (JND) ellipsoids in three dimensions and ellipses in two dimensions. We also show how this metric can be transformed between various colour spaces by means of the Jacobian matrix. Finally, the CIEDE2000 JND ellipses are plotted into the xy chromaticity diagram and compared to the observed BFD-P colour matching ellipses by a comparing method described in Pant and Farup (CGIV2010).
BibTeX:
@inproceedings{Pant2010a,
  author = {Dibakar Raj Pant and Ivar Farup},
  title = {Riemannian Formulation of the CIEDE2000 Color Difference Formula},
  booktitle = {Color Imaging Conference},
  address = {San Antonio, TX},
  month = {Nov},
  publisher = {IS\&T},
  year = {2010}
}
BibTeX:
@inproceedings{Pedersen2010b,
  author = {Marius Pedersen and Nicolas Bonnier and Jon Y. Hardeberg and Fritz Albregtsen},
  title = {Validation of Quality Attributes for Evaluation of Color Prints},
  booktitle = {Color and Imaging Conference},
  address = {San Antonio, TX},
  month = {Nov},
  publisher = {IS\&T and SID},
  year = {2010},
  pages = {74--79},
  url = {http://www.colorlab.no/content/download/29992/360170/file/Pedersen2010a_poster.pdf}
}
BibTeX:
@inproceedings{Pedersen2010c,
  author = {Marius Pedersen and Nicolas Bonnier and Jon Y. Hardeberg and Fritz Albregtsen},
  title = {Estimating Print Quality Attributes by Image Quality Metrics},
  booktitle = {Color and Imaging Conference},
  address = {San Antonio, TX},
  month = {Nov},
  publisher = {IS\&T and SID},
  year = {2010},
  pages = {68--73},
  url = {http://www.colorlab.no/content/download/29992/360170/file/Pedersen2010a_poster.pdf}
}
Abstract: In this paper we investigate if the Difference of Gaussians model is able to predict observers perceived difference in relation to compression artifacts. A new image difference metric for specifically designed for compression artifacts is proposed. In order to evaluate this new metric a psychophysical experiment is carried out, where a dataset of 80 compressed JPEG and JPEG2000 images were generated from 10 different scenes. The results of the psychophysical experiment with 18 observers and the quality scores obtained from a large number of image difference metrics are presented.

Furthermore, a quantitative study based on a number of image difference metrics and five additional databases is performed in order to reveal the potential of the proposed metric. The analyses show that the proposed metric and most of the tested ones do not correlate well with the subjective test results, and thus the increased complexity of the recent metrics is not justified.

BibTeX:
@inproceedings{Simone2010a,
  author = {Gabriele Simone and Valentina Caracciolo and Marius Pedersen and Faouzi Alaya Cheikh},
  title = {Evaluation of a Difference of Gaussians Based Image Difference Metric in Relation to Perceived Compression Artifacts},
  booktitle = {Advances in Visual Computing - 6th International Symposium},
  address = {Las Vegas, NV},
  month = {Nov},
  publisher = {Springer},
  year = {2010},
  series = {Lecture Notes in Computer Science},
  pages = {491-500}
}
Abstract: Several techniques for the computation of gamut boundaries have been presented in the past. In this paper we take an in-depth look at some of the gamut boundary descriptors used when performing today’s gamut mapping algorithms. We present a method for evaluating the mismatch introduced when using a descriptor to approximate the boundary of a device gamut. First, a visually verified reference gamut boundary is created by triangulating the gamut surface using a device profile or a device characterization model. The different gamut boundary descriptor techniques are then used to construct gamut boundaries based on several sets of simulated measurement data from the device. These boundaries are then compared against the reference gamut by utilizing a novel voxel based approach. Results from experiments using several gamut boundary descriptors are presented and analyzed statistically The modified convex hull algorithm proposed by Balasubramian and Dalal performs well for all the different data sets.
BibTeX:
@article{Bakke2010a,
  author = {Arne M. Bakke and Ivar Farup and Jon Y. Hardeberg},
  title = {Evaluation of Algorithms for the Determination of Color Gamut Boundaries},
  month = {Sep},
  journal = {Journal of Imaging Science and Technology},
  year = {2010},
  volume = {54},
  number = {5},
  pages = {050502-(11)}
}
Abstract: In this paper, a new color visualization technique for multi and hyperspectral images is proposed. This method is based on a maximization of the perceptual distance between the scene endmembers as well as natural constancy of the resulting images. The stretched CMF principle is used to transform reflectance into values in the CIE L*a*b* colorspace combined with an a priori known segmentation map for separability enhancement between classes. Boundaries are set in the a*b* subspace to balance the natural palette of colors in order to ease interpretation by a human expert. Convincing results on two different images are shown.
BibTeX:
@conference{Moan2010a,
  author = {Steven Le Moan and Alamin Mansouri and Jon Y. Hardeberg and Yvon Voisin},
  title = {A CLASS-SEPARABILITY-BASED METHOD FOR MULTI/HYPERSPECTRAL IMAGE COLOR VISUALIZATION},
  booktitle = {International Conference on Image Processing (ICIP)},
  address = {Hong Kong},
  month = {Sep},
  year = {2010}
}
Abstract: This paper defines one of the many ways to setup a soft proofing workstation comprising of a monitor display and viewing booth in a printing workflow as per the Function 4 requirements of PSO certification. Soft proofing requirements defined by ISO 12646 are explained and are implemented in this paper. Nec SpectraView LCD2180WG LED display along with Just colorCommunicator 2 viewing booth and X-rite EyeOne Pro spectrophotometer are used in this setup. Display monitor colour gamut is checked for its ability to simulate the ISO standard printer profile (ISOcoated_v2_300_eci.icc) as per the ISO 12646 requirements.

Methods and procedures to perform ambient light measurements and viewing booth measurements using EyeOne Pro spectrophotometer are explained. Adobe Photoshop CS4 software is used to simulate the printer profile on to the monitor display, while, Nec SpectraView Profiler software is used to calibrate and characterize the display and also to perform ambient light and viewing booth measurements and adjustments.

BibTeX:
@conference{Sole2010,
  author = {Aditya Sole and Peter Nussbaum and Jon Yngve Hardeberg},
  title = {Implementing ISO12646 standards for soft proofing in a standardized printing workflow according to PSO},
  booktitle = {iarigai},
  address = {Montreal, Canada},
  month = {Sep},
  year = {2010},
  keywords = {Colour measurement, colour management, process control standards, soft proofing, display
calibration, display characterisation}
}
Abstract: This paper proposes a reference free perceptual quality metric for blackboard lecture images. The text in the image is mostly affected by high compression ratio and de-noising filters which cause blocking and blurring artifacts. As a result the perceived text quality of the blackboard image degrades. The degraded text is not only difficult to read by humans but it also makes the optical character recognition task even more difficult. Therefore, we put our effort firstly to estimate the presence of these artifacts and then we used it in our proposed quality metric. The blocking and blurring features are extracted from the image content on block boundaries without the presence of reference image. Thus it makes our metric reference free. The metric also uses the visual saliency model to mimic the human visual system (HVS) by focusing only on the distortions in perceptually important regions, i.e. those regions which contains the text. Moreover psychophysical experiments are conducted that show very good correlation between the mean opinion score and quality scores obtained from our reference free perceptual quality metric (RF-PQM). The correlation results are also compared with standard reference and reference free metric.
BibTeX:
@conference{Imran2010,
  author = {Ali Shariq Imran and Faouzi Alaya Cheikh},
  title = {Blind Image Quality Metric For Blackboard Lecture Images},
  booktitle = {European Signal Processing Conference (EUSIPCO)},
  address = {Aalborg, Denmark},
  month = {Aug},
  year = {2010}
}
Abstract: The development of faster and more cost effective acquisition systems is very important for the widespread use of multispectral imaging. This paper studies the feasibility of using

two commercially available RGB cameras, each equipped with an optical filter, as a six channel multispectral image capture system. The main idea is to pick the best pair of filters from among readily available filters that modifies the sensitivities of the two cameras in such a way that their dominant wavelengths spread well spaced throughout the visible spectrum. Simulations with reasonably large number of available filters show encouraging result clearly indicating the possibility of using such systems.

BibTeX:
@conference{Shrestha2010,
  author = {Raju Shrestha and Jon Yngve Hardeberg},
  title = {Multispectral Image Capture using two RGB cameras},
  booktitle = {European Signal Processing Conference (EUSIPCO)},
  address = {Aalborg, Denmark},
  month = {Aug},
  year = {2010},
  url = {http://www.colorlab.no/content/download/28852/330365/file/Shrestha2010Poster.pdf}
}
BibTeX:
@conference{Cao2010a,
  author = {Guanqun Cao and Faouzi Alaya Cheikh},
  title = {SALIENT REGION DETECTION WITH OPPONENT COLOR BOOSTING},
  booktitle = {European Workshop on Visual Information Processing (EUVIP)},
  address = {Paris, France},
  month = {Jul},
  year = {2010}
}
BibTeX:
@conference{Imran2010a,
  author = {Ali Imran and Fahad Guraya and Faouzi Alaya Cheikh},
  title = {A VISUAL ATTENTION BASED REFERENCE FREE PERCEPTUAL QUALITY METRIC},
  booktitle = {European Workshop on Visual Information Processing (EUVIP)},
  address = {Paris, France},
  month = {Jul},
  year = {2010}
}
Abstract: Development and implementation of spatial color algorithms has been an active field of research in image processing for the last few decades. A number of investigations have been carried out so far in mimicking the properties of the human visual system (HVS). Various algorithms and models have been developed, but they produce more or less neutral output. Some applications demand the preservation of appearance of the original image along with the enhancement performed by these models. It is our attempt in this paper to present a number of techniques that are designed to satisfy the requirements of those applications. Our techniques work in two general stages. In the first stage, properties of the original image are extracted and stored. In the second stage, the resulting images from the image enhancement models are processed with those properties. Most of these techniques perform quite well for different categories of images. We combine different approaches such as gamma, scaling, linear, scaling and clipping to preserve properties like color cast, maximum and minimum channel value etc. Our methods have been extended for Low-key and High-key images as well.
BibTeX:
@conference{Islam2010,
  author = {ABM Tariqul Islam and Ivar Farup},
  title = {ENHANCING THE OUTPUT OF SPATIAL COLOR ALGORITHMS},
  booktitle = {European Workshop on Visual Information Processing (EUVIP)},
  address = {Paris, France},
  month = {Jul},
  year = {2010}
}
BibTeX:
@conference{Simone2010,
  author = {Gabriele Simone and Marius Pedersen and Jon Hardeberg},
  title = {MEASURING PERCEPTUAL CONTRAST IN UNCONTROLLED ENVIRONMENTS},
  booktitle = {European Workshop on Visual Information Processing (EUVIP)},
  address = {Paris, France},
  month = {Jul},
  year = {2010}
}
Abstract: The goal of this work is to present and review two new image difference metrics, named SDOG −CIELAB and SDOG −DEE. These metrics are along the same lines as the standard SCIELAB metric (Zhang and Wandell, 1997), modified to include a pyramidal subsampling, the Difference of Gaussians receptivefield model (DOG) (Tadmor and Tolhurst, 2000), and the ΔEE color-difference formula (Oleari et al., 2009). The DOG model and the ΔEE formula have been shown to improve respectively contrast measures and image quality metrics (Simone et al., 2009). Extensive testing using 29 state-of-the-art metrics and six image databases has been performed. Although this new approach is promising, we only find weak evidence of effectiveness. Analysis of the results indicates that the metrics show fairly good correlations over particular test images, yet they do not outperform the most common objective quality

measures.

BibTeX:
@inproceedings{Ajagamelle2010,
  author = {Sebastien Akli Ajagamelle and Marius Pedersen and Gabriele Simone},
  title = {Analysis of the Difference of Gaussians Model in Image Difference Metrics},
  booktitle = {5th European Conference on Colour in Graphics, Imaging, and Vision (CGIV)},
  address = {Joensuu, Finland},
  month = {June},
  year = {2010},
  pages = {489--496}
}
Abstract: Gamut boundary determination is an important step in device characterisation and colour gamut mapping. Many different algorithms for the determination of colour gamuts are proposed in the literature. They vary in accuracy, computational efficiency, and complexity of the resulting triangulated gamut surface. Recently, an algorithm called uniform segment visualization (USV) was developed. The gamut surfaces produced by the USV algorithm is more accurate than the ones produced by the the segment maxima algorithm, while at the same time, they are significantly simpler than the ones produced by the somewhat more accurate modified convex hull. In this paper, we propose a new method. First, an accurate gamut boundary is computed using the modified convex hull. The resulting surface is then simplified using an established mesh decimation technique. This results in surfaces that are significantly more accurate than the ones produced by the USV algorithm at a comparable complexity.
BibTeX:
@inproceedings{Bakke2010,
  author = {Arne Magnus Bakke and Ivar Farup},
  title = {Simplified Gamut Boundary Representation Using Mesh Decimation},
  booktitle = {5th European Conference on Colour in Graphics, Imaging, and Vision (CGIV)},
  address = {Joensuu, Finland},
  month = {June},
  year = {2010},
  pages = {459--465}
}
Abstract: When an image is reproduced with a device different artifacts can occur. These artifacts, if detectable by observers, will reduce the quality of the image. If these artifacts occur in salient regions (regions of interest) or if the artifacts introduce salient regions they contribute to reduce the quality of the reproduction. In this paper we propose a novel method for the detection of artifacts based on saliency models. The method is evaluated against a set of gamut mapped images containing the most common artifacts, which have been marked by a group of color experts. The results have shown that the proposed metrics are promising to detect the artifacts through the reproduction.
BibTeX:
@inproceedings{Cao2010,
  author = {Guanqun Cao and Marius Pedersen and Zofia Baranczuk},
  title = {Saliency Models as Gamut-Mapping Artifact Detectors},
  booktitle = {5th European Conference on Colour in Graphics, Imaging, and Vision (CGIV)},
  address = {Joensuu, Finland},
  month = {June},
  year = {2010},
  pages = {437--443}
}
Abstract: In this paper we present the design of an image Content-Based Indexing and Retrieval (CBIR) system which, based upon existing implementations of a number of well-known color descriptors, makes use of the bag-of-words or codebook model in order to construct a robust approach to the retrieval of images from a database in a query-by-example context. A new object image database was constructed specifically for this task, in an attempt to challenge the invariance properties of the system under controlled conditions of illumination, point of view and scale. The system permits the combined use of up to two of the different color descriptors considered. The experiments run over a subset of the image database show an improvement of the obtained results under some of the tested combinations, as well as the effect of the variation of the employed codebook size.
BibTeX:
@inproceedings{Gila2010,
  author = {Aitor Alvarez Gila and Guanqun Cao and Sheikh Faridul Hasan and Yu Hu},
  title = {Combining Color Descriptors for Improved Codebook Model-Based Image Retrieval},
  booktitle = {5th European Conference on Colour in Graphics, Imaging, and Vision (CGIV)},
  address = {Joensuu, Finland},
  month = {June},
  year = {2010},
  pages = {306--313}
}
Abstract: Quantifying the perceptual difference between original and reproduced (and inevitably modified) color images is currently a key research challenge in the field of color imaging. Such information can be extremely valuable for instance in the development of new equipment and algorithms for color reproduction.

While in many research areas it is common practice to obtain quantitative quality information by the use of perceptual tests, in which the judgments of several human observers are being collected and carefully analyzed statistically, this approach has serious limitations for practical use, in particular because of the time consumption.

Motivated by this, and aided by the ever increasing available knowledge about the mechanisms of the human visual system, the quest for perceptual color image quality metrics that can adequately predict human quality judgments of complex images, has been on for several decades. However, unfortunately, the Holy Grail is yet to be found.

The current paper outlines the state of the art of this field, including benchmarking of existing metrics, presents recent research, and proposes promising areas for further work. Aspects that are covered in particular include new models and metrics for color image quality, and new frameworks for using the metrics to improve color image representation and reproduction algorithms.

BibTeX:
@inproceedings{Hardeberg2010,
  author = {Jon Yngve Hardeberg},
  title = {Color by Numbers -- Quantifying the Quality of Color Reproduction},
  booktitle = {5th European Conference on Colour in Graphics, Imaging, and Vision (CGIV)},
  address = {Joensuu, Finland},
  month = {June},
  year = {2010},
  pages = {429--430},
  note = {Keynote}
}
Abstract: In this paper, a new approach for the recognition and classification of convex objects in color images is presented. It is based on a collaboration between color quantization, mathematical morphology and reflectance estimation from RGB data. This yields a robust algorithm regarding the conditions of illumination, the color sensor used for acquisition, as well as the shape/overlapping ambiguities among the objects. One singularity of this work is the use of mathematical morphology in two distinct topologies: first in the entire image, for segmentation purposes, then locally, to enhance the classification of each object. A resolution reduction is used to alleviate the effect of local disturbances such as noise or natural impurities on the objects. The method’s efficiency and usefulness are illustrated on the particular task of coffee beans sorting.
BibTeX:
@inproceedings{Moan2010,
  author = {Steven Le Moan and Alamin Mansouri and Tadeusz Sliwa and Madaín Pérez and Patricio and Yvon Voisin and Jon Y. Hardeberg},
  title = {Convex Objects Recognition and Classification Using Spectral and Morphological Descriptors},
  booktitle = {5th European Conference on Colour in Graphics, Imaging, and Vision (CGIV)},
  address = {Joensuu, Finland},
  month = {June},
  year = {2010},
  pages = {293--299}
}
Abstract: For precision color matching, visual sensitivity to small color difference is an essential factor. Small color differences can be measured by the just noticeable difference (JND) ellipses. The points on the ellipse represent colours that are just noticably different from the colour of the centre point. Mathematically, such an ellipse can be described by a positive definite quadratic

differential form, which is also known as the Riemannian metric. In this paper, we propose a method which makes use of the Riemannian metric and Jacobean transformations to transform JND ellipses between different colour spaces. As an example,

we compute the JND ellipses of the CIELAB and CIELUV color difference formulae in the xy chromaticity diagram. We also propose a measure for comparing the similarity of a pair of ellipses and use that measure to compare the CIELAB and CIELUV ellipses to two previously established experimental sets of ellipses. The proposed measure takes into account the size, shape and orientation. The technique works by calculating the ratio of the area of the intersection and the area of the union of a pair of ellipses. The method developed can in principle be applied for comparing the performance of any color difference formula and experimentally obtained sets of colour discrimination ellipses.

BibTeX:
@inproceedings{Pant2010,
  author = {Dibakar Raj Pant and Ivar Farup},
  title = {Evaluating Color Difference Formulae by Riemannian Metric},
  booktitle = {5th European Conference on Colour in Graphics, Imaging, and Vision (CGIV)},
  address = {Joensuu, Finland},
  month = {June},
  year = {2010},
  pages = {497--503},
  url = {http://colorlab.no/content/download/30169/361106/file/Pant2010Poster.pdf}
}
BibTeX:
@inproceedings{Pedersen2010,
  author = {Marius Pedersen and Seyed Ali Amirshahi},
  title = {Framework for the Evaluation of Color Prints Using Image Quality Metrics},
  booktitle = {5th European Conference on Colour in Graphics, Imaging, and Vision (CGIV)},
  address = {Joensuu, Finland},
  month = {June},
  year = {2010},
  pages = {75--82}
}
BibTeX:
@inproceedings{Wang2010,
  author = {Zhaohui Wang and Anna Aristova and Jon Yngve Hardeberg},
  title = {Evaluating the Effect of Noise on 3D LUT-Based Color Transformations},
  booktitle = {5th European Conference on Colour in Graphics, Imaging, and Vision (CGIV)},
  address = {Joensuu, Finland},
  month = {June},
  year = {2010},
  pages = {88--93}
}
BibTeX:
@conference{Hardeberg2010a,
  author = {Jon Yngve Hardeberg},
  title = {Multispectral Color Imaging},
  booktitle = {Industrial Visionday},
  address = {Copenhagen, Denmark},
  month = {May},
  year = {2010},
  note = {Invited talk}
}
BibTeX:
@conference{Wang2010a,
  author = {Zhaohui Wang and Anna Aristova and Jon Yngve Hardeberg},
  title = {Quantifying Smoothness of the LUTs-based Color Transformations},
  booktitle = {31st International Congress on Imaging Science (ICIS)},
  address = {Beijing, China},
  month = {May},
  year = {2010}
}
BibTeX:
@article{Pedersen2010a,
  author = {M. Pedersen and N. Bonnier and J. Y. Hardeberg and F. Albregtsen},
  title = {Attributes of Image Quality for Color Prints},
  month = {Jan},
  journal = {Journal of Electronic Imaging},
  year = {2010},
  volume = {19},
  number = {1},
  pages = {011016-1 -- 011016-13},
  url = {http://spiedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JEIME5000019000001011016000001&idtype=cvips&gifs=Yes&ver=dl&type=ALERT}
}
BibTeX:
@article{George2010,
  author = {Sony George and Jon Y. Hardeberg and Tomson G. George and V. P. N. Nampoori},
  title = {Automatic Redeye Correction Algorithm with Multilevel Eye Confirmation},
  journal = {Journal of Imaging Science and Technology},
  publisher = {IST},
  year = {2010},
  volume = {54},
  number = {3},
  pages = {030404},
  keywords = {eye; image colour analysis; image sensors; photography; reflection},
  url = {http://link.aip.org/link/?IST/54/030404/1},
  doi = {10.2352/J.ImagingSci.Technol.2010.54.3.030404}
}
BibTeX:
@article{Thomas2010,
  author = {Jean-Baptiste Thomas and Arne Magnus Bakke and Jeremie Gerhardt},
  title = {Spatial Nonuniformity of Color Features in Projection Displays: A Quantitative Analysis},
  journal = {Journal of Imaging Science and Technology},
  publisher = {IST},
  year = {2010},
  volume = {54},
  number = {3},
  pages = {030403},
  keywords = {brightness; colour displays; optical projectors},
  url = {http://link.aip.org/link/?IST/54/030403/1},
  doi = {10.2352/J.ImagingSci.Technol.2010.54.3.030403}
}
BibTeX:
@article{Tong2010,
  author = {Yubing Tong and Hubert Konik and Faouzi A. Cheikh and Alain Tremeau},
  title = {Full Reference Image Quality Assessment Based on Saliency Map Analysis},
  journal = {Journal of Imaging Science and Technology},
  publisher = {IST},
  year = {2010},
  volume = {54},
  number = {3},
  pages = {030503},
  keywords = {image recognition; set theory},
  url = {http://link.aip.org/link/?IST/54/030503/1},
  doi = {10.2352/J.ImagingSci.Technol.2010.54.3.030503}
}
BibTeX:
@inproceedings{Pedersen2009c,
  author = {Marius Pedersen and Nicolas Bonnier and Jon Y. Hardeberg and Fritz Albregtsen},
  title = {Attributes of a New Image Quality Model for Color Prints},
  booktitle = {17th Color Imaging Conference},
  address = {Albuquerque, NM, USA},
  month = {Nov},
  year = {2009},
  pages = {204--209},
  url = {http://colorlab.no/content/download/26878/303515/file/Pedersen2009c_Poster.pdf}
}
BibTeX:
@inproceedings{Wang2009,
  author = {Zhaohui Wang and Jon Yngve Hardeberg},
  title = {An adaptive Bilateral Filter for Predicting Color Image Difference},
  booktitle = {17th Color Imaging Conference},
  address = {Albuquerque, NM, USA},
  month = {Nov},
  year = {2009},
  pages = {27-31}
}
Abstract: In this paper, we approach color-image-difference metrics by a Euclidean color-difference formula for small-medium color differences in log-compressed OSA-UCS space, recently published (C. Oleari, M. Melgosa and R. Huertas, J. Opt. Soc. Am. A, 26(1):121–134, 2009). We start from previous imagedifference metrics by replacing the CIE color-difference formulae with the new one. Tests are made by using the Pearson-, Spearman- and Kendall-correlation coefficient. Particularly, we compare the

calculated image-difference metrics in relation to the perceived image difference obtained with psychophysical experiments. Current results show improvements in the actual state of art, making this formula the future key for image- difference metrics.

BibTeX:
@conference{Simone2009d,
  author = {Gabriele Simone and Claudio Oleari and Ivar Farup},
  title = {PERFORMANCE OF THE EUCLIDEAN COLOR-DIFFERENCE FORMULA IN LOG-COMPRESSED OSA-UCS SPACE APPLIED TO MODIFIED-IMAGE-DIFFERENCE METRICS},
  booktitle = {11th Congress of the International Colour Association (AIC)},
  address = {Sydney, Australia},
  month = {Sep},
  year = {2009}
}
BibTeX:
@conference{Ajagamelle2009,
  author = {S. A. Ajagamelle and G. Simone and M. Pedersen},
  title = {Performance of the Difference of Gaussians Model in Image Difference Metrics},
  booktitle = {Proceedings from Gjøvik Color Imaging Symposium 2009},
  address = {Gj\{o}vik, Norway},
  month = {Jun},
  year = {2009},
  series = {Høgskolen i Gjøviks rapportserie},
  number = {4},
  pages = {27-30},
  url = {http://brage.bibsys.no/hig/bitstream/URN:NBN:no-bibsys_brage_9313/3/sammensatt_elektronisk.pdf}
}
Abstract: We present a novel, computationally efficient, iterative, spatial gamut mapping algorithm. The proposed algorithm offers a compromise between the colorimetrically optimal gamut clipping and the most successful spatial methods. This is achieved by the iterative nature of the method. At iteration level zero, the result is identical to gamut clipping. The more we iterate the more we approach an optimal, spatial, gamut mapping result. Optimal is defined as a gamut mapping algorithm that preserves the hue of the image colours as well as the spatial ratios at all scales. Our results show that as few as five iterations are sufficientto produce an output that is as good or better than that achieved in previous, computationally more expensive, methods. Being able to improve upon previous results using such low number of iterations allows us to state that the proposed algorithm is O(N), N being the number of pixels. Results based on a challenging small destination gamut supports our claims that it is indeed efficient.
BibTeX:
@inproceedings{Alsam2009,
  author = {A. Alsam and I. Farup},
  title = {Colour Gamut Mapping as a Constrained Variational Problem},
  booktitle = {16th Scandinavian Conference on Image Analysis},
  address = {Oslo, Norway},
  month = {Jun},
  year = {2009},
  series = {Lecture Notes in Computer Science},
  volume = {5575},
  pages = {109--118},
  url = {http://www.springerlink.com/link.asp?id=105633}
}
BibTeX:
@inproceedings{Anderson2009,
  author = {Hyrum S. Anderson and Jon Yngve Hardeberg and Maya R. Gupta},
  title = {Full Reference Image Quality Metrics for Optimizing Example-based Total Variation Deblurring},
  booktitle = {Proceedings from Gjøvik Color Imaging Symposium 2009},
  address = {Gj\{o}vik, Norway},
  month = {Jun},
  year = {2009},
  series = {Høgskolen i Gjøviks rapportserie},
  number = {4},
  pages = {38-44},
  url = {http://brage.bibsys.no/hig/bitstream/URN:NBN:no-bibsys_brage_9313/3/sammensatt_elektronisk.pdf}
}
BibTeX:
@inproceedings{Bakke2009b,
  author = {Arne Magnus Bakke and Jean-Baptiste Thomas and Jérémie Gerhardt},
  title = {Common Assumptions in Color Characterization of Projectors},
  booktitle = {Proceedings from Gjøvik Color Imaging Symposium 2009},
  address = {Gj\{o}vik, Norway},
  month = {Jun},
  year = {2009},
  series = {Høgskolen i Gjøviks rapportserie},
  number = {4},
  pages = {45-53},
  url = {http://brage.bibsys.no/hig/bitstream/URN:NBN:no-bibsys_brage_9313/3/sammensatt_elektronisk.pdf}
}
BibTeX:
@inproceedings{Colantoni2009,
  author = {P. Colantoni and J-B. Thomas},
  title = {A color management process for real time color reconstruction of multispectral images},
  booktitle = {16th Scandinavian Conference on Image Analysis},
  address = {Oslo, Norway},
  month = {Jun},
  year = {2009},
  series = {Lecture Notes in Computer Science},
  volume = {5575},
  pages = {128--137},
  url = {http://www.springerlink.com/link.asp?id=105633}
}
BibTeX:
@inproceedings{George2009,
  author = {Sony George and Jon Yngve Hardeberg and Tomson G George},
  title = {A fully Automatic Redeye Correction Algorithm with Multilevel Eye Confirmation},
  booktitle = {Proceedings from Gjøvik Color Imaging Symposium 2009},
  address = {Gj\{o}vik, Norway},
  month = {Jun},
  year = {2009},
  series = {Høgskolen i Gjøviks rapportserie},
  number = {4},
  pages = {82-89},
  url = {http://brage.bibsys.no/hig/bitstream/URN:NBN:no-bibsys_brage_9313/3/sammensatt_elektronisk.pdf}
}
BibTeX:
@inproceedings{Gerhardt2009,
  author = {J. Gerhardt and J.Y. Hardeberg},
  title = {Simple Comparison of Spectral Color Reproduction Workflows},
  booktitle = {16th Scandinavian Conference on Image Analysis},
  address = {Oslo, Norway},
  month = {Jun},
  year = {2009},
  series = {Lecture Notes in Computer Science},
  volume = {5575},
  pages = {550--559},
  url = {http://www.springerlink.com/link.asp?id=105633}
}
BibTeX:
@inproceedings{Pant2009,
  author = {Dibakar Raj Pant},
  title = {Least-Square Technique for Color Reproduction of Semi-Transparent Material},
  booktitle = {Proceedings from Gjøvik Color Imaging Symposium 2009},
  address = {Gj\{o}vik, Norway},
  month = {Jun},
  year = {2009},
  series = {Høgskolen i Gjøviks rapportserie},
  number = {4},
  pages = {70-76},
  url = {http://brage.bibsys.no/hig/bitstream/URN:NBN:no-bibsys_brage_9313/3/sammensatt_elektronisk.pdf}
}
BibTeX:
@inproceedings{Pedersen2009a,
  author = {Marius Pedersen},
  title = {111 Full-Reference Image Quality Metrics and Still Not Good Enough?},
  booktitle = {Proceedings from Gjøvik Color Imaging Symposium 2009},
  address = {Gj\{o}vik, Norway},
  month = {Jun},
  year = {2009},
  series = {Høgskolen i Gjøviks rapportserie},
  number = {4},
  pages = {4},
  url = {http://brage.bibsys.no/hig/bitstream/URN:NBN:no-bibsys_brage_9313/3/sammensatt_elektronisk.pdf}
}
BibTeX:
@techreport{Pedersen2009d,
  author = {Marius Pedersen and Jon Yngve Hardeberg},
  title = {Survey of full-reference image quality metrics},
  address = {Gjøvik, Norway},
  month = {June},
  year = {2009},
  number = {5},
  note = {ISSN: 1890-520X},
  url = {http://brage.bibsys.no/hig/bitstream/URN:NBN:no-bibsys_brage_9330/1/rapport052009_elektroniskversjon.pdf}
}
BibTeX:
@inproceedings{Rizzi2009,
  author = {Alessandro Rizzi and Aditya Sole and Peter Nussbaum},
  title = {Colour and Lightness Perception in Low and High Dynamic Range ScenesRange Scenes},
  booktitle = {Proceedings from Gjøvik Color Imaging Symposium 2009},
  address = {Gj\{o}vik, Norway},
  month = {Jun},
  year = {2009},
  series = {Høgskolen i Gjøviks rapportserie},
  number = {4},
  pages = {110-116},
  url = {http://brage.bibsys.no/hig/bitstream/URN:NBN:no-bibsys_brage_9313/3/sammensatt_elektronisk.pdf}
}
BibTeX:
@inproceedings{Sharma2009,
  author = {Puneet Sharma and Faouzi Alaya Cheikh and Jon Yngve Hardeberg},
  title = {Face Saliency in Human Visual Saliency Models},
  booktitle = {Proceedings from Gjøvik Color Imaging Symposium 2009},
  address = {Gj\{o}vik, Norway},
  month = {Jun},
  year = {2009},
  series = {Høgskolen i Gjøviks rapportserie},
  number = {4},
  pages = {12-18},
  url = {http://brage.bibsys.no/hig/bitstream/URN:NBN:no-bibsys_brage_9313/3/sammensatt_elektronisk.pdf}
}
BibTeX:
@inproceedings{Simone2009c,
  author = {G. Simone and C. Oleari and I. Farup},
  title = {An Alternative Color Difference Formula for Computing Image Difference},
  booktitle = {Proceedings from Gjøvik Color Imaging Symposium 2009},
  address = {Gj\{o}vik, Norway},
  month = {Jun},
  year = {2009},
  series = {Høgskolen i Gjøviks rapportserie},
  number = {4},
  pages = {8-11},
  url = {http://brage.bibsys.no/hig/bitstream/URN:NBN:no-bibsys_brage_9313/3/sammensatt_elektronisk.pdf}
}
Abstract: In this paper, we propose and discuss a novel approach for measuring perceived contrast. The proposed method comes from the modification of previous algorithms with a different local measure of contrast and with a parameterized way to recombine local contrast maps and color channels. We propose the idea of recombining the local contrast maps using gaze information, saliency maps and a gaze-attentive fixation finding engine as weighting parameters giving attention to regions that observers stare at, finding them important. Our experimental results show that contrast measures cannot be improved using different weighting maps as contrast is an intrinsic factor and it’s judged by the global impression of the image.
BibTeX:
@inproceedings{Simone2009b,
  author = {Gabriele Simone and Marius Pedersen and Jon Yngve Hardeberg and Ivar Farup},
  title = {On the use of gaze information and saliency maps for measuring perceptual contrast},
  booktitle = {16th Scandinavian Conference on Image Analysis},
  address = {Oslo, Norway},
  month = {Jun},
  year = {2009},
  series = {Lecture Notes in Computer Science},
  volume = {5575},
  pages = {597--606},
  url = {http://www.springerlink.com/link.asp?id=105633}
}
BibTeX:
@proceedings{Simone2009a,,
  title = {Gjøvik Color Imaging Symposium},
  address = {Gj\{o}vik, Norway},
  month = {June},
  year = {2009},
  series = {Gjøvik University College Report Series},
  number = {4},
  note = {ISSN 1890-520X},
  url = {http://brage.bibsys.no/hig/bitstream/URN:NBN:no-bibsys_brage_9313/3/sammensatt_elektronisk.pdf}
}
BibTeX:
@conference{Pedersen2009,
  author = {Marius Pedersen and Jon Yngve Hardeberg},
  title = {SHAME: A new spatial hue angle metric for perceptual image difference},
  booktitle = {Vision Sciences Society 9th Annual Meeting},
  address = {Naples, Florida},
  month = {May},
  year = {2009},
  note = {Vision Sciences Society}
}
BibTeX:
@conference{Marius2009,
  author = {Marius Pedersen and Nicolas Bonnier and Fritz Albregtsen and Jon Yngve Hardeberg},
  title = {Towards a New Image Quality Model for Color Prints},
  booktitle = {ICC Digital Print Day},
  month = {Mar},
  year = {2009},
  url = {http://www.color.org/DigitalPrint/ICCDigitalPrint_presentations.pdf}
}
BibTeX:
@inproceedings{Pedersen2009e,
  author = {Marius Pedersen and Jon Yngve Hardeberg},
  title = {A new spatial hue angle metric for perceptual image difference},
  booktitle = {Second International Workshop Computational Color Imaging (CCIW09)},
  address = {Saint-Etienne, France},
  month = {Mar},
  publisher = {Springer},
  year = {2009},
  series = {Lecture Notes in Computer Science},
  volume = {5646},
  pages = {81--90},
  url = {http://www.springerlink.com/link.asp?id=105633}
}
BibTeX:
@inproceedings{Thomas2009,
  author = {Jean-Baptiste Thomas and Arne Magnus Bakke},
  title = {A colorimetric study of spatial uniformity in projection displays},
  booktitle = {Second International Workshop Computational Color Imaging (CCIW09)},
  address = {Saint-Etienne, France},
  month = {Mar},
  year = {2009},
  series = {Lecture Notes in Computer Science},
  volume = {5646},
  url = {http://www.springerlink.com/link.asp?id=105633}
}
Abstract: Gamut mapping algorithms are currently being developed to take advantage of the spatial information in an image to improve

the utilization of the destination gamut. These algorithms try to preserve the spatial information between neighboring pixels

in the image, such as edges and gradients, without sacrificing global contrast. Experiments have shown that such algorithms

can result in significantly improved reproduction of some images compared with non-spatial methods. However, due to the spatial processing of images, they introduce unwanted artefacts when used on certain types of images. In this paper we perform basic image analysis to predict whether a spatial algorithm is likely to perform better or worse than a good, non-spatial algorithm. Our approach starts by detecting the relative amount of areas in the image that are made up of uniformly colored pixels, as well as the amount of areas that contain details in out-of-gamut areas. A weighted difference is computed from these numbers, and we show that the result has a high correlation with the observed performanceof the spatial algorithm in a previous psychophysical experiment.

BibTeX:
@inproceedings{Bakke2009,
  author = {Arne M. Bakke and Ivar Farup and Jon Y. Hardeberg},
  title = {Predicting the performance of a spatial gamut mapping algorithm},
  booktitle = {Color Imaging XIV: Displaying, Hardcopy, Processing, and Applications},
  address = {San Jose, CA, USA},
  month = {Jan},
  year = {2009},
  volume = {7241}
}
BibTeX:
@inproceedings{Bakke2009a,
  author = {Arne M. Bakke and Jon Y. Hardeberg and Steffen Paul},
  title = {Simulation of film media in motion picture production using a digital still camera},
  booktitle = {Image Quality and System Performance VI},
  address = {San Jose, CA, USA},
  month = {Jan},
  year = {2009},
  volume = {7242}
}
BibTeX:
@inproceedings{Pedersen2009b,
  author = {Marius Pedersen and Fritz Albregtsen and Jon Y. Hardeberg},
  title = {Detection of worms in error diffusion halftoning},
  booktitle = {Image Quality and System Performance VI},
  address = {San Jose, CA, USA},
  month = {Jan},
  year = {2009},
  volume = {7242}
}
BibTeX:
@inproceedings{Renani2009,
  author = {Siavash Asgari Renani and Masato Tsukada and Jon Yngve Hardeberg},
  title = {Compensating for non-uniform screens in projection display systems},
  booktitle = {Color Imaging XIV: Displaying, Hardcopy, Processing, and Applications},
  address = {San Jose, CA, USA},
  month = {Jan},
  year = {2009},
  volume = {7241}
}
BibTeX:
@inproceedings{Simone2009,
  author = {Gabriele Simone and Marius Pedersen and Jon Yngve Hardeberg and Alessandro Rizzi},
  title = {Measuring perceptual contrast in a multilevel framework},
  booktitle = {Human Vision and Electronic Imaging XIV},
  month = {Jan},
  publisher = {SPIE},
  year = {2009},
  volume = {7240}
}
BibTeX:
@article{Dugay2007b,
  author = {Fabienne Dugay and Ivar Farup and Jon Y. Hardeberg},
  title = {Perceptual Evaluation of Color Gamut Mapping Algorithms},
  month = {Dec},
  journal = {Color Research \& Application},
  year = {2008},
  volume = {33},
  number = {6},
  pages = {470-476}
}
BibTeX:
@article{Gerhardt2008,
  author = {Jérémie Gerhardt and Jon Y. Hardeberg},
  title = {Spectral color reproduction minimizing spectral and perceptual color differences},
  month = {Dec},
  journal = {Color Research \& Application},
  year = {2008},
  volume = {33},
  number = {6},
  pages = {494-504}
}
BibTeX:
@article{Mansouri2008,
  author = {Alamin Mansouri and Tadeusz Sliwa and Jon Y. Hardeberg and Yvon Voisin},
  title = {Representation and estimation of spectral reflectances using projection on PCA and wavelet bases},
  month = {Dec},
  journal = {Color Research \& Application},
  year = {2008},
  volume = {33},
  number = {6},
  pages = {485-493}
}
BibTeX:
@conference{Mansouri2008a,
  author = {Mansouri, Alamin and Sliwa, Tadeusz and Hardeberg, Jon Yngve and Voisin, Yvon},
  title = {An adaptive-PCA algorithm for reflectance estimation from color images},
  booktitle = {19th International Conference on Pattern Recognition},
  month = {Dec},
  year = {2008},
  pages = {1-4},
  url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4761120&isnumber=4760915}
}
BibTeX:
@article{Thomas2008b,
  author = {Jean-Baptiste Thomas and Jon Y. Hardeberg and Irène Foucherot and Pierre Gouton},
  title = {The PLVC display color characterization model revisited},
  month = {Dec},
  journal = {Color Research \& Application},
  year = {2008},
  volume = {33},
  number = {6},
  pages = {449-460}
}
BibTeX:
@conference{Sharma2008,
  author = {Puneet Sharma and Faouzi Alaya Cheikh and Jon Yngve Hardeberg},
  title = {Saliency Map for Human Gaze Prediction in Images},
  booktitle = {Sixteenth Color Imaging Conference},
  address = {Portland, Oregon},
  month = {Nov},
  year = {2008}
}
BibTeX:
@conference{Simone2008,
  author = {Gabriele Simone and Claudio Oleari},
  title = {Software with Visual Phenomena, Tests, and Standard Colorimetric Computations for Didactics and Laboratory},
  booktitle = {Sixteenth Color Imaging Conference},
  address = {Portland, Oregon},
  month = {Nov},
  year = {2008}
}
BibTeX:
@article{Simone2008a,
  author = {Gabriele Simone and Marius Pedersen and Jon Yngve Hardeberg and Alessandro Rizzi},
  title = {A multi-level framework for measuring perceptual image contrast},
  month = {Oct},
  journal = {Scandinavian Journal of Optometry and Visual Science},
  year = {2008},
  volume = {1},
  number = {1},
  pages = {15},
  url = {http://www.synsinformasjon.no/Optikeren/pop.cfm?FuseAction=Doc&pAction=View&pDocumentId=17216}
}
Abstract: We propose a new method for the computation of gamut boundaries, consisting of a combination of the segment maxima gamut boundary descriptor, the modified convex hull algorithm, and a sphere tessellation technique. This method gives a more uniform subdivision of the colour space into segments, and thus a more consistent level of detail over the gamut surface. First, the colour space is divided into segments around a centre point using the triangles from the tessellation algorithm. The measurement points are processed, and the point with the largest radius is found for each non-empty segment. The convex hull algorithm with a preprocessing step is then applied to these maxima points to generate the final gamut surface. The method is tested on different input data, including data sets both with and without internal gamut points. Different numbers of segments are used, and the resulting gamut boundaries are compared with the gamuts constructed using the segment maxima method. A reference gamut is constructed for each device, and the average mismatch is calculated. Our method is shown to perform better than the segment maxima method, particularly for a higher number of segments.
BibTeX:
@conference{Bakke2008,
  author = {A.M. Bakke and I. Farup and J.Y. Hardeberg},
  title = {Improved gamut boundary determination for color gamut mapping},
  booktitle = {IARIGAI},
  address = {Valencia, Spain},
  month = {Sep},
  year = {2008}
}
BibTeX:
@article{Hardeberg2008,
  author = {Jon Yngve Hardeberg and Eriko Bando and Marius Pedersen},
  title = {Evaluating colour image difference metrics for gamut-mapped images},
  month = {Aug},
  journal = {Coloration Technology},
  year = {2008},
  volume = {124},
  number = {4},
  pages = {243-253},
  url = {http://www3.interscience.wiley.com/cgi-bin/fulltext/121356959/PDFSTART}
}
BibTeX:
@inproceedings{Koppen2008,
  author = {Mario Koppen and Katrin Franke},
  title = {A Color Morphology based on Pareto-Dominance Relation and Hypervolume Measure},
  booktitle = {CGIV 2008 - Fourth European Conference on Color in Graphics, Imaging and Vision},
  address = {Terrassa, Spain},
  month = {Jun},
  publisher = {IS/\&T},
  year = {2008}
}
BibTeX:
@inproceedings{Mikalsen2008,
  author = {Espen Bårdsnes Mikalsen and Jon Yngve Hardeberg and Jean-Baptiste Thomas},
  title = {Verification and extension of a camera-based end-user calibration method for projection displays},
  booktitle = {CGIV 2008 - Fourth European Conference on Color in Graphics, Imaging and Vision},
  address = {Terrassa, Spain},
  month = {Jun},
  publisher = {IS/\&T},
  year = {2008}
}
BibTeX:
@inproceedings{Pedersen2008b,
  author = {Marius Pedersen and Jon Yngve Hardeberg},
  title = {Rank Order and Image Difference Metrics},
  booktitle = {CGIV 2008 Fourth European Conference on Color in Graphics, Imaging and Vision},
  address = {Terrassa, Spain},
  month = {Jun},
  publisher = {IS\&T},
  year = {2008},
  pages = {120-125}
}
BibTeX:
@inproceedings{Pedersen2008a,
  author = {Marius Pedersen and Alessandro Rizzi and Jon Yngve Hardeberg and Gabriele Simone},
  title = {Evaluation of contrast measures in relation to observers perceived contrast},
  booktitle = {CGIV 2008 - Fourth European Conference on Color in Graphics, Imaging and Vision},
  address = {Terrassa, Spain},
  month = {Jun},
  publisher = {IS\&T},
  year = {2008},
  pages = {253-256}
}
BibTeX:
@inproceedings{Rizzi2008,
  author = {Alessandro Rizzi and Gabriele Simone and Roberto Cordone},
  title = {A modified algorithm for perceived contrast in digital images},
  booktitle = {CGIV 2008 - Fourth European Conference on Color in Graphics, Imaging and Vision},
  address = {Terrassa, Spain},
  month = {Jun},
  publisher = {IS\&T},
  year = {2008},
  pages = {249-252}
}
BibTeX:
@conference{Kominkova2008a,
  author = {Barbora Kominkova and Jon Yngve Hardeberg and Marius Pedersen and Marie Kaplanova.},
  title = {Comparison of eye tracking devices used on printed images},
  booktitle = {Scandinavian Workshop on Applied Eye-tracking},
  address = {Lund, Sweden},
  month = {Apr},
  year = {2008}
}
BibTeX:
@conference{Pedersen2008c,
  author = {Marius Pedersen and Jon Yngve Hardeberg and Peter Nussbaum},
  title = {Using gaze information to improve image difference metrics},
  booktitle = {Scandinavian Workshop on Applied Eye-tracking},
  address = {Lund, Sweden},
  month = {Apr},
  year = {2008}
}
BibTeX:
@inproceedings{Nussbaum2008,
  author = {Peter Nussbaum},
  title = {Print Quality Evaluation and Applied Colour Management in Coldset Offset Newspaper Print},
  booktitle = {{TAGA} 60th Annual Technical Conference},
  address = {San Francisco, CA, USA},
  month = {Mar},
  year = {2008}
}
BibTeX:
@article{Alsam2008a,
  author = {Ali Alsam and David Connah},
  title = {Optimal bases for convex color mixture},
  month = {Feb},
  journal = {J. Opt. Soc. Am. A},
  year = {2008},
  volume = {25},
  pages = {3}
}
Abstract: Eye tracking as a quantitative method for collecting eye movement data, requires the accurate knowledge of the eye position, where eye movements can provide indirect evidence about what the subject sees. In this study two eye tracking devices have been compared, Head-mounted Eye Tracking Device (HED) and Remote Eye Tracking Device (RED). It has been found out precisions of both devices, gaze position accuracy and stability of the calibration. For the HED it has been investigated how to register data to real-world coordinates. Whereas, since coordinates collected by the eye tracker are relative to the position of the subject's head and not relative to the actual stimuli as in the RED case. Result shows that the precision with time delay get worse for both eye tracking devices. The precision of RED is better than the HED and the difference between them is around 10 - 16 pixels (5.584 mm). Distribution of gaze position for HED and RED was expressed by a percentage representation of the point of regard in areas maked defined by the viewing angle. For both eye tracking devices the gaze position accuracy has been 95-99% at 1.5-2 degree viewing angle. The stability of the calibration was investigated on the end of the experiment and the result is not statistically significant. But the distribution of the gaze position is larger at the end of the experiment than at the beginning.
BibTeX:
@inproceedings{Kominkova2008,
  author = {Barbora Kominkova and Marius Pedersen and Jon Yngve Hardeberg and Marie Kaplanova},
  title = {Comparison of eye tracking devices used on printed images},
  booktitle = {Human Vision and Electronic Imaging VIII (HVEI-08)},
  address = {San Jose, USA},
  month = {Jan},
  publisher = {SPIE},
  year = {2008},
  series = {SPIE proceedings},
  volume = {6806},
  keywords = {Eye tracking, precision, gaze position, stability of calibration.}
}
BibTeX:
@inproceedings{Lefloch2008,
  author = {Damien Lefloch and Faouzi Alaya Cheikh and Jon Yngve Hardeberg and Pierre Goutton and Romain Picot-Clemente},
  title = {Real-time people counting system using a single video camera},
  booktitle = {Real-Time Image Processing},
  month = {Jan},
  publisher = {SPIE},
  year = {2008},
  volume = {6811}
}
Abstract: We have used image difference metrics to measure the quality of a set of images to know how well they predict perceived image difference. We carried out a psychophysical experiment with 25 observers along with an recording of the observers gaze position. The image difference metrics used were CIELAB deltaEab, S-CIELAB, the hue angle algorithm, iCAM and SSIM. A frequency map from the eye tracker data was applied as a weighting to the image difference metrics. The results indicate an improvement in correlation between the predicted image difference and the perceived image difference.
BibTeX:
@inproceedings{Pedersen2008,
  author = {Marius Pedersen and Jon Yngve Hardeberg and Peter Nussbaum},
  title = {Using gaze information to improve image difference metrics},
  booktitle = {Human Vision and Electronic Imaging VIII (HVEI-08)},
  address = {San Jose, USA},
  month = {Jan},
  publisher = {SPIE},
  year = {2008},
  series = {SPIE proceedings},
  volume = {6806},
  pages = {680611-1--680611-12},
  keywords = {Image difference metrics, Eye tracking, CIELAB deltaEab, S-CIELAB, SSIM, Hue angle, iCAM.}
}
BibTeX:
@inproceedings{Thomas2008,
  author = {Jean-Baptiste Thomas and Philippe Colantoni and Jon Yngve Hardeberg and Irene Foucherot and Pierre Gouton},
  title = {An inverse display color characterization model based on an optimized geometrical structure},
  booktitle = {Color Imaging XIII: Processing, Hardcopy, and Applications},
  address = {San Jose, USA},
  month = {Jan},
  publisher = {SPIE},
  year = {2008},
  volume = {6807}
}
BibTeX:
@article{Alsam2008,
  author = {Ali Alsam and Graham Finlayson},
  title = {Integer Programming for Optimal Reduction of Calibration Targets},
  journal = {Color, Research \& Application},
  year = {2008}
}
BibTeX:
@article{Thomas2008a,
  author = {Jean-Baptiste Thomas and Philippe Colantoni and Jon Y. Hardeberg and Irène Foucherot and Pierre Gouton},
  title = {A geometrical approach for inverting display color characterization models},
  journal = {SID},
  year = {2008},
  volume = {16},
  number = {10}
}
BibTeX:
@article{Wroldsen2008,
  author = {Wroldsen, Maria Sunde and Nussbaum, Peter and Hardeberg, Jon Yngve},
  title = {A comparison of densitometric and planimetric techniques for newspaper printing},
  journal = {TAGA Journal},
  year = {2008}
}
BibTeX:
@inproceedings{Gerhardt2007,
  author = {Jeremie Gerhardt and Jon Yngve Hardeberg},
  title = {Spectral color reproduction},
  booktitle = {34th International Research Conference of iarigai},
  address = {Grenoble},
  month = {Sep},
  year = {2007}
}
BibTeX:
@conference{Silva2007,
  author = {E. A. Silva and K. Panettaa and S.S. Agaian},
  title = {Quantifying image similarity using measure of enhancement by entropy},
  booktitle = {Mobile multimedia/image processing for military and security applications},
  address = {Orlando, Florida},
  month = {Apr},
  year = {2007}
}
BibTeX:
@inproceedings{Gerhardt2007b,
  author = {Jeremie Gerhardt and Jon Yngve Hardeberg},
  title = {Controlling the error in spectral vector error diffusion},
  booktitle = {Electronic Imaging:Color Imaging XII: Processing, Hardcopy, and Applications},
  address = {San Jose, CA},
  month = {Jan},
  publisher = {SPIE},
  year = {2007},
  series = {SPIE Proceedings},
  volume = {6493},
  pages = {649316}
}
BibTeX:
@article{Alsam2007a,
  author = {Ali Alsam and Graham Finlayson},
  title = {Metamer Sets without Spectral Calibration},
  journal = {JOSA A},
  year = {2007},
  volume = {24},
  pages = {2505-2512}
}
BibTeX:
@article{Alsam2007,
  author = {Ali Alsam and Reiner Lenz},
  title = {Calibrating Color Cameras using Metameric Blacks},
  journal = {JOSA A},
  year = {2007},
  volume = {24},
  number = {1},
  pages = {11-17}
}
BibTeX:
@article{Farup2007,
  author = {Ivar Farup and Carlo Gatta and Alessandro Rizzi},
  title = {A Multiscale Framework for Spatial Gamut Mapping},
  journal = {IEEE Transactions on Image Processing},
  year = {2007},
  volume = {16},
  number = {10},
  pages = {2423-2435}
}
Abstract: A particular version of a spectral integrator has been designed. It consists of a xenon lamp whose light is dispersed into a color spectrum by dispersing prisms. Using a transmissive LCD panel controlled by a computer, certain fractions of the light in different parts of the spectrum are masked out. The remaining transmitted light is integrated and projected onto a translucent diffusing plate. A spectroradiometer that measures the generated light is also attached to the computer, thus making the spectral integrator a closed-loop system. An algorithm for generating the light of a specified spectral power distribution has

been developed. The resulting measured spectra differ from the specified ones with relative rms errors in the range of 1%–20% depending on the shape of the spectral power distribution.

BibTeX:
@article{Farup2007a,
  author = {Ivar Farup and Jan Henrik Wold and Thorstein Seim and Torkjel Søndrol},
  title = {Generating lights with a specified spectral power distribution},
  journal = {Applied Optics},
  year = {2007},
  volume = {46},
  number = {13},
  pages = {2414-2422}
}
BibTeX:
@inproceedings{Gerhardt2007a,
  author = {Jeremie Gerhardt},
  title = {Spectral Color Reproduction versus color reproduction},
  booktitle = {Gjøvik Color Imaging Symposium},
  year = {2007}
}
BibTeX:
@inproceedings{Gerhardt2007c,
  author = {Jeremie Gerhardt and Jon Yngve Hardeberg},
  title = {Spectral color reproduction versus color reproduction},
  booktitle = {Advances in Printing and Media Technology},
  address = {Zagreb, Croatia},
  publisher = {Acta Graphica Publishers},
  year = {2007},
  volume = {34},
  pages = {147-152},
  note = {ISBN 978-953-7292-04-1}
}
BibTeX:
@inproceedings{Hardeberg2007,
  author = {Jon Yngve Hardeberg and Jeremie Gerhardt},
  title = {Towards spectral color reproduction},
  booktitle = {Ninth International Symposium on Multispectral Colour Science and Application},
  publisher = {IS\&T},
  year = {2007},
  pages = {16--22},
  note = {ISBN 978-0-89208-272-8}
}
BibTeX:
@techreport{Hardeberg2007a,
  author = {Jon Yngve Hardeberg and Peter Nussbaum and Ali Alsam and Ivar Farup},
  title = {Proceedings from Gjøvik Color Imaging Symposium 2007},
  year = {2007}
}
BibTeX:
@article{Hardeberg2007b,
  author = {Jon Yngve Hardeberg and Peter Nussbaum and Sylvain Roch and Ondrej Panak},
  title = {Time matters in soft proofing},
  journal = {Acta Graphica - Journal of Printing Science and Graphic Communication},
  year = {2007},
  volume = {19},
  number = {1-2},
  pages = {1-10},
  note = {ISSN 0353-4707}
}
Abstract: We present a new efficient hue- and edge-preserving spatial color gamut mapping algorithm. The initial computation of the algorithm is to project all out-of-gamut colors to the destination gamut boundary towards the center of the gamut. Based on this spatially invariant hue-preserving clipping of the image, we construct a greyscale map indicating the amount of compression performed. This map can be spatially modified by applying an edge-preserving smoothing filter that never decreases the amount of compression applied to an individual pixel. Finally, the colors of the original image are compressed towards the gamut center according to the filtered map. Examples on real images show that the algorithm gives interesting results.
BibTeX:
@inproceedings{Kolaas2007,
  author = {Øyvind Kolås and Ivar Farup},
  title = {Efficient Hue-preserving and Edge-preserving Spatial Color Gamut Mapping},
  booktitle = {15th Color Imaging Conference},
  address = {Nov},
  publisher = {IS\T},
  year = {2007},
  pages = {207-212}
}
BibTeX:
@inproceedings{Koeppen2007,
  author = {Mario Koppen and Katrin Franke},
  title = {A generalized approach of color morphology by means of Pareto-set theory},
  booktitle = {GCIS Proceedings},
  year = {2007},
  pages = {29}
}
BibTeX:
@inproceedings{Mansouri2007,
  author = {Alamin Mansouri and Tedeusz Sliwa and Jon Yngve Hardeberg and Yvon Voisin},
  title = {New decomposition basis for reflectance recovery from multispectral imaging systems},
  booktitle = {GCIS2007 Proceedings},
  year = {2007},
  pages = {75-82}
}
Abstract: A color memory experiment with 5 colors (red, green, blue, yellow, and Caucasian skin color) was carried out. The color patches, shown on an LCD monitor, was memorized under a given viewing condition. The mixing of the memory color was then done first under the same viewing condition, and subsequently under other two altered viewing conditions. The conditions were different in the background and surround parameters. The color appearance model CIECAM02 was then used to predict color attributes under the altered viewing conditions. The lowest color memory shift in hue attribute was found for the red color. CIECAM02 seemed to have some limitation in colorfulness and chroma attribute prediction, for colors viewed on a black background. The result show, that the color attributes prediction in color memory experiment was not successful.
BibTeX:
@inproceedings{Panak2007,
  author = {Ondrej Panak and Peter Nussbaum and Jon Yngve Hardeberg and Marie Kaplanova},
  title = {Colour Memory Match Under Disparate Viewing Conditions},
  booktitle = {IS\&T and SID's 15th Color Imaging Conference},
  year = {2007},
  pages = {325-330}
}
BibTeX:
@inproceedings{Roch2007,
  author = {Sylvain Roch and Jon Yngve Hardeberg and Peter Nussbaum},
  title = {Effect of time spacing on the perceived color},
  booktitle = {SPIE Proceedings Color Imaging XII: Processing, Hardcopy, and Applications},
  year = {2007},
  volume = {6493}
}
BibTeX:
@inproceedings{Thomas2007,
  author = {Jean-Baptiste Thomas and Jon Yngve Hardeberg and Irene Foucherot and Pierre Gouton},
  title = {Additivity based LC display color characterization},
  booktitle = {GCIS2007 Proceedings},
  year = {2007},
  pages = {50-55}
}
BibTeX:
@inproceedings{Wroldsen2007,
  author = {Maria Sunde Wroldsen and Peter Nussbaum and Jon Yngve Hardeberg},
  title = {Densitometric and Planimetric Measurement Techniques for Newspaper Printing},
  booktitle = {TAGA Proceedings},
  year = {2007},
  pages = {273-290}
}
Abstract: Calibration charts are used in colour imaging to determine color correction transforms and for spectrally characterising imaging devices. Traditionally, quite complex charts have evolved as it was reasoned that the more reflectances in a chart the more the chart could represent all other reflectances. However, a chart with many reflectances is both expensive, difficult and tedious to use. The difficulty lies in assuming constant lighting conditions over the whole chart and the tedium appears when the chart must be measured using a spectrophotometer. To circumvent these problems researchers have sought methods to find smaller sets of reflectances which, in some sense, represent larger reflectance sets. In this paper we develop an iterative selection procedure where we select individual reflectances from a colour chart. The first is chosen so it best accounts for the majority of the spectral variance. The next best accounts for the variance that is left. In general the ith selected chart reflectance best accounts for the variance among reflectances (given that 1 reflectances are already selected). We show that this procedure is weakly optimal and as such compares with prior art which chooses reflectances using simple heuristics. The new method is also much faster than algorithms that are built on stronger optimality conditions. Experiments demonstrate that our new method represents a reasonable compromise between fast (and feasible) reflectance selection and the optimality of the chosen set.
BibTeX:
@inproceedings{Alsam2006b,
  author = {Ali Alsam and Graham Finlayson},
  title = {Reducing the Number of Calibration Surfaces},
  booktitle = {Fourteenth Color Imaging Conference},
  address = {Scottsdale, Arizona},
  month = {Nov},
  year = {2006},
  pages = {170-174},
  note = {ISBN / ISSN: 0-89208-291-7}
}
Abstract: We propose a colour to greyscale algorithm providing colour separation as well as edge and texture enhancement. An image dependent grey-axis is computed based on the colour distribution in the image. An initial greyscale image is created by a point-wise operation where the grey value is the magnitude of the RGB coordinates re-mapped to the grey axis. The resulting greyscale image is enhanced by applying a novel correction mask. This mask, resembling an unsharp mask, is the sum of the difference between each of the colour components and a blurred version of the greyscale image. The resulting greyscale images are rich in detail without undesirable artifacts.
BibTeX:
@inproceedings{Alsam2006a,
  author = {Ali Alsam and Øyvind Kolås},
  title = {Grey Colour Sharpening},
  booktitle = {Fourteenth Color Imaging Conference},
  address = {Scottsdale, Arizona},
  month = {Nov},
  year = {2006},
  pages = {263-267},
  note = {ISBN / ISSN: 0-89208-292-5}
}
Abstract: Several techniques for the computation of gamut boundaries have been presented in the past. In this paper we take an in-depth look at some of the gamut boundary descriptors used when performing todays gamut mapping algorithms. We present a method for evaluation of the mismatch introduced when using a descriptor to approximate the boundary of a device gamut. First, a visually verified reference gamut boundary is created by triangulating the gamut surface using a device profile or a device characterization model. The different gamut boundary descriptor techniques are then used to construct gamut boundaries based on several sets of simulated measurement data from the device. These boundaries are then compared against the reference gamut by utilizing a novel voxel based approach. Preliminary results from experiments using several gamut boundary descriptors are presented, and the performance of the different algorithms is discussed.
BibTeX:
@inproceedings{Bakke2006,
  author = {Arne Magnus Bakke and Jon Yngve Hardeberg and Ivar Farup},
  title = {Evaluation of Gamut Boundary Descriptors},
  booktitle = {Fourteenth Color Imaging Conference},
  address = {Scottsdale, Arizona, USA},
  month = {Nov},
  year = {2006},
  pages = {50-55},
  note = {ISBN / ISSN: 0-89208-291-7}
}
BibTeX:
@inproceedings{Nussbaum2006,
  author = {Peter Nussbaum and Jon Yngve Hardeberg},
  title = {Print quality evaluation and applied colour management in heat-set web offset},
  booktitle = {IARIGAI Conference},
  address = {Leipzig},
  month = {Sep},
  year = {2006}
}
BibTeX:
@inproceedings{Ouglov2006,
  author = {Andrei Ouglov and Ali Alsam and Rune Hjelsvold},
  title = {Gamut Intersection for Image Retrieval},
  booktitle = {CGIV 2006 -- Third European Conference on Color in Graphics, Imaging and Vision},
  address = {Leeds},
  month = {Jun},
  year = {2006}
}
Abstract: The surface reflectance functions of natural and man-made surfaces are invariably smooth. It is desirable to exploit this smoothness in a multispectral imaging system by using as few sen-sors as possible to capture and reconstruct the data. In this paper we investigate the minimum number of sensors to use, while also minimizing reconstruction error. We do this by deriving different numbers of optimized sensors, constructed by transforming the characteristic vectors of the data, and simulating reflectance recov-ery with these sensors in the presence of noise. We find an upper limit to the number of optimized sensors one should use, above which the noise prevents decreases in error. For a set of Munsell reflectances, captured under educated levels of noise, we find that this limit occurs at approximately nine sensors. We also demon-strate that this level is both noise and dataset dependent, by provid-ing results for different magnitudes of noise and different reflectance datasets.
BibTeX:
@article{Connah2006,
  author = {David Connah and Ali Alsam and Jon Y. Hardeberg},
  title = {Multispectral Imaging: How Many Sensors Do We Need?},
  month = {Jan/Feb},
  journal = {The Journal of Imaging Science and Technology},
  year = {2006},
  volume = {50},
  number = {1},
  pages = {45-52},
  note = {ISBN / ISSN: 1062-3701}
}
BibTeX:
@inproceedings{Marin2006,
  author = {Ambroise Marin and David Connah and Audrey Roman and Jon Yngve Hardeberg},
  title = {Robustness of texture parameters for color texture analysis},
  booktitle = {Proc. SPIE Electronic Imaging: Machine Vision Applications in Industrial Inspection XIV},
  address = {San Jose, California},
  month = {Jan},
  year = {2006},
  volume = {6070},
  pages = {47-56}
}
Abstract: Spectral calibration of digital cameras based on the spectral data of commercially available calibration charts is an ill-conditioned problem which has an infinite number of solutions. To improve upon the estimate, different constraints are commonly employed. Traditionally such constraints include: non-negativity, smoothness, uni-modality and that the estimated sensors results in as good as possible response fit.

In this paper, we introduce a novel method to solve a general ill-conditioned linear system with special focus on the solution of spectral calibration. We introduce a new approach based on metamerism. We observe that the difference between two metamers (spectra that integrate to the same sensor response) is in the null-space of the sensor. These metamers are used to robustly estimate the sensor's null-space. Based on this null-space, we derive projection operators to solve for the range of the unknown sensor. Our new approach has a number of advantages over standard techniques: It involves no minimization which means that the solution is robust to outliers and is not dominated by larger response values. It also offers the ability to evaluate the goodness of the solution where it is possible to show that the solution is optimal, given the data, if the calculated range is one dimensional.

When comparing the new algorithm with the truncated singular value decomposition and Tikhonov regularization we found that the new method performs slightly better for the training set with noticeable improvements for the test data.

BibTeX:
@inproceedings{Alsam2006,
  author = {Ali Alsam and Reiner Lenz},
  title = {Calibrating Color Cameras Using Metameric Blacks},
  booktitle = {CGIV 2006 -- Third European Conference on Color in Graphics, Imaging and Vision},
  address = {Leeds, UK},
  year = {2006},
  pages = {75-80},
  note = {ISBN / ISSN: 0-89208-262-3}
}
BibTeX:
@article{Finlayson2006,
  author = {Graham Finlayson and S. D. Hordley and Ali Alsam},
  title = {Investigating von Kries-like adaptation using local linear models},
  journal = {Color Research \& Application},
  year = {2006},
  volume = {31},
  number = {2},
  pages = {90-101}
}
Abstract: This paper demonstrates the feasibility of vector error diffusion for spectral colour reproduction using a multi-channel printing device. Using a simplified spectral printer model we demonstrate that spectral vector error diffusion is able to produce a good spectral match, implicitly solves the problem of printer model inversion and achieves reduced visual noise (stochastic moire) compared to when using standard channel independent scalar error diffusion.
BibTeX:
@inproceedings{Gerhardt2006,
  author = {Jeremie Gerhardt and Jon Y. Hardeberg},
  title = {Spectral Colour Reproduction by Vector Error Diffusion},
  booktitle = {CGIV 2006 -- Third European Conference on Color in Graphics, Imaging and Vision},
  address = {Leeds, UK},
  year = {2006},
  pages = {469-473},
  note = {ISBN / ISSN: 0-89208-262-3}
}
BibTeX:
@conference{Hardeberg2006a,
  author = {Jon Y. Hardeberg},
  title = {RECENT ADVANCES IN ACQUISITION AND REPRODUCTION OF MULTISPECTRAL IMAGES},
  booktitle = {EUSIPCO},
  year = {2006}
}
BibTeX:
@conference{Hardeberg2006b,
  author = {Jon Y. Hardeberg},
  title = {Color science, color management, and color image quality},
  booktitle = {NOBIM},
  year = {2006}
}
Abstract: For the third consecutive year Gjøvik University College and The Norwegian Color Research Laboratory organised an international symposium on colour imaging. Gjøvik Color Imaging Symposium 2005 took place November 30 and December 1, 2005, at Gjøvik University College in Gjøvik, Norway. The first day of the conference focused mainly on applied colour management, whereas the second day was devoted to current topics in colour imaging research, such as advanced colour management, spatial colour imaging, colour vision and colour constancy.
BibTeX:
@techreport{Hardeberg2006,
  author = {Jon Yngve Hardeberg and Peter Nussbaum and Ali Alsam and Ivar Farup},
  title = {Proceedings from Gjøvik Color Imaging Symposium 2005},
  year = {2006}
}
BibTeX:
@article{Nussbaum2006a,
  author = {Peter Nussbaum and Jon Yngve Hardeberg and Svein Erik Skarsbø},
  title = {Print quality evaluation for governmental purchase decisions},
  journal = {Advances in Printing Science and Technology},
  year = {2006},
  volume = {31},
  pages = {189-200},
  note = {ISBN 953-96276-9-9}
}
Abstract: In this paper we present a colorimetric characterization method for digital color cameras, based on hue plane and white point preservation. The present implementation of the method incorporates a series of 3 by 3 matrices, each responsible for the transformation of a subset of camera RGB-values to colorimetric XYZ-values. The method is compared to a choice of three other common characterization methods based on least squares fitting. These other methods are an unconstrained 3 by 3 matrix, a white point preserving 3 by 3 matrix and a second order polynomial.

The methods have been evaluated on real camera signals coming from an Imacon Ixpress professional digital CCD camera, under flash light. The Gretag MacBeth Color Checker and the Color Checker DC charts have been used as test set and training set (respectively). The method is evaluated in combination with a noise susceptibility estimation of the training set samples and a preliminary subdivision of the hue domain, that reduces the amount of test samples needed in the characterization. The noise estimation is based on a geometric analysis in camera chromaticity space.

BibTeX:
@inproceedings{Andersen2005,
  author = {Casper Find Andersen and Jon Yngve Hardeberg},
  title = {Colorimetric Characterization of Digital Cameras Preserving Hue Planes},
  booktitle = {Thirteenth Color Imaging Conference},
  address = {Scottsdale, Arizona},
  month = {Nov},
  year = {2005},
  pages = {141-146},
  note = {ISBN / ISSN: 0-89208-259-3}
}
BibTeX:
@inproceedings{Alsam2005,
  author = {Ali Alsam and Jeremie Gerhardt and Jon Yngve Hardeberg},
  title = {Inversion of the Spectral Neugebauer Printer model},
  booktitle = {AIC Colour 05},
  month = {May},
  year = {2005},
  pages = {44--62}
}
BibTeX:
@inproceedings{Andersen2005a,
  author = {Casper Find Andersen and Jon Yngve Hardeberg},
  title = {Hue plane preserving colorimetric characterization of digital cameras},
  booktitle = {Proceedings of the 10th Congress of the International Colour Association},
  address = {Granada, Spain},
  month = {May},
  year = {2005},
  pages = {287-290},
  note = {ISBN 84-609-5163-4}
}
BibTeX:
@inproceedings{Gouton2005,
  author = {Pierre Gouton and Loic Peigne and Gabrielle Menu and Jon Yngve Hardeberg},
  title = {Using a Standard Colour Camera to Correct Spatial Colorimetric Variation in Videoprojector Display},
  booktitle = {Proceedings of 7th International Conference on Quality Control by Artificial Vision (QCAV2005)},
  address = {Nagoya, Japan},
  month = {May},
  year = {2005},
  pages = {313-318}
}
BibTeX:
@inproceedings{Lau2005,
  author = {Daniel L. Lau and Jon Yngve Hardeberg},
  title = {Geometric alignment of a multiprimary display built by stacking six DLP projectors},
  booktitle = {Proceedings of the 10th Congress of the International Colour Association},
  address = {Granada, Spain},
  month = {May},
  year = {2005},
  pages = {133-136},
  note = {ISBN 84-609-5163-4}
}
Abstract: The partial results of a collaborative research project conducted by researchers at Gjovik University College and Lillehammer University College are described in this paper. The goal of the project is fo develop methods and fools for improving the control of color information in the production and presentation of digital video. The project represenfs a unique attempt to bring together two scientific communities-graphic arts and television/video production - on a theme of common interest, namely color. The color quality achieved by a system for digital distribution and presentation of cinema commercials has been investigated. Results show that the "quality bottleneck" is fhe digital projector. The "business-type" projector does not yield sufficient image quality, especially in large theaters.
BibTeX:
@article{Hardeberg2005a,
  author = {Jon Yngve Hardeberg and Ivar Farup and Gudmund Stjernvang},
  title = {Color quality analysis of a system for digital distribution and projection of cinema commercials},
  month = {Apr},
  journal = {SMPTE Motion Imaging Journal},
  year = {2005},
  volume = {114},
  number = {4},
  pages = {146-151}
}
Abstract: We carried out a CRT monitor based psychophysical experiment to investigate the quality of three colour image difference metrics, the CIE DElta Eab equation, the iCAM and the S-CIELAB metrics. Six original images were reproduced through six gamut mapping algorithms for the observer experiment. The result indicates that the colour image difference calculated by each metric does not directly relate to perceived image difference.
BibTeX:
@inproceedings{Bando2005,
  author = {Eriko Bando and Jon Yngve Hardeberg and David Connah},
  title = {Can gamut mapping quality be predicted by colour image difference formulae?},
  booktitle = {Human Vision and Electronic Imaging X},
  address = {San Jose, California},
  month = {Mar},
  year = {2005},
  pages = {180-191},
  note = {ISBN / ISSN: 0-8194-5639-X}
}
BibTeX:
@article{Mansouri2005,
  author = {A. Mansouri and F. S. Marzani and Jon Yngve Hardeberg and Pierre Gouton},
  title = {Optical Calibration of a Multispectral Imaging System based on Interference Filters},
  month = {Feb},
  journal = {Optical Engineering},
  year = {2005},
  volume = {44},
  number = {2}
}
Abstract: Calibration targets are widely used to characterize imaging devices and estimate optimal proles to map the response of one device to the space of another. The question addressed in this paper is that of how many surfaces in a calibration target are needed to account for the whole target perfectly. To accurately answer this question we first note that the reflectance spectra space is closed and convex. Hence the extreme points of the convexhull of the data encloses the whole target. It is thus sufficientto use the extreme points to represent the whole set. Further, we introduce a volume projection algorithm to reduce the extremes to a user defined number of surfaces such that the remaining surfaces are more important, i.e. account for a larger number of surfaces, than the rest. When testing our algorithm using the Munsell book of colors of 1269 reflectances we found that as few as 110 surfaces were sufficientto account for the rest of the data and as few as 3 surfaces accounted for 86% of the volume of the whole set.
BibTeX:
@inproceedings{Alsam2005a,
  author = {Ali Alsam and Jon Yngve Hardeberg},
  title = {Convex reduction of calibration charts},
  booktitle = {Color Imaging X: Processing, Hardcopy, and Applications},
  address = {San Jose, California},
  month = {Jan},
  year = {2005},
  pages = {38-46},
  note = {ISBN / ISSN: 0-8194-5640-3}
}
Abstract: A method is proposed for performing spectral gamut mapping, whereby spectral images can be altered to fit within an approximation of the spectral gamut of an output device. Principal component analysis (PCA) is performed on the spectral data, in order to reduce the dimensionality of the space in which the method is applied. The convex hull of the spectral device measurements in this space is computed, and the intersection between the gamut surface and a line from the center of the gamut towards the position of a given spectral reflectance curve is found. By moving the spectra that are outside the spectral gamut towards the center until the gamut is encountered, a spectral gamut mapping algorithm is defined. The spectral gamut is visualized by approximating the intersection of the gamut and a 2-dimensional plane. The resulting outline is shown along with the center of the gamut and the position of a spectral reflectance curve. The spectral gamut mapping algorithm is applied to spectral data from the Macbeth Color Checker and test images, and initial results show that the amount of clipping increases with the number of dimensions used.
BibTeX:
@inproceedings{Bakke2005a,
  author = {Arne Magnus Bakke and Ivar Farup and Jon Yngve Hardeberg},
  title = {Multispectral gamut mapping and visualization: a first attempt},
  booktitle = {Color Imaging X: Processing, Hardcopy, and Applications},
  address = {San Jose, California, USA},
  month = {Jan},
  year = {2005},
  pages = {193-200},
  note = {ISBN / ISSN: 0-8194-5640-3}
}
Abstract: In this paper we apply polynomial models to the problem of reflectance recovery for both three-channel and multispectral imaging systems. The results suggest that the technique is superior in terms of accuracy to a standard linear transform and its generalisation performance is equivalent provided that some regularisation is employed. The experiments with the multispectral system suggest that this advantage is reduced when the number of sensors are increased.
BibTeX:
@inproceedings{Connah2005,
  author = {David R. Connah and Jon Yngve Hardeberg},
  title = {Spectral recovery using polynomial models},
  booktitle = {Color Imaging X: Processing, Hardcopy, and Applications},
  address = {San Jose, California},
  month = {Jan},
  year = {2005},
  pages = {65-75},
  note = {ISBN / ISSN: 0-8194-5640-3}
}
Abstract: In this study we investigate the feasibility of using an inexpensive webcam to correct the projection display non-uniformity. Two main approaches are proposed and evaluated, the colorimetric characterization and the global characterization. Both approaches are based on displaying images, which should ideally have uniform color distribution, capturing the displayed image with the webcam, and using this captured image, creating a correction function, which is then applied to images in order to, correct them. Our results show that the feasibility of the proposed methods depends a lot on the qualities of the equipment involved. For standard webcams it is generally difficult to obtain reliable device-independent color measurements needed for the colorimetric characterization.
BibTeX:
@inproceedings{Menu2005,
  author = {Gabrielle Menu and Loic Peigne and Jon Yngve Hardeberg and Pierre Gouton},
  title = {Correcting projection display nonuniformity using a webcam},
  booktitle = {Color Imaging X: Processing, Hardcopy, and Applications},
  address = {San Jose, California},
  month = {Jan},
  year = {2005},
  pages = {364-373},
  note = {ISBN / ISSN: 0-8194-5640-3}
}
Abstract: Recently the use of projection displays has increased dramatically in different applications such as digital cinema, home theatre, and business and educational presentations. Even if the color image quality of these devices has improved significantly over the years, it is still a common situation for users of projection displays that the projected colors differ significantly from the intended ones. This study presented in this paper attempts to analyze the color image quality of a large set of projection display devices, particularly investigating the variations in color reproduction. As a case study, a set of 14 projectors (LCD and DLP technology) at Gjøvik University College have been tested under four different conditions: dark and light room, with and without using an ICC-profile. To find out more about the importance of the illumination conditions in a room, and the degree of improvement when using an ICC-profile, the results from the measurements was processed and analyzed. Eye-One Beamer from GretagMacbeth was used to make the profiles. The color image quality was evaluated both visually and by color difference calculations. The results from the analysis indicated large visual and colorimetric differences between the projectors. Our DLP projectors have generally smaller color gamut than LCD projectors. The color gamuts of older projectors are significantly smaller than that of newer ones. The amount of ambient light reaching the screen is of great importance for the visual impression. If too much reflections and other ambient light reaches the screen, the projected image gets pale and has low contrast. When using a profile, the differences in colors between the projectors gets smaller and the colors appears more correct. For one device, the average DelteE*ab color difference when compared to a relative white reference was reduced from 22 to 11, for another from 13 to 6. Blue colors have the largest variations among the projection displays and makes them therefore harder to predict.
BibTeX:
@inproceedings{Strand2005a,
  author = {Monica Strand and Jon Yngve Hardeberg and Peter Nussbaum},
  title = {Color image quality in projection displays: a case study},
  booktitle = {Image Quality and System Performance II},
  address = {San Jose, California},
  month = {Jan},
  year = {2005},
  pages = {185-195},
  note = {ISBN / ISSN: 0-8194-5641-1}
}
BibTeX:
@inproceedings{Alsam2005b,
  author = {Ali Alsam and David Connah},
  title = {Recovering Natural Reflectances with Convexity},
  booktitle = {Proceedings of the 10th Congress of the International Colour Association},
  address = {Granada, Spain},
  year = {2005},
  pages = {1677-1680},
  note = {ISBN 84-609-5164-2}
}
BibTeX:
@article{Cheung2005,
  author = {Vien Cheung and Changjun Li and Stephen Westland and Jon Yngve Hardeberg and David Connah},
  title = {Characterization of trichromatic color cameras using a new multispectral imaging technique},
  journal = {Journal of Optical Society of America A},
  year = {2005},
  volume = {22},
  number = {7},
  pages = {1231-1240}
}
BibTeX:
@inproceedings{Finlayson2005,
  author = {Graham Finlayson and Ali Alsam},
  title = {Optimal Reduction of Calibration Charts by Integer Programming},
  booktitle = {Proceedings of the 10th Congress of the International Colour Association},
  address = {Granada, Spain},
  year = {2005},
  pages = {1215-1218},
  note = {ISBN 84-609-5164-2}
}
BibTeX:
@inproceedings{Gerhardt2005,
  author = {Jeremie Gerhardt and Jon Yngve Harderberg},
  title = {Spectral vector error diffusion},
  booktitle = {Second Gjøvik Color Symposium},
  year = {2005}
}
BibTeX:
@article{Hardeberg2005b,
  author = {Jon Yngve Hardeberg},
  title = {Colorimetric Scanner Characterization},
  journal = {Acta Graphica},
  year = {2005}
}
BibTeX:
@inproceedings{Hardeberg2005,
  author = {Jon Yngve Hardeberg and Jeremie Gerhardt},
  title = {Caracterisation spectrale d'un systeme d'impression jet d'encre huit encres},
  booktitle = {Revue Traitement du Signal},
  year = {2005},
  volume = {21}
}
Abstract: Human colour vision is the result of a complex process involving topics ranging from physics of light to perception. Whereas the diversity of light entering the eye in principle span an infinite-dimensional vector space in terms of the spectral power distributions, the space of human colour perceptions is three dimensional. One important consequence of this is that a variety of colours can be visually matched by a mixture of only three adequately chosen reference lights. It has been observed that there exists one particular set of monochromatic reference lights that, according to a certain definition, is optimal for producing

colour matches. These reference lights are commonly denoted prime colours. In the present paper, we intend to rigorously show that the existence of prime colours is not particular to the human visual system as sometimes stated, but rather an algebraic consequence of the manner in which a kind of colorimetric functions called colour-matching functions are defined

and transformed. The solution is based on maximisation of a determinant determining the gamut size of the colour space spanned by the prime colours. Cramer’s rule for solving a set of linear equations is an essential part of the proof. By means of examples, it is shown that mathematically the optimal set of reference lights is not unique in general, and that the existence of a maximum determinant is not a necessary condition for the existence of prime colours.

BibTeX:
@article{Hornaes2005,
  author = {Hans Petter Hornæs and Jan Henrik Wold and Ivar Farup},
  title = {Colorimetry and prime colours - a theorem},
  journal = {Journal of Mathematical Biology},
  year = {2005},
  volume = {51},
  number = {2},
  pages = {144-156}
}
Abstract: Solving for a camera's sensors based on its response to the surfaces of a calibration target is an ill-conditioned problem with an infi nite number of possible solutions. To obtain a stable estimate we need to control the solution space by constraining the sensors to match some known physical characteristics e. g. sensors are normally constrained to be positive. The use of constraints limits the uncertainty encountered in sensor recovery and results in im-proved estimates. Unfortunately, it is not possible to know which exact constraints should be used in recovering an unknown sensor. In this paper we present a method to estimate the support (the region where the sensor's sensitivity is not zero) of a sensor prior to recovering it. If the sensor's support is limited this constraint is very stringent and imposing it on the solution space results in a clear reduction in the uncertainty encountered in the solution. In the results section we show that it is indeed possible to recover a sensor's bandwidth based on its response to a set of reflectances.
BibTeX:
@inproceedings{Alsam2004a,
  author = {Ali Alsam and Graham Finlayson},
  title = {Estimating the Bandlimits of an Unknown Sensor},
  booktitle = {Twelfth Color Imaging Conference: Color Science and Engineering Systems, Technologies, Applications},
  address = {Scottsdale, AZ},
  month = {Nov},
  year = {2004},
  pages = {217-222},
  note = {ISBN / ISSN: 0-89208-254-2}
}
Abstract: The gamut of a colour space is defi ned by a number of extreme points. The best inks to achieve an accurate spectral reproduction of a given target are those which span the tar-get's spectral gamut. Using a modi fied non-negative matrix factorization (NMF) algorithm we derive m colorants and their spectral curves such that they are the extreme points of the targets gamut. Using the spectral Neugebauer printing model where eight colorants are assumed we com-pare our new method with existing techniques. Comparison with a set of optimal rotated principal vectors as well as the classical NMF clearly shows that the performance of the new method is superior.
BibTeX:
@inproceedings{Alsam2004,
  author = {Ali Alsam and Jon Yngve Hardeberg},
  title = {Optimal Colorant Design for Spectral Colour Reproduction},
  booktitle = {Twelfth Color Imaging Conference: Color Science and Engineering Systems, Technologies, Applications},
  address = {Scottsdale, AZ},
  month = {Nov},
  year = {2004},
  pages = {157-162},
  note = {ISBN / ISSN: 0-89208-254-2}
}
Abstract: The surface reflectance functions of natural and man made surfaces are invariably smooth. It is desirable to exploit this smoothness in a multispectral imaging system by us-ing as few sensors as possible to capture and reconstruct the data. In this paper we investigate the minimum num-ber of sensors to use, whilst also minimising reconstruc-tion error. We do this by deriving different numbers of optimised sensors, constructed by transforming the char-acteristic vectors of the data, and simulating reflectance recovery with these sensors in the presence of noise. We find an upper limit to the number of optimised sensors one should use, above which the noise prevents decreases in error. For a set of Munsell reflectances, captured under educated levels of noise, we find that this limit occurs at approximately 9 sensors.
BibTeX:
@inproceedings{Connah2004,
  author = {David Connah and Ali Alsam and Jon Yngve Hardeberg},
  title = {Multispectral Imaging: How Many Sensors Do We Need?},
  booktitle = {Twelfth Color Imaging Conference: Color Science and Engineering Systems, Technologies, Applications},
  address = {Scottsdale, AZ},
  month = {Nov},
  year = {2004},
  pages = {53-58},
  note = {ISBN / ISSN: 0-89208-254-2}
}
Abstract: The SGCK gamut mapping algorithm suggested by CIE TC8-03 has been enhanced by introducing a two-step procedure. Firstly, SGCK is used for gamut mapping the image onto a convex hull representation of the reproduction gamut. The resulting image is then further mapped onto a more realistic representation of the reproduction gamut using hue-angle preserving minimum Deab clipping. Panel testing with fifteen test persons, six different test images, and two different printers shows that this technique gives significantly better results than SGCK.
BibTeX:
@inproceedings{Farup2004a,
  author = {Ivar Farup and Jon Yngve Hardeberg and Morten Amsrud},
  title = {Enhancing the {SGCK} Colour Gamut Mapping Algorithm},
  booktitle = {CGIV 2004 -- Second European Conference on Color in Graphics, Imaging and Vision},
  address = {Aachen, Germany},
  month = {Apr},
  year = {2004},
  pages = {520-524},
  note = {ISBN / ISSN: 0-89208-250-X}
}
Abstract: The experimental setup of a 8-channel inkjet printing system intended for spectral color reproduction is proposed. A spectral model of the printer based on the Yule-Nielsen modified spectral Neugebauer equation is presented, discussed, and evaluated experimentally. Although the spectral and colorimetric precision of the printer model leaves room for improvement, the presented research forms an interesting foundation for further research in the field of spectral color reproduction.
BibTeX:
@inproceedings{Hardeberg2004,
  author = {Jon Yngve Hardeberg and Jeremie Gerhardt},
  title = {Characterization of an Eight Colorant Inkjet System for Spectral Color Reproduction},
  booktitle = {CGIV 2004 -- Second European Conference on Color in Graphics, Imaging and Vision},
  address = {Aachen, Germany},
  month = {Apr},
  year = {2004},
  pages = {263-267},
  note = {ISBN / ISSN: 0-89208-250-X}
}
Abstract: The quality of a multispectral color image acquisition system depends on many factors, the spectral sensitivity of the different channels being one of them. In a relatively common setup, a multispectral camera is being implemented by coupling a monochrome digital camera with a set of optical filters, typically mounted on a filter wheel. The properties of these filters is an important component of the system design. Different methods have been proposed for the design or selection of appropri ate filters. In this article we review several methods used for selection of an optimal subset of filters from a set of available filters. The different filter selection meth ods are subjected to a comprehensive evaluation procedure, in which their quality is evaluated mainly in terms of the ability of the resulting system to reconstruct scene spectral reflectances.
BibTeX:
@article{Hardeberg2004a,
  author = {Jon Yngve Hardeberg},
  title = {Filter Selection for Multispectral Color Image Acquisition},
  month = {Mar/Apr},
  journal = {The Journal of Imaging Science and Technology},
  year = {2004},
  volume = {48},
  number = {2},
  pages = {105-110},
  note = {ISBN / ISSN: 1062-3701}
}
BibTeX:
@inproceedings{Alsam2004b,
  author = {Ali Alsam and Jon Yngve Hardeberg},
  title = {Smoothing Jagged Spectra for Accurate Spectral Sensitivities Recovery},
  booktitle = {Proc. International Conference on Computer Vision and Graphics},
  year = {2004}
}
BibTeX:
@inproceedings{Alsam2004c,
  author = {Ali Alsam and Jon Yngve Hardeberg},
  title = {Metamer Set Based Measures of Goodness for Colour Cameras},
  booktitle = {Proc. International Conference on Computer Vision and Graphics},
  year = {2004}
}
Abstract: We carried out a CRT monitor based psychophysical experiment to investigate the quality of three colour image difference metrics, the CIEΔE ab equation, the iCAM and the S-CIELAB metrics. Six original images were reproduced through six gamut mapping algorithms for the observer experiment. The result indicates that the colour image difference calculated by each metric does not directly relate to perceived image difference.
BibTeX:
@conference{Bando2004,
  author = {Eriko Bando and Jon Yngve Hardeberg and David Connah and Ivar Farup},
  title = {Predicting visible image degradation by colour image difference formulae},
  booktitle = {The 5th International Conference on Imaging Science and Hardcopy, volume 25 of Chinese Journal of Scientific Instrument,},
  address = {China},
  year = {2004},
  pages = {121-124}
}
BibTeX:
@techreport{Farup2004b,
  author = {Ivar Farup and Jon Yngve Hardeberg.},
  title = {Colour calibration of an electronic camera system for object recognition.},
  year = {2004}
}
Abstract: The spectral integrator at the University of Oslo consists of a lamp whose light is dispersed into a spectrum by means of a prism. Using a transmissive LCD panel controlled by a computer, certain fractions of the light in different parts of the spectrum is masked out. The remaining spectrum is integrated and the resulting colored light projected onto a dispersing plate. Attached to the computer is also a spectroradiometer measuring the projected light, thus making the spectral integrator a closed-loop system. One main challenge is the generation of stimuli of arbitrary spectral power distributions. We have solved this by means of a computational calibration routine: Vertical lines of pixels within the spectral window of the LCD panel are opened successively and the resulting spectral power distribution on the dispersing plate is measured. A similar procedure for the horizontal lines gives, under certain assumptions, the contribution from each opened pixel. Hereby, light of any spectral power distribution can be generated by means of a fast iterative heuristic search algorithm. The apparatus is convenient for research within the elds of color vision, color appearance modelling, multispectral color imaging, and spectral characterization of devices ranging from digital cameras to solar cell panels.
BibTeX:
@inproceedings{Farup2004,
  author = {Ivar Farup and Thorstein Seim and Jan Henrik Wold and Jon Yngve Hardeberg},
  title = {Generating stimuli of arbitrary spectral power distributions for vision and imaging research},
  booktitle = {Human Vision and Electronic Imaging IX},
  address = {San Jose, California},
  year = {2004},
  pages = {69-79},
  note = {ISBN / ISSN: 0-8194-5195-9}
}
Abstract: In this paper we describe the partial results of a collaborative research project conducted by researchers at Gjøvik University

College and Lillehammer University College. The goal of the project is to develop methods and tools to improve the control of color information in the production and presentation of digital video. The project represents a unique attempt to bring together two scientific communities – graphic arts and television/video production – on a theme of common interest, namely color. We have investigated the color quality achieved by a system for digital distribution and presentation of cinema commercials. Our results show that the “quality bottleneck” is the digital projector. Especially in large theaters, the “business-type” projector does not yield sufficient image quality.

BibTeX:
@conference{Hardeberg2003b,
  author = {Jon Yngve Hardeberg and Ivar Farup and Gudmund Stjernvang},
  title = {Digital cinema commercials in Norway, is the quality good enough?},
  booktitle = {The SMPTE International Conference, D-Cinema and Beyond},
  address = {Milano, Italy},
  month = {Nov},
  year = {2003}
}
Abstract: This study aims to investigate factors affecting the appearance of print on both opaque and transparent substrates. In particular it looks at factors from five categories: the digital input, the printing system, the print, the illumination under which the print is viewed and the viewing environment in which it is viewed. The key method underlying the work described here relies on identifying a range of factors in these categories and having alternative states for each factor, e.g., the substrate factor can be plain paper,glossy paperor newsprint. A reference state is then defined for each factor and alternative states are compared with the reference one factor at a time. The comparison is in terms of color differences between patches of a test chart obtained in the reference and an alternative state. The results for factors are then viewed both individually and by grouping all factors of a given category together. Finally the results indicate the magnitude of the change that can be expected due to a given factor or category and this makes it possible to order factors in terms of the magnitude of visual difference they can cause when altered. Having such an ordered list is then of use both in improving printing systems and in dealing with customer service queries.
BibTeX:
@article{Morovic2003,
  author = {Jan Morovic and Peter Nussbaum},
  title = {Factors Affecting the Appearance of Print on Opaque and Transparent Substrates},
  month = {Nov/Dec},
  journal = {The Journal of Imaging Science and Technology},
  year = {2003},
  volume = {47},
  number = {6},
  pages = {554-564},
  note = {ISBN / ISSN: 1062-3701}
}
Abstract: The quality of a multispectral color image acquisition system depends on many factors, the spectral sensitivity of the different channels being one of them. In a relatively common setup a multispectral camera is being implemented by coupling a monochrome digital camera with a set of optical filters, typically mounted on a filter wheel. The properties of these filters is an important component of the system design.

Different methods have been proposed for the design or selection of appropriate filters. In this paper we review several methods used for selection of an optimal subset of filters from a set of available filters. The different filter selection methods are subjected to a comprehensive evaluation procedure, in which their quality is evaluated mainly in terms of the ability of the resulting system to reconstruct scene spectral reflectances.

BibTeX:
@conference{Hardeberg2003a,
  author = {Jon Y.ngve Hardeberg},
  title = {Filter Selection for Multispectral Color Image Acquisition},
  booktitle = {PICS 2003: The PICS Conference, An International Technical Conference on The Science and Systems of Digital Photography, including the Fifth International Symposium on Multispectral Color Science},
  address = {Rochester, NY},
  month = {May},
  year = {2003},
  pages = {177-182},
  note = {ISBN / ISSN: 0-89208-245-3}
}
BibTeX:
@inproceedings{Hardeberg2003,
  author = {Jon Yngve Hardeberg and Lars Seime and Trond Skogstad},
  title = {Colorimetric characterization of projection displays using a digital colorimetric camera},
  booktitle = {Projection Displays IX (Proceedings of SPIE/IS\&T Volume 5002)},
  address = {Santa Clara, CA},
  month = {Mar},
  year = {2003},
  pages = {51-61},
  note = {ISBN / ISSN: 0-8194-4802-8}
}
BibTeX:
@techreport{Hardeberg2003c,
  author = {Jon Yngve Hardeberg and Ivar Farup and Gudmund Stjernvang},
  title = {Proceedings from Gjøvik Color Imaging Symposium 2003},
  year = {2003}
}
Abstract: Several tools and techniques for the visualization of color gamuts have been presented in the past.We present a short survey on the topic,and conclude that tools with the possibility for interactive color adjustment in some color space are almost absent.Therefore,a new tool which combines the known techniques with the possibility of interactive gamut mapping is presented along with suggestions for future work.The motivation for developing the new tool is threefold:First,it will serve as an important pedagogical tool in the teaching of color engineering.Secondly,we believe that the tool will prove helpful in research related to color reproduction.Finally,we hope that the tool can be used in the production of high quality color images in the future.
BibTeX:
@inproceedings{Farup2002,
  author = {Ivar Farup and Jon Yngve Hardeberg and Arne Magnus Bakke and Ståle Kopperud and Anders Rindal},
  title = {Visualization and Interactive Manipulation of Color Gamuts},
  booktitle = {Tenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, Applications},
  address = {Scottsdale, Arizona, USA},
  month = {Nov},
  year = {2002},
  pages = {250-255},
  note = {ISBN / ISSN: 0-89208-241-0}
}
Abstract: Successful colour management of projection systems depends on knowledge of their characteristics. In this study, two typical portable projectors have been characterised. The two projectors are based on different technologies, Liquid Crystal Display (LCD) and Digital Light Processing (DLP). Measurements were made with a spectroradiometer.

The LCD projector showed good colour additivity. The luminance difference between the sum of primaries and white was 0.33% after correction of the black level. The corresponding value for the DLP projector was 56%. This is due to a non-filtering segment in the filter wheel.

The inter-channel dependency was calculated. The LCD projector showed good independence. For the DLP projector, the additional segment complicates the interpre-tation of the calculated values.

Measurements of the signal input-output relationship have been made. The LCD projector showed a power function response, while the DLP projector showed an S-shaped response. Neither of these are native responses of the projectors, so this is probably a deliberate design.

The chromaticity changes of primary colours and grey depending on the input signal were measured. The chromaticity constancy was poor for both projectors. It was shown that the relatively high black luminance is the dom-inant reason for this.

The spatial uniformity was surprisingly poor. Measurements revealed uniformities down to 20% and 30% for the DLP and the LCD projector, respectively.

Our tests showed that both the intensity and the colour of the background influenced the displayed colour. The average colour differences were found to be Delta E ab =4.83 for the LCD and Delta E ab =2.94 for the DLP projector.

BibTeX:
@inproceedings{Seime2002,
  author = {Lars Seime and Jon Yngve Hardeberg},
  title = {Characterisation of LCD and DLP Projection Displays},
  booktitle = {Tenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, Applications},
  address = {Scottsdale, Arizona, USA},
  month = {Nov},
  year = {2002},
  pages = {277-282},
  note = {ISBN / ISSN: 0-89208-241-0}
}
Abstract: Gamut mapping is an important issue in cross-media publishing. Although much research and development has been performed, consensus on a single gamut mapping algorithm working for a broad range of images and devices has not yet been reached. The recent tendency in the literature suggests that image-dependent gamut mapping work best. To avoid the computational overhead associated with image-dependent gamut mapping algorithms, one solution is to use different rendering intents (absolute or relative colorimetric, perceptual, or saturation) for traditional device gamut based algorithms. The optimal solution, however, still turns out to be image dependent, leaving craftsmanship as the only real alternative. Unfortunately, no intuitive tools – neither software nor hardware – exists for this work, so one is left with trial-and-error based methods with no direct intuitive coupling between parameters adjusted and color corrections obtained. Hence, a software tool for interactive color gamut mapping in a device independent color space such as CIELAB is needed. Such a tool has been developed by the authors. The application allows for interactive manipulation of colors in the 3D color spaces CIELAB, CIEXYZ, and sRGB. Image and device gamuts can be visualized in various ways in the same figure. The view can be changed interactively, and points representing individual pixel colors, groups of pixels, or the image gamut boundary can be moved in color space using a pointing device. Already at the present stage, the application has become a useful tool for understanding mechanisms associated with color image reproduction, as well as for actually performing interactive image-dependent color gamut mapping.
BibTeX:
@conference{Farup2002a,
  author = {Ivar Farup and Jon Yngve Hardeberg},
  title = {Interactive color gamut mapping.},
  booktitle = {The 11th International Printing and Graphics Arts Conference},
  address = {Bordeaux, France},
  month = {Oct},
  year = {2002}
}
Abstract: In this paper we describe the preliminary results of a collaborative research project conducted by researchers at Gjøvik University College and Lillehammer University College. The goal of the project is to develop methods and tools to improve the control of color information in the production and presentation of digital video. The project represents a unique attempt to bring together two scientific communities — graphic arts and television/video production — on a theme of common interest, namely color. Promising results have been obtained by using an innovative color warping algorithm for color correction in editing of digital video.
BibTeX:
@inproceedings{Hardeberg2002c,
  author = {Jon Yngve Hardeberg and Ivar Farup and Øyvind Kolåss and Gudmund Stjernvang},
  title = {Color management for digital video: Color correction in the editing phase.},
  booktitle = {29th International iarigai Research Conference. Proceedings: Advances in Graphic Arts \& Media Technology},
  address = {Lucerne, Switzerland},
  month = {Sep},
  year = {2002}
}
Abstract: The current paper provides methods to correct the artifact known as "red eye" by means of digital color image processing.This artifact is typically formed in amateur photographs taken with a built-in camera flash.To correct red eye artifacts,an image mask is computed by calculating a colorimetric distance between a prototypical reference �?¢â�??¬�?�??red eye�?¢â�??¬ï¿½color and each pixel of the image containing the red eye.Various image processing algorithms such as thresholding,blob analysis,and morphological filtering, are applied to the mask,in order to eliminate noise,reduce errors,and facilitate a more natural looking result.The mask serves to identify pixels in the color image needing correction,and further serves to identify the amount of correction needed. Pixels identified as having red eye artifacts are modified to a substantially monochrome color,while the bright specular reflection of the eye is preserved.
BibTeX:
@article{Hardeberg2002b,
  author = {Jon Yngve Hardeberg},
  title = {Digital Red Eye Removal},
  month = {Jul/Aug},
  journal = {The Journal of Imaging Science and Technology},
  year = {2002},
  volume = {46},
  number = {4},
  pages = {375-379},
  note = {ISBN / ISSN: 1062-3701}
}
Abstract: How many components are needed to represent the spectral reflectance of a surface?What is the dimension of a spectral reflectance?How many image channels are needed for the acquisition of a multispectral colour image? Such and similar questions have been discussed extensively in the literature.We have done a survey of the literature concerning this topic,and have seen that there is a large variation in the answers.We propose a method to quantify the effective dimension of a set of spectral re- . ectances.The method is based on a Principal Component Analysis,and in particular on specific requirements for the accumulated energy of the principal components. We apply the analysis to . ve different databases of spectral re . ectances,and conclude that they have very different statistical properties.The effective dimension of a set of Munsell colour spectra is found to be 18,that of a set of natural object re . ectances 23,while the effective dimension of a set of re . ectances of pigments used in oil painting was only 13.
BibTeX:
@inproceedings{Hardeberg2002,
  author = {Jon Yngve Hardeberg},
  title = {On the Spectral Dimensionality of Object Colors},
  booktitle = {The First European Conference on Color in Graphics, Imaging and Vision (CGIV)},
  address = {Poitiers, France},
  month = {Apr},
  year = {2002},
  pages = {480-485},
  note = {ISBN / ISSN: 0-89208-239-9}
}
Abstract: Color image quality is becoming an increasingly important factor in the consumer imaging industry.Users of imaging devices such as Multi-Function Peripherals (MFP)have increasing expectations to the quality of the reproduced images.In this paper we address the subject of color image quality from a practical point of view,and from the point of view of a provider of imaging technology for consumer MFPs.We show how the notion of color image quality is ultimately tied to the preferences of the end users.Because of this,practical quality evaluation experiments involving a panel of human observers is a very useful tool to quantify color image quality.As an illustration,we then describe a color image quality evaluation experiment,which was carried out in order to benchmark the copy function of two MFP devices.
BibTeX:
@conference{Hardeberg2002a,
  author = {Jon Yngve Hardeberg},
  title = {Color Image Quality for Multi-Function Peripherals},
  booktitle = {PICS 2002: IS\&T's PICS Conference, An International Technical Conference on Digital Image Capture and Associated System, Reproduction and Image Quality Technologies},
  address = {Portland, Oregon, USA},
  month = {Apr},
  year = {2002},
  pages = {76-81},
  note = {ISBN / ISSN: 0-89208-238-0}
}
BibTeX:
@article{Watson1988,
  author = {A. B. Watson and A. Fitzhugh},
  title = {The method of constant stimuli is inefficient},
  journal = {Percept Psychophys.},
  year = {1988},
  volume = {47},
  number = {1},
  pages = {87--91}
}

Please report errors to Marius Pedersen. Created by JabRef on 07/12/2010.