Refinement of the RLAB Color Space

The prediction of color appearance using the RLAB color space has been tested for a variety of viewing conditions and stimulus types. These tests have shown that RLAB performs well for complex stimuli and not-so-well for simple stimuli. This article reviews the various psychophysical results, interprets their differences, and describes evolutionary enhancements to the RLAB model that simplify it and improve its performance

Color-difference assessment and enhancement for driving headlight simulation

Real-time headlight simulation in driving conditions is used by most car manufacturers to assure the quality, cost, and delivery of headlight engineering design. An important parameter judged by the headlight assessment team is color restitution; indeed, this parameter has to meet the standard of “lamps for road vehicles.” Therefore, the goal of this study was the color assessment and enhancement of a driving headlight simulator. For this purpose, this study was conducted in two phases: the process of constructing two color acceptability scales that directly reflect the perception of two different populations (experts and “naive”), and the assessment of a method based on the chromatic adaptation transform (CAT) for reducing the color difference between real and virtual environments. In the first phase, we conducted two psychophysical experiments (i.e., one for each population), in which the observers had to report their degree of satisfaction about the color difference. These two experiments enabled the creation of two acceptability scales for headlight simulation. In the second phase, we compared the performance of different chromatic transformations; as a result of this comparison, we advise the use of the CAT02 transformation, in order to reduce the color difference for headlight assessment in driving simulation experiments.ANRT (Association Nationale de la Recherche et de la Technologie) and Renaul

Color reproduction of CRT-displayed images as projected transparencies

This thesis evaluated the color appearance predictions of four digital color transforms (Hunt, RLAB, CIELAB, and von Kries) between CRT original images, viewed in a lighted room, and projected slides, viewed in the dark. Calibrated projection of these images required resolution of several complex issues. Upon projection, the slide colors changed. A rapid color shift (on the order of 75 seconds) was followed by a slower, steady degradation which also had to be minimized for accurate image presentation. Therefore, a model of the film behavior was based upon dye absorptivities and color measurements of slides as they were projected. The psychophysical experiments included a comparison between preference choices and memory matching to the CRT original. Two CRT white points were evaluated: D93 and D65. The preference choices were, in fact, distinct from the selected matches. RLAB produced statistically superior matches over any other model for both white points. Model performance was image dependent. Occasionally, CIELAB or von Kries images were equivalent to RLAB. However, CIELAB and von Kries predictions ranged widely in their performance. Hunt\u27s image predictions consistently gave the worst results. Interestingly, RLAB was also elected as the most acceptable choice: judged \u27acceptable\u27 in more than 2/3 of all cases, with a maximum approval of 89%

Edge-Aware Image Color Appearance and Difference Modeling

The perception of color is one of the most important aspects of human vision. From an evolutionary perspective, the accurate perception of color is crucial to distinguishing friend from foe, and food from fatal poison. As a result, humans have developed a keen sense of color and are able to detect subtle differences in appearance, while also robustly identifying colors across illumination and viewing conditions. In this paper, we shall briefly review methods for adapting traditional color appearance and difference models to complex image stimuli, and propose mechanisms to improve their performance. In particular, we find that applying contrast sensitivity functions and local adaptation rules in an edge-aware manner improves image difference predictions

Quantifying mixed adaptation in cross-media color reproduction

An investigation has been undertaken to address the goal set by the CEE Technical committee TC8-04: To investigate the state of adaptation of the visual system when comparing soft-copy images on self-luminous displays and hard copy images viewed under various ambient lighting conditions A set of psychophysical experiments have been conducted for the determination of corresponding colors between printed stimuli under CIE Illuminant D50 simulators and CRT displayed stimuli with a D93 white point. The experiments were completed with 15 observers and 6 different viewing conditions. Analysis was completed to quantify any systematic effects of viewing configuration and to identify the extent to which existing adaptation and appearance models can predict the results. After examining a number of adaptation transforms, preliminary results showed how a simple von Kries type adaptation transform provided the best predictions for all conditions while subsequent iterations of the von Kries transform using simple ratios between the adapting and ambient illuminants improved upon these results. The results also indicated how the CIECAM97s model, given certain conditions, could provide results equal to or better than the von Kries model

Color-appearance modeling for cross-media image reproduction

Five color-appearance transforms were tested under a variety of conditions to determine which is best for producing CRT reproductions of original printed images. The transforms included: von Kries chromatic adaptation, CIELAB color space, RLAB color appearance model, Hunt\u27s color appearance model, and Nayatani\u27s color appearance model. It was found that RLAB produced the best matches for changes in white point, luminance level, and background changes, but did not accurately predict the effect of surround. The ability of CIELAB color space was equal to that of RLAB in many cases, and performed better for changes in surround. Expert observers generated CRT images in one viewing condition that they perceived to match an original image viewed in another condition. This technique produced images that were equal to or better than the best color appearance model tested and is a useful technique to generate color appearance data for developing new models and testing existing models

Color-difference assessment and enhancement for driving headlight simulation

Real-time headlight simulation in driving conditions is used by most car manufacturers to assure the quality, cost, and delivery of headlight engineering design. An important parameter judged by the headlight assessment team is color restitution; indeed, this parameter has to meet the standard of “lamps for road vehicles.” Therefore, the goal of this study was the color assessment and enhancement of a driving headlight simulator. For this purpose, this study was conducted in two phases: the process of constructing two color acceptability scales that directly reflect the perception of two different populations (experts and “naive”), and the assessment of a method based on the chromatic adaptation transform (CAT) for reducing the color difference between real and virtual environments. In the first phase, we conducted two psychophysical experiments (i.e., one for each population), in which the observers had to report their degree of satisfaction about the color difference. These two experiments enabled the creation of two acceptability scales for headlight simulation. In the second phase, we compared the performance of different chromatic transformations; as a result of this comparison, we advise the use of the CAT02 transformation, in order to reduce the color difference for headlight assessment in driving simulation experiments.ANRT (Association Nationale de la Recherche et de la Technologie) and Renaul

Preferred color correction for mixed taking-illuminant placement and cropping

The growth of automatic layout capabilities for publications such as photo books and image sharing websites enables consumers to create personalized presentations without much experience or the use of professional page design software. Automated color correction of images has been well studied over the years, but the methodology for determining how to correct images has almost exclusively considered images as independent indivisible objects. In modern documents, such as photo books or web sharing sites, images are automatically placed on pages in juxtaposition to others and some images are automatically cropped. Understanding how color correction preferences are impacted by complex arrangements has become important. A small number of photographs taken under a variety illumination conditions were presented to observers both individually and in combinations. Cropped and uncropped versions of the shots were included. Users had opportunities to set preferred color balance and chroma for the images within the experiment. Analyses point toward trends indicating a preference for higher chroma for most cropped images in comparison to settings for the full spatial extent images. It is also shown that observers make different color balance choices when correcting an image in isolation versus when correcting the same image in the presence of a second shot taken under a different illuminant. Across 84 responses, approximately 60% showed the tendency to choose image white points that were further from the display white point when multiple images from different taking illuminants were simultaneously presented versus when the images were adjusted in isolation on the same display. Observers were also shown to preserve the relative white point bias of the original taking illuminants

Apport du contenu visuel à l'adaptation chromatique

Les systèmes de capture d'images tels que les scanners, les caméras et les appareils photos numériques, n'ont pas l'habilité à s'adapter dynamiquement au changement d'illumination comme le système visuel humains. Ainsi, pour reproduire fidèlement l'apparence d'une image couleur, les systèmes de formation et de traitement d'images ont besoin d'appliquer une transformation qui convertit les couleurs capturées sous un illuminant d'entrée, vers des couleurs correspondantes sous un illuminant de sortie. Cette transformation est appelée, transformation pour l'adaptation chromatique, connue dans les étapes de formation physique d'image par la balance du blanc. L'adaptation chromatique est une transformation linéaire simple à implémenter. C'est un avantage qui la rend adaptée aux dispositifs à faible énergie, tel que les PDAs et les appareils photos numériques intégrés dans les téléphones portables. Dans ce mémoire, nous abordons l'adaptation chromatique d'un point de vue incluant le contenu visuel de la scène. Dans cette perspective, nous commençons par examiner l'influence de l'adaptation chromatique sur le contenu de l'image. Par la suite, nous proposons une reformulation mathématique de la transformation Sharp en se basant sur le contenu de l'image, et en incluant des contraintes liées à la structure du capteur, tel que le chevauchement entre réponses spectrales des différentes bandes, et la préservation du gamut du capteur