Luminance cues constrain chromatic blur discrimination in natural scene stimuli

Introducing blur into the color components of a natural scene has very little effect on its percept, whereas blur introduced into the luminance component is very noticeable. Here we quantify the dominance of luminance information in blur detection and examine a number of potential causes. We show that the interaction between chromatic and luminance information is not explained by reduced acuity or spatial resolution limitations for chromatic cues, the effective contrast of the luminance cue, or chromatic and achromatic statistical regularities in the images. Regardless of the quality of chromatic information, the visual system gives primacy to luminance signals when determining edge location. In natural viewing, luminance information appears to be specialized for detecting object boundaries while chromatic information may be used to determine surface properties

Variational models for color image processing in the RGB space inspired by human vision Mémoire d'Habilitation a Diriger des Recherches dans la spécialité Mathématiques

La recherche que j'ai développée jusqu'à maintenant peut être divisée en quatre catégories principales : les modèles variationnels pourla correction de la couleur basée sur la perception humaine, le transfert d'histogrammes, le traitement d'images à haute gammedynamique et les statistiques d'images naturelles en couleur. Les sujets ci-dessus sont très inter-connectés car la couleur est un sujetfortement inter-disciplinaire

Spatial summation of individual cones in human color vision.

The human retina contains three classes of cone photoreceptors each sensitive to different portions of the visual spectrum: long (L), medium (M) and short (S) wavelengths. Color information is computed by downstream neurons that compare relative activity across the three cone types. How cone signals are combined at a cellular scale has been more difficult to resolve. This is especially true near the fovea, where spectrally-opponent neurons in the parvocellular pathway draw excitatory input from a single cone and thus even the smallest stimulus projected through natural optics will engage multiple color-signaling neurons. We used an adaptive optics microstimulator to target individual and pairs of cones with light. Consistent with prior work, we found that color percepts elicited from individual cones were predicted by their spectral sensitivity, although there was considerable variability even between cones within the same spectral class. The appearance of spots targeted at two cones were predicted by an average of their individual activations. However, two cones of the same subclass elicited percepts that were systematically more saturated than predicted by an average. Together, these observations suggest both spectral opponency and prior experience influence the appearance of small spots

Understanding perceived quality through visual representations

The formatting of images can be considered as an optimization problem, whose cost function is a quality assessment algorithm. There is a trade-off between bit budget per pixel and quality. To maximize the quality and minimize the bit budget, we need to measure the perceived quality. In this thesis, we focus on understanding perceived quality through visual representations that are based on visual system characteristics and color perception mechanisms. Specifically, we use the contrast sensitivity mechanisms in retinal ganglion cells and the suppression mechanisms in cortical neurons. We utilize color difference equations and color name distances to mimic pixel-wise color perception and a bio-inspired model to formulate center surround effects. Based on these formulations, we introduce two novel image quality estimators PerSIM and CSV, and a new image quality-assistance method BLeSS. We combine our findings from visual system and color perception with data-driven methods to generate visual representations and measure their quality. The majority of existing data-driven methods require subjective scores or degraded images. In contrast, we follow an unsupervised approach that only utilizes generic images. We introduce a novel unsupervised image quality estimator UNIQUE, and extend it with multiple models and layers to obtain MS-UNIQUE and DMS-UNIQUE. In addition to introducing quality estimators, we analyze the role of spatial pooling and boosting in image quality assessment.Ph.D

Aesthetic ratings of northern forest scenes : the effects of spatiochromatic stimulus attributes in silvicultural landscape images

The Environmental Impact Assessment Act, through the use of The Social Impact Assessment (SIA) established public participation in environmental decision-making. The concern for landscape aesthetics has been one among many issues, and has received special prominence in the case of timber management in Ontario’s northern forests. Research on landscape perception has contributed to the debate. Typically such studies use rating methods to evaluate public perceptions of landscape quality, beauty and/or aesthetics. However, these studies did not consider whether luminance-, spatial- and/or chromatic variations influence aesthetic judgments in the natural environment. From that perspective, this study is an extension of earlier visual search studies that investigated the effects of specific spatial and chromatic properties of target stimuli into the realm of landscape perception. Based on the findings from this extensive body of work, we predicted that high levels of chromatic conspicuity and extrinsic (or unnatural) regularity in spatial patterning in a wilderness scene would have a negative impact on the public perception of forest landscapes. Three conditions representing landscape elements (targets) that simulate silvicultural practices were manipulated using Adobe Photoshop software. The targets were a checkerboard clear-cut, an irregular cut, and a roadway. The chromaticity of each target was defined by the target midtones (average across 400 pixels, or 1° subtense). The “neutral” chromaticity was equated across checkerboard and irregular patches. The chromaticity of the targets was modulated (7 steps) along red-green axes in Commission Internationale de l’Eclairage (CIE) 1931 chromaticity space. All presentations were done on a high-resolution colour monitor (CRT). Each of the targets was presented in five background conditions of oblique aerial photographs of coniferous trees with and without a lake to determine position bias and target/lake proximity effects. Each of the 16 observers per background condition (N=80) was presented 84 randomized landscapes from a total of 420 images. Data interpretation was conducted using a 4-way multifactor design with repeated measures on 3 factors (5 randomized backgrounds X 3 spatial targets X 7 target chromaticities X 4 quadrant locations). Results showed that varying the spatiochromatic properties of the silvicultural targets and their locations significantly influenced the perceived beauty of northern forest landscapes. Patches in a scene that had spatial regularity and a colour appearance that was shifted towards the “reds” were given the lowest ratings. Comparable situations can be observed in real scenes that have undergone recent harvesting operations