Parallel detection of violations of color constancy

The perceived colors of reflecting surfaces generally remain stable despite changes in the spectrum of the illuminating light. This color constancy can be measured operationally by asking observers to distinguish illuminant changes on a scene from changes in the reflecting properties of the surfaces comprising it. It is shown here that during fast illuminant changes, simultaneous changes in spectral reflectance of one or more surfaces in an array of other surfaces can be readily detected almost independent of the numbers of surfaces, suggesting a preattentive, spatially parallel process. This process, which is perfect over a spatial window delimited by the anatomical fovea, may form an early input to a multistage analysis of surface color, providing the visual system with information about a rapidly changing world in advance of the generation of a more elaborate and stable perceptual representation.

The Computation of Color

This thesis takes an interdisciplinary approach to the study of color vision, focussing on the phenomenon of color constancy formulated as a computational problem. The primary contributions of the thesis are (1) the demonstration of a formal framework for lightness algorithms; (2) the derivation of a new lightness algorithm based on regularization theory; (3) the synthesis of an adaptive lightness algorithm using "learning" techniques; (4) the development of an image segmentation algorithm that uses luminance and color information to mark material boundaries; and (5) an experimental investigation into the cues that human observers use to judge the color of the illuminant. Other computational approaches to color are reviewed and some of their links to psychophysics and physiology are explored.

The neurological basis of conscious color perception in a blind patient

We have studied patient PB, who, after an electric shock that led to vascular insufficiency, became virtually blind, although he retained a capacity to see colors consciously. For our psychophysical studies, we used a simplified version of the Land experiments [Land, E. (1974) Proc. R. Inst. G. B. 47, 23–58] to learn whether color constancy mechanisms are intact in him, which amounts to learning whether he can assign a constant color to a surface in spite of changes in the precise wavelength composition of the light reflected from that surface. We supplemented our psychophysical studies with imaging ones, using functional magnetic resonance, to learn something about the location of areas that are active in his brain when he perceives colors. The psychophysical results suggested that color constancy mechanisms are severely defective in PB and that his color vision is wavelength-based. The imaging results showed that, when he viewed and recognized colors, significant increases in activity were restricted mainly to V1-V2. We conclude that a partly defective color system operating on its own in a severely damaged brain is able to mediate a conscious experience of color in the virtually total absence of other visual abilities.

Color-based surface reflectance separation for scene illumination estimation and rendering

Given the importance of color processing in computer vision and computer graphics, estimating and rendering illumination spectral reflectance of image scenes is important to advance the capability of a large class of applications such as scene reconstruction, rendering, surface segmentation, object recognition, and reflectance estimation. Consequently, this dissertation proposes effective methods for reflection components separation and rendering in single scene images. Based on the dichromatic reflectance model, a novel decomposition technique, named the Mean-Shift Decomposition (MSD) method, is introduced to separate the specular from diffuse reflectance components. This technique provides a direct access to surface shape information through diffuse shading pixel isolation. More importantly, this process does not require any local color segmentation process, which differs from the traditional methods that operate by aggregating color information along each image plane. ^ Exploiting the merits of the MSD method, a scene illumination rendering technique is designed to estimate the relative contributing specular reflectance attributes of a scene image. The image feature subset targeted provides a direct access to the surface illumination information, while a newly introduced efficient rendering method reshapes the dynamic range distribution of the specular reflectance components over each image color channel. This image enhancement technique renders the scene illumination reflection effectively without altering the scene’s surface diffuse attributes contributing to realistic rendering effects. ^ As an ancillary contribution, an effective color constancy algorithm based on the dichromatic reflectance model was also developed. This algorithm selects image highlights in order to extract the prominent surface reflectance that reproduces the exact illumination chromaticity. This evaluation is presented using a novel voting scheme technique based on histogram analysis. ^ In each of the three main contributions, empirical evaluations were performed on synthetic and real-world image scenes taken from three different color image datasets. The experimental results show over 90% accuracy in illumination estimation contributing to near real world illumination rendering effects. ^

Linear Chromatic Adaptation Transform Based on Delaunay Triangulation

Computer vision algorithms that use color information require color constant images to operate correctly. Color constancy of the images is usually achieved in two steps: first the illuminant is detected and then image is transformed with the chromatic adaptation transform ( CAT). Existing CAT methods use a single transformation matrix for all the colors of the input image. The method proposed in this paper requires multiple corresponding color pairs between source and target illuminants given by patches of the Macbeth color checker. It uses Delaunay triangulation to divide the color gamut of the input image into small triangles. Each color of the input image is associated with the triangle containing the color point and transformed with a full linear model associated with the triangle. Full linear model is used because diagonal models are known to be inaccurate if channel color matching functions do not have narrow peaks. Objective evaluation showed that the proposed method outperforms existing CAT methods by more than 21%; that is, it performs statistically significantly better than other existing methods.

Linear Chromatic Adaptation Transform Based on Delaunay Triangulation

Computer vision algorithms that use color information require color constant images to operate correctly. Color constancy of the images is usually achieved in two steps: first the illuminant is detected and then image is transformed with the chromatic adaptation transform ( CAT). Existing CAT methods use a single transformation matrix for all the colors of the input image. The method proposed in this paper requires multiple corresponding color pairs between source and target illuminants given by patches of the Macbeth color checker. It uses Delaunay triangulation to divide the color gamut of the input image into small triangles. Each color of the input image is associated with the triangle containing the color point and transformed with a full linear model associated with the triangle. Full linear model is used because diagonal models are known to be inaccurate if channel color matching functions do not have narrow peaks. Objective evaluation showed that the proposed method outperforms existing CAT methods by more than 21%; that is, it performs statistically significantly better than other existing methods.

Learning Object-Independent Modes of Variation with Feature Flow Fields

We present a unifying framework in which "object-independent" modes of variation are learned from continuous-time data such as video sequences. These modes of variation can be used as "generators" to produce a manifold of images of a new object from a single example of that object. We develop the framework in the context of a well-known example: analyzing the modes of spatial deformations of a scene under camera movement. Our method learns a close approximation to the standard affine deformations that are expected from the geometry of the situation, and does so in a completely unsupervised (i.e. ignorant of the geometry of the situation) fashion. We stress that it is learning a "parameterization", not just the parameter values, of the data. We then demonstrate how we have used the same framework to derive a novel data-driven model of joint color change in images due to common lighting variations. The model is superior to previous models of color change in describing non-linear color changes due to lighting.

Farbkonstanz und Farbkontrast – eine Untersuchung mit Hilfe der farbigen Schatten

Zusammenfassung der Dissertation von Anatol Julian Kallmann Farbkonstanz und Farbkontrast – eine Untersuchung mit Hilfeder farbigen Schatten Die farbigen Schatten werden als ein Spezialfall dessimultanen Farbkontrastes angesehen. Um herauszufinden,warum die farbigen Schatten im Vergleich zur gewöhnlichenDarstellung des simultanen Farbkontrastes so intensiv farbigerscheinen, wurde das Phänomen hinsichtlich derFarbparameter Helligkeit, Sättigung und Farbton analysiert. Der Induktionseffekt scheint weniger von der Sättigung desUmfeldes als vom Leuchtdichtekontrast zwischen dem Umfeldund dem Infeld abhängig zu sein.Das farbig beleuchtete Umfeld wurde von den Versuchspersonenmit einer geringeren Farbsättigung im Verhältnis zurtatsächlichen Umfeldsättigung eingestellt. Die Farbe desUmfeldes wurde unterschiedlich wahrgenommen, wenn keinzentrales Testfeld präsentiert wurde.Dichromaten nahmen das physikalisch weiße Infeld ebenfallsfarbig wahr. Sie stellten Farben auf dem Abgleichbildschirmein, deren Farborte in der CIE-Farbtafel auf denVerwechslungslinien liegen und somit denen der Trichromatenentsprechen. Die Farbbenennungen wichen jedoch von denen derTrichromaten ab. Das Phänomen der farbigen Schatten scheint ein Spezialfallder Farbkonstanz zu sein: Vermutlich dient das Umfeld alshellste Fläche im Gesichtsfeld dem visuellen System alsReferenz. Wenn die Helligkeit des zentralen Infeldeszunimmt, so dass dieses letztlich im visuellen Felddominiert, dann ist das visuelle System in der Lage, es als'weiß' wahrzunehmen. Es verwendet dann wahrscheinlich diesesFeld als Weißreferenz, welches die übrigen Farben imGesichtsfeld bestimmt.

Linear color correction for multiple illumination changes and non-overlapping cameras

Many image processing methods, such as techniques for people re-identification, assume photometric constancy between different images. This study addresses the correction of photometric variations based upon changes in background areas to correct foreground areas. The authors assume a multiple light source model where all light sources can have different colours and will change over time. In training mode, the authors learn per-location relations between foreground and background colour intensities. In correction mode, the authors apply a double linear correction model based on learned relations. This double linear correction includes a dynamic local illumination correction mapping as well as an inter-camera mapping. The authors evaluate their illumination correction by computing the similarity between two images based on the earth mover's distance. The authors compare the results to a representative auto-exposure algorithm found in the recent literature plus a colour correction one based on the inverse-intensity chromaticity. Especially in complex scenarios the authors’ method outperforms these state-of-the-art algorithms.

Sunglasses, traffic signals, and color vision deficiencies

Purpose: To determine (a) the effect of different sunglass tint colorations on traffic signal detection and recognition for color normal and color deficient observers, and (b) the adequacy of coloration requirements in current sunglass standards. Methods: Twenty color-normals and 49 color-deficient males performed a tracking task while wearing sunglasses of different colorations (clear, gray, green, yellow-green, yellow-brown, red-brown). At random intervals, simulated traffic light signals were presented against a white background at 5° to the right or left and observers were instructed to identify signal color (red/yellow/green) by pressing a response button as quickly as possible; response times and response errors were recorded. Results: Signal color and sunglass tint had significant effects on response times and error rates (p < 0.05), with significant between-color group differences and interaction effects. Response times for color deficient people were considerably slower than color normals for both red and yellow signals for all sunglass tints, but for green signals they were only noticeably slower with the green and yellow-green lenses. For most of the color deficient groups, there were recognition errors for yellow signals combined with the yellow-green and green tints. In addition, deuteranopes had problems for red signals combined with red-brown and yellow-brown tints, and protanopes had problems for green signals combined with the green tint and for red signals combined with the red-brown tint. Conclusions: Many sunglass tints currently permitted for drivers and riders cause a measurable decrement in the ability of color deficient observers to detect and recognize traffic signals. In general, combinations of signals and sunglasses of similar colors are of particular concern. This is prima facie evidence of a risk in the use of these tints for driving and cautions against the relaxation of coloration limits in sunglasses beyond those represented in the study.

Effect of optical aberrations on the color appearance of small defocused lights

We investigated influences of optics and surround area on color appearance of defocused, small narrow band photopic lights (1’ arc diameter, λmax 510 - 628 nm) centered within a black annulus and surrounded by a white field. Participants included seven normal trichromats with L- or M-cone biased ratios. We controlled chromatic aberration with elements of a Powell achromatizing lens and corrected higher-order aberrations with an adaptive-optics system. Longitudinal chromatic aberrations, but not monochromatic aberrations, are involved in changing appearance of small lights with defocus. Surround field structure is important because color changes were not observed when lights were presented on a uniform white surround.

Color and texture feature fusion using kernel PCA with application to object-based vegetation species classification

A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.