Showing papers on "Color constancy published in 2004"

Retinex processing for automatic image enhancement

Abstract: There has been a revivification of interest in the Retinex computation in the last six or seven years, especially in its use for image enhancement. In his last published concept (1986) for a Ret- inex computation, Land introduced a center/surround spatial form, which was inspired by the receptive field structures of neurophysi- ology. With this as our starting point, we develop the Retinex con- cept into a full scale automatic image enhancement algorithm—the multiscale Retinex with color restoration (MSRCR)—which com- bines color constancy with local contrast/lightness enhancement to transform digital images into renditions that approach the realism of direct scene observation. Recently, we have been exploring the fun- damental scientific questions raised by this form of image process- ing. 1. Is the linear representation of digital images adequate in visual terms in capturing the wide scene dynamic range? 2. Can visual quality measures using the MSRCR be developed? 3. Is there a canonical, i.e., statistically ideal, visual image? The answers to these questions can serve as the basis for automating visual as- sessment schemes, which, in turn, are a primitive first step in bring- ing visual intelligence to computers. © 2004 SPIE and IS&T.

Shades of Gray and Colour Constancy

Abstract: Colour constancy is a central problem for any visual system performing a task which requires stable perception of the colour world. To solve the colour constancy problem we estimate the colour of the prevailing light and then, at the second stage, remove it. Two of the most commonly used simple techniques for estimating the colour of the light are the Grey-World and Max-RGB algorithms. In this paper we begin by observing that this two colour constancy computations will respectively return the right answer if the average scene colour is grey or the maximum is white (and conversely, the degree of failure is proportional to the extent that these assumptions hold). We go on to ask the following question: “ Would we perform better colour constancy by assuming the scene average is some shade of grey?”. We give a mathematical answer to this question. Firstly, we show that Max-RGB and Grey-World are two instantia-tions of Minkowski norm. Secondly, that for a large cali-brated dataset L6 norm colour constancy works best over-all (we have improved the performance achieved by a sim-ple normalization based approach). Surprisingly we found performance to be similar to more elaborated algorithm.

Difference scaling of gloss: nonlinearity, binocularity, and constancy.

Abstract: Gloss is an attribute of visual appearance that originates from the geometrical distribution of the light reflected by the surface. We used the maximum likelihood difference scaling (MLDS) procedure (L.T. Maloney & J. N. Yang, 2003) to estimate gloss scales over an extended range. Observers' judgments were obtained for a series of 10 black, coated samples for two directions of illumination, in binocular and monocular vision. The results showed a nonlinear relation between gloss percept and instrumental specular gloss values. Sensitivity is higher at extreme scale values than in the middle. In binocular vision, the sensitivity to gloss is higher than in monocular vision exclusively for high gloss levels. Lastly, we found that gloss difference scales, when expressed in terms of the samples rather than the photometric characteristics, vary little with the direction of illumination. Gloss scaling thus seems to be independent of the geometrical variations of the luminous flux at the surface of the sample. By analogy with the term "color constancy," we call this property "gloss constancy."

Color constancy through inverse-intensity chromaticity space.

Abstract: Existing color constancy methods cannot handle both uniformly colored surfaces and highly textured surfaces in a single integrated framework. Statistics-based methods require many surface colors and become error prone when there are only a few surface colors. In contrast, dichromatic-based methods can successfully handle uniformly colored surfaces but cannot be applied to highly textured surfaces, since they require precise color segmentation. We present a single integrated method to estimate illumination chromaticity from single-colored and multicolored surfaces. Unlike existing dichromatic-based methods, the proposed method requires only rough highlight regions without segmenting the colors inside them. We show that, by analyzing highlights, a direct correlation between illumination chromaticity and image chromaticity can be obtained. This correlation is clearly described in "inverse-intensity chromaticity space," a novel two-dimensional space that we introduce. In addition, when Hough transform and histogram analysis is utilized in this space, illumination chromaticity can be estimated robustly, even for a highly textured surface.

Self quotient image for face recognition

Abstract: The reliability of facial recognition techniques is often affected by the variation of illumination, such as shadows and illumination direction changes. In this paper, we present a novel framework, called the self-quotient image, for the elimination of the lighting effect in the image. Although this method has a similar invariant form to the quotient image by Shashua etc. (2001), it does not need the alignment and bootstrap images. Our method combines the image processing technique of edge-preserved filtering with the Retinex applications of by Jobson, et al., (1997) and Gross and Brajovie (2003). We have analyzed this algorithm with a 3D imaging model and formulated the conditions where illumination-invariant and -variant properties can be realized, respectively. A fast anisotropic filter is also presented. The experiment results show that our method is effective in removing the effect of illumination for robust face recognition.

From Retinex to Automatic Color Equalization: issues in developing a new algorithm for unsupervised color equalization

Abstract: We present a comparison between two color equalization algorithms: Retinex, the famous model due to Land and McCann, and Automatic Color Equalization (ACE), a new algorithm recently presented by the authors. These two algorithms share a common approach to color equalization, but different computational models. We introduce the two models focusing on differences and common points. An analysis of their computational characteristics illustrates the way the Retinex approach has influenced ACE structure, and which aspects of the first algorithm have been modified in the second one and how. Their interesting equalization properties, like lightness and color constancy, image dynamic stretching, global and local filtering, and data driven dequantization, are qualitatively and quantitatively presented and compared, together with their ability to mimic the human visual system. © 2004 SPIE and IS&T.

Information limits on neural identification of colored surfaces in natural scenes.

Abstract: If surfaces in a scene are to be distinguished by their color, their neural representation at some level should ideally vary little with the color of the illumination. Four possible neural codes were considered: von-Kries-scaled cone responses from single points in a scene, spatial ratios of cone responses produced by light reflected from pairs of points, and these quantities obtained with sharpened (opponent-cone) responses. The effectiveness of these codes in identifying surfaces was quantified by information-theoretic measures. Data were drawn from a sample of 25 rural and urban scenes imaged with a hyperspectral camera, which provided estimates of surface reflectance at 10-nm intervals at each of 1344 × 1024 pixels for each scene. In computer simulations, scenes were illuminated separately by daylights of correlated color temperatures 4000 K, 6500 K, and 25,000 K. Points were sampled randomly in each scene and identified according to each of the codes. It was found that the maximum information preserved under illuminant changes varied with the code, but for a particular code it was remarkably stable across the different scenes. The standard deviation over the 25 scenes was, on average, approximately 1 bit, suggesting that the neural coding of surface color can be optimized independent of location for any particular range of illuminants.

Does human color constancy incorporate the statistical regularity of natural daylight

Abstract: The chromaticities of natural daylights cluster around the blackbody locus. We investigated whether the mechanisms that mediate human color constancy embody this statistical regularity of the natural environment, so that constancy is best when the illuminant change is one likely to occur. Observers viewed scenes displayed on a CRT-based stereoscope and adjusted a test patch embedded in the scene until it appeared achromatic. Scenes were rendered using physics-based graphics software (RADIANCE) coupled with custom extensions that ensured colorimetric accuracy. Across conditions, both the simulated illuminant and the simulated reflectance of scene objects were varied. Achromatic settings from paired conditions were used to compute a constancy index (CI) that characterizes the stability of object appearance across the two illuminants of the pair. Constancy indices were measured for four illuminant changes from a Neutral illuminant (CIE D65). Two of these changes (Blue and Yellow) were consistent with the statistics of daylight, whereas two (Green and Red) were not. The results indicate that constancy was least across the Red change, as one would expect for the statistics of natural daylight. Constancy for the Green direction, however, exceeded that for the Yellow illuminant change and was comparable to that for the Blue. This result is difficult to reconcile with the hypothesis that mechanisms of human constancy incorporate the statistics of daylights. Some possible reasons for the discrepancy are discussed.

Color contrast: a contributory mechanism to color constancy.

Abstract: Color constancy--by which objects tend to appear the same color under changes in illumination--is most likely achieved by several mechanisms, operating at different levels in the visual system. One powerful contributory mechanism is simultaneous spatial color contrast. Under changes in natural illumination the spatial ratios of within-type cone excitations between natural surfaces tend to be preserved (Foster and Nascimento, 1994); therefore, the neural encoding of colors as spatial contrasts tends to achieve constancy. Several factors are known to influence the strength of chromatic contrast induction between surfaces, including their relative luminance, spatial scale, spatial configuration and context (Ware and Cowan, 1982; Zaidi et al., 1991). Here we test the hypothesis that color contrast is weakened by differences between surfaces which indicate that they may be under distinct illuminants. We summarize psychophysical measurements of the effects of relative motion, relative depth and texture differences on chromatic contrast induction. Of these factors, only texture differences between surfaces weaken chromatic contrast induction. We also consider neurophysiological and neuropsychological evidence and conclude that the mechanisms which mediate local chromatic contrast effects are sited at low levels in the visual system, in primary visual cortex (V1) or below, prior to image segmentation mechanisms which require computation of relative depth or motion. V1 and lower areas may therefore play a larger role in color constancy than previously thought.

Robust segmentation and tracking of colored objects in video

Abstract: Segmenting and tracking of objects in video is of great importance for video-based encoding, surveillance, and retrieval. However, the inherent difficulty of object segmentation and tracking is to distinguish changes in the displacement of objects from disturbing effects such as noise and illumination changes. Therefore, in this paper, we formulate a color-based deformable model which is robust against noisy data and changing illumination. Computational methods are presented to measure color constant gradients. Further, a model is given to estimate the amount of sensor noise through these color constant gradients. The obtained uncertainty is subsequently used as a weighting term in the deformation process. Experiments are conducted on image sequences recorded from three-dimensional scenes. From the experimental results, it is shown that the proposed color constant deformable method successfully finds object contours robust against illumination, and noisy, but homogeneous regions.

Capturing a black cat in shade: past and present of Retinex color appearance models

Abstract: This work recounts the research on capturing real-life scenes, calculating appearances, and rendering sensations on film and other limited dynamic-range media. It describes the first pat- ents, a hardware display used in Land's Ives Medal Address in 1968, the first computer simulations using 20 324 pixel arrays, psy- chophysical experiments and computational models of color con- stancy and dynamic range compression, and the Frankle-McCann computationally efficient retinex image processing of 512 3512 im- ages. It includes several modifications of the original approach, in- cluding recent models of human vision and gamut-mapping applica- tions. This work emphasizes the need for parallel studies of psychophysical measurements of human vision and computational algorithms used in commercial imaging systems. © 2004 SPIE and IS&T. (DOI: 10.1117/1.1635831)

Mechanism of Color Constancy.

Abstract: There are two widely held theories of color constancy based on very different mechanisms: Chromatic Adaptation and Spatial Comparisons. Chromatic Adaptation is based on the change of retinal sensitivity in response to changes in incident light. The Spatial Comparisons mechanism is insensitive to illumination changes because it uses ratios of radiance from different pixels in the image. A spatially uniform increase in long-wave light increases both the numerator and the denominator by the same factor, so that the ratio remains constant. Spatial Comparisons of all pixels in the image synthesize a constant image, when the long-, middle-, and short-wave images are processed independently. Measurements of color appearance in constancy experiments have shown that there are small consistent departures from perfect constancy. This paper measures the color and magnitude of these departures from perfect color constancy. It tests the hypothesis that these departures provide a signature of the underlying constancy mechanism. Since Chromatic Adaptation mechanism is specific for illumination, then these departures are predicted to be the same, regardless of the color of the paper. Since the Spatial Comparisons mechanism is based on the Integrated Reflectance of the paper, gray papers should show greater constancy than colored papers. In other words, the signature of Chromatic Adaptation is constant departures for each illumination, while the signature of Spatial Comparisons is variable departures for each reflectance. This paper measures the color matches for a yellow, a purple and a gray paper in 27 different illuminants.

Color constancy under changes in reflected illumination.

Abstract: Distinct physical processes can change the spectrum of the illumination that impinges on a surface. Here we consider two such changes. The first is a change in the spectrum of the light source that provides the scene illumination (light source change). The second is a change in the reflectance of a surface located near a test surface of interest (reflected light change). A color constant visual system must compensate for changes caused by both of these physical processes. We report measurements of constancy with respect to reflected light changes and compare them to results from a recent experiment that examines constancy across light source changes. Observers viewed synthetic images rendered from three-dimensional scene descriptions and displayed on a CRT-based stereoscope. They made achromatic adjustments to test surfaces embedded in the images. The degree of constancy varied with the color direction of the illuminant change, and the variation was similar for reflected light and light source changes. The overall level of constancy was lower for reflected light changes than for light source changes. A second experiment suggests that for our conditions, constancy across reflected light changes is driven almost entirely by changes in the local surround of the test. In a third experiment, observers made asymmetric matches across both types of illuminant change. Here the matches were essentially identical across both types of illuminant change.

Bio-inspired color image enhancement

Abstract: Capturing and rendering an image that fulfills the observer's expectations is a difficult task. This is due to the fact that the signal reaching the eye is processed by a complex mechanism before forming a percept, whereas a capturing device only retains the physical value of light intensities. It is especially difficult to render complex scenes with highly varying luminances. For example, a picture taken inside a room where objects are visible through the windows will not be rendered correctly by a global technique. Either details in the dim room will be hidden in shadow or the objects viewed through the window will be too bright. The image has to be treated locally to resemble more closely to what the observer remembers. The purpose of this work is to develop a technique for rendering images based on human local adaptation. We take inspiration from a model of color vision called Retinex. This model determines the perceived color given spatial relationships of the captured signals. Retinex has been used as a computational model for image rendering. In this article, we propose a new solution inspired by Retinex that is based on a single filter applied to the luminance channel. All parameters are image-dependent so that the process requires no parameter tuning. That makes the method more exible than other existing ones. The presented results show that our method suitably enhances high dynamic range images.

Comparison of the accuracy of different white-balancing options as quantified by their color constancy

Abstract: Six different methods for white-balancing digital images were compared in terms of their ability to produce white-balanced colors close to those viewed under a specific viewing illuminant. The six methods were: native camera RGB, XYZ, CAM02, ITU Rec BT.709 RGB, sharpened camera RGB, and illuminant-dependent. 4096 different sets of camera sensitivities were synthesized; 170 objects were evaluated under a canonical viewing illuminant (D65) and six additional taking illuminants (A, D50, D75, F2, F7, and F11). Each white balancing method was exercised in turn, and the mean and 90th percentile ΔE*ab were determined. We found that illuminant-dependent characterization produced the best results, sharpened camera RGB and native camera RGB were next best, XYZ and CAM02 were often not far behind, and balancing in the -709 primaries was significantly worse. We recommend that, whenever the illuminant is identified, the illuminant-dependent technique be employed because of its superior performance.

Color image enhancement using a Retinex-based adaptive filter

Abstract: We present a new adaptation of Retinex to enhance the rendering of high dynamic range digital color images. The image is processed using an adaptive Gaussian filter. The shape of the filter basis is adapted to follow the high contrasted edges of the image. In this way, the artifacts introduced by a circularly symmetric filter at the border of high contrasted areas are reduced. This method provides a way of rendering natural images that is inspired by human local adaptation. It is included into a framework that takes raw linear images or radiance maps and outputs 24-bit images rendered for display.

Dynamic Color Object Recognition Using Fuzzy Logic

Abstract: This paper presents a novel Logit-Logistic Fuzzy Color Constancy (LLFCC) algorithm and its variants for dynamic color object recognition. Contrary to existing color constancy algorithms, the proposed scheme focuses on manipulating a color locus depicting the colors of an object, and not stabilizing the whole image appearance per se. In this paper, a new set of adaptive contrast manipulation operators is introduced and utilized in conjunction with a fuzzy inference system. Moreover, a new perspective in extracting color descriptors of an object from the rg-chromaticity space is presented. Such color descriptors allow for the reduction of the effects of brightness/darkness and at the same time adhere to human perception of colors. The proposed scheme tremendously cuts processing time by simultaneously compensating for the effects of a multitude of factors that plague the scene of traversal, eliminating the need for image pre-processing steps. Experiment results attest to its robustness in scenes with multiple white light sources, spatially varying illumination intensities, varying object position, and presence of highlights.

Photo sensor for standardized color measurement

Abstract: The invention is directed to a photosensor for color measurement based on three spectral components, particularly for highly accurate color measurement for testing and guaranteeing color constancy in engineered surfaces and consumer articles of any kind. The object of the invention, to find a novel possibility for color measurement based on a three-range method with color measurement values generated by preceding interference filters with different spectral responses which permits a virtually true-color measurement in conformity with standards in a simple manner without costly reference light calibration, is met according to the invention in that the photosensor comprises at least three partial surfaces which are covered by different interference filters adapted to the X-, Y- and Z-spectral characteristic of the human eye, each partial surface being arranged so as to be uniformly distributed in a sector-shaped manner and so as to cover the same area around a center with passivated webs located therebetween, and every partial surface is provided with an interference filter whose transmission characteristic over the wavelength of the light to be measured spectrally is adapted to the response of the human eye, wherein the spectral components passed by the interference filters approximate the normal spectral value functions of the human eye in color coordinates of the color space.

A system for the acquisition of reproducible digital skin lesions images

Abstract: A major issue concerning the design and implementation of an image acquisition system for skin lesions is its ability to capture reproducible images. The reproducibility is considered essential for image analysis and for the comparison of sequential images during follow-up studies. This paper describes a prototype image acquisition system that includes a standardized illumination and capturing geometry with polarizing filters and a series of software corrections: Calibration to Black, White and Color for color constancy, Internal camera Parameters adjustment and Pose extraction for stereo vision, Shading correction and Noise Filtering for color quality. The validity of the calibration procedure and the images' reproducibility were tested by capturing sample images in three different lighting conditions: dark, medium and intense lighting. For each case the average values of the three color planes RGB and their standard deviations were calculated; the measured error differences ranged between 0.7 and 12.9 (in the 0-255 scale). Preliminary experiments for stereo measurements provided repeatability of about 0.3 mm. The above results demonstrate the reproducibility of the captured images at a satisfactory level. The developed prototype was also evaluated clinically, for its ability to support the construction of knowledge-based decision systems and for telemedicine, thus to support telemedical sessions in dermatology.

An efficient face recognition for variant illumination condition

Abstract: The aim of this paper is to investigate how to preprocess the input face image for the task of robust face recognition, especially in changing illumination environment Changing illumination poses a most challenging problem in face recognition Previous research for illumination compensation has been investigated We found that the performance of each preprocessing method for compensating illumination is highly affected by the working illumination environment This paper proposes an adaptive filter block for efficient face recognition Since no priori knowledge of the system working environment can be assumed, illumination environments are analyzed by an unsupervised learning method, fuzzy ART The proposed method can decide an optimal configuration of filter block by exploring the filter combination and the associated parameters to unknown illumination conditions The filter block includes retinex filter, histogram equalization filter The proposed method has been tested in robust face recognition in varying illumination conditions Extensive experiments show that the proposed system can achieve very encouraging performance in varying illumination environments

A method to speed-up retinex-type algorithms

Abstract: An apparatus, and a corresponding method, are usable for speeding up Retinex processing of an input image. The apparatus includes a down sample module (110) having a sub-sampling algorithm, where sub-sampled images of the input image are produced, and a non-linear illumination estimation module (120) that receives the sub-sampled images and produces corresponding interim illumination estimations. Finally, the apparatus includes an up sample module (140) including one or more up-sampling algorithms (150). The interim illumination estimations are interpolated (152) to produce an illumination estimation, and the illumination estimation is usable to perform a Retinex correction to the input image.

Study of instantaneous color constancy mechanisms in human vision

Abstract: We have extended the experiments of McCann et al. by incorporating their Mondrian stimulus into a dynamic color matching (DCM) technique that allows the subject to match accurately the color of any test patch under sequential changes of illuminant. Changes in the perceived color of a central test stimulus as a result of surround illuminant changes are investigated in a number of successful binocular and dichoptic experiments. The contribution made by distant patches to instantaneous color constancy (ICC) is found to be small, with the immediate surround (i.e., ,1.5-deg separation) contributing most of the constancy effect. A modified DCM technique was developed to study ICC in patients with unilateral damage to the primary visual cortex. The results of this part of the study suggest that retinal mechanisms do not contribute to ICC. Experiments carried out in subjects with cerebral achromatopsia reveal the existence of hidden constancy, even when the subjects are unable to see the result of functioning ICC mechanisms. Dichoptic implementation of the DCM technique yields reduced but significant ICC index values with more equal contribution from distant surrounds. Our findings suggest that early stage processing of chromatic information in the primary visual cortex contributes significantly to ICC, with only small contributions from extrastriate areas of the cortex. © 2004 SPIE and IS&T. [DOI: 10.1117/1.1636491]

Color constancy by asymmetric color matching with real objects in three-dimensional scenes.

Abstract: Color matching experiments use, in general, stimuli that are poor representations of the natural world. The aim of this work was to compare the degree of color constancy for a range of illuminant pairs using a new matching technique that uses both real objects and three-dimensional (3-D) real scenes. In the experiment, observers viewed a 3-D real scene through a large beamsplitter that projects on the right-hand side of the scene (match scene), the virtual image of a 3-D object (match object) such it appeared part of the scene. On the left-hand side of the scene (test scene), observers viewed a symmetrical scene containing a test object identical to the match object. Test and match objects were both surrounded by the same reflectances with identical spatial arrangement. The illuminant on the test scene had always a correlated color temperature of 25,000 K. The illuminant on the match scene could be any of seven different illuminants with correlated color temperatures in the range 25,000 K-4000 K. In each trial, the observers, who were instructed to perform surface color matches, adjusted the illuminant on the match object. Constancy indices were very high (0.81-0.93), varied with the color of the match object, and increased with the extent of the illuminant change. Observer's mismatches, however, were independent of the extent of the illuminant change.