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The light reflected from an object depends on its reflectance, the illumination, and the pose of the object within the scene. An observer is called lightness constant if the perceived reflectance (lightness) of achromatic objects stays the same despite variation in object-extrinsic factors such as illumination and pose. Here, we used a dissimilarity scaling task to measure lightness constancy as the intensity of the illuminant and the slant of test surfaces were varied. Across two experiments, we had observers rate the dissimilarity of flat grayscale test stimulus pairs. The test stimuli were real illuminated surfaces, not computer simulations. Each test stimulus was seen in its own illuminated chamber, with the two chambers viewed side by side. We varied test surface reflectance, chamber illumination intensity, and the slant of the test in relation to the single light source in each chamber. Data were analyzed using nonmetric multidimensional scaling. The data were well-described by a one-dimensional perceptual representation. This representation was consistent across observers, revealed partial lightness constancy with respect to a change in illumination intensity, and no lightness constancy with respect to changes in surface slant. An additional experiment using a matching procedure and the same stimulus set, however, revealed moderate constancy with respect to changes in surface slant. The difference in results between the two methods is interesting, but not understood.

This paper describes the design and performance of an image capture simulator. The general model underlying the simulator assumes that the image capture device contains multiple classes of sensors with different spectral sensitivities and that each sensor responds in a known way to irradiance over most of its operating range. The input to the simulator is a set of narrow-band images of the scene taken with a custom-designed hyperspectral camera system. The parameters for the simulator are the number of sensor classes, the sensor spectral sensitivities, the noise statistics and number of quantization levels for each sensor class, the spatial arrangement of the sensors and the exposure duration. The output of the simulator is the raw image data that would have been acquired by the simulated image capture device. To test the simulator, we acquired images of the same scene both with the hyperspectral camera and with a calibrated Kodak DCS-200 digital color camera. We used the simulator to predict the DCS-200 output from the hyperspectral data. The agreement between simulated and acquired images validated the image capture response model and our simulator implementation. We believe the simulator will provide a useful tool for understanding the effect of varying the design parameters of an image capture device.

A model for chromoluminance pattern detection and pedestal effects is described. This model has five stages. The stimulus is first processed by the cone array and then by color-spatial linear operators. The outputs of the linear operators may be expressed as weighted sums of cone contrasts over space. There are three opposite sign pairs of linear spatial operators in the model. Their spectral tuning at each point in space is similar to the luminance, green/red and blue/yellow mechanisms in color opponent models, but their sensitivity to cone inputs varies as a function of space. The operators in each pair are the same except that the signs of the cone inputs in one are the opposite of those in the other. A non-linear response operator follows each linear operator. It receives two inputs, one excitatory and the other divisive inhibitory. The excitatory input is the half-wave rectified output of one of the linear operators. The inhibitory input is a non-linear sum of all linear operator outputs. The non-linear response operator raises the excitatory input to a power, and divides it by the inhibitory input plus a constant to produce the response. The detection variable is computed by combining the difference in response to target-plus-pedestal and pedestal alone across the three non-linear operators. The model accounts well for the large data set presented in the companion paper and is generally consistent with other results in the literature. The spectral sensitivities of the inferred chromoluminance pattern mechanisms are similar to those obtained with different methods. The data set is shown to be inconsistent with several other models.

Color constancy is our ability to perceive constant surface colors despite changes in illumination. Although color constancy has been studied extensively, its mechanisms are still largely unknown. Three classic hypotheses are that constancy is mediated by local adaptation, by adaptation to the spatial mean of the image, or by adaptation to the most intense image region. We measure color constancy under nearly natural viewing conditions, by using a design that allows us to test these three hypotheses directly. By suitable stimulus manipulation, we are able to titrate the degree of constancy between 11% and 83%, indicating that we have achieved good laboratory control. Our results rule out all three classic hypotheses and thus suggest that there is more to constancy than can be easily explained by the action of simple visual mechanisms.

The Psychophysics Toolbox is a software package that supports visual psychophysics. Its routines provide an interface between a high-level interpreted language (MATLAB on the Macintosh) and the video display hardware. A set of example programs is included with the Toolbox distribution.

Retinal image alignment is fundamental to many applications in diagnosis of eye diseases. In this paper, we address the problem of landmark matching based retinal image alignment. We propose a novel landmark matching formulation by enforcing sparsity in the correspondence matrix and offer its solutions based on linear programming. The proposed formulation not only enables a joint estimation of the landmark correspondences and a predefined transformation model but also combines the benefits of the soft assign strategy (Chui and Rangarajan, 2003) and the combinatorial optimization of linear programming. We also introduced a set of reinforced self-similarities descriptors which can better characterize local photometric and geometric properties of the retinal image. Theoretical analysis and experimental results with both fundus color images and angiogram images show the superior performances of our algorithms to several state-of-the-art techniques.

We present a system of automated drusen detection from color fundus photographs with our ultimate goal being to automatically assess the risk for the development of Age-related Macular Degeneration (AMD). Our system incorporates learning based drusen detection and includes fundus image analysis techniques for image denoising, illumination correction and color transfer. In contrast to previous work, we incorporate both optimal color descriptors and robust multiscale local image descriptors in our drusen detection process. Our system was evaluated with color fundus photographs from two AMD clinical studies [1, 2]. By comparing our results to those obtained via manual drusen segmentation, we show that our system outperforms two state-of-the-art techniques.

Using the double pass procedure, Navarroet al. (1993;Journal of the Optical Society of America A, 10, 201–212) measured the monochromatic modulation transfer function (MTF) of the human eye as a function of retinal eccentricity. They chose conditions as similar as possible to those encountered in natural viewing. We report new measurements obtained with conditions chosen instead to optimize retinal image quality: we paralyzed accommodation, used a 3 mm pupil, and corrected defocus and oblique astigmatism at each retinal location. MTFs were estimated at the tangential focus, circle of least confusion, and sagittal focus produced by oblique astigmatism. Though optical blur is well-known to have little effect on peripheral visual acuity, it can nonetheless substantially reduce aliasing by receptoral and post-receptoral spatial sampling.

SummaryIn 1918, Gordon Holmes combined observations of visual-field scotomas across brain-lesioned soldiers to produce a schematic map of the projection of the visual field upon the striate cortex [1]. One limit to the precision of his result, and the mapping of anatomy to retinotopy generally, is the substantial individual variation in the size [2, 3], volumetric position [4], and cortical magnification [5] of area V1. When viewed within the context of the curvature of the cortical surface, however, the boundaries of striate cortex fall at a consistent location across individuals [6]. We asked whether the surface topology of the human brain can be used to accurately predict the internal, retinotopic function of striate cortex as well. We used fMRI to measure polar angle and eccentricity in 25 participants and combined their maps within a left-right, transform-symmetric representation of the cortical surface [7]. These data were then fit using a deterministic, algebraic model of visual-field representation [8]. We found that an anatomical image alone can be used to predict the retinotopic organization of striate cortex for an individual with accuracy equivalent to 10–25 min of functional mapping. This indicates tight developmental linkage of structure and function within a primary, sensory cortical area.

We present a fully automated adaptive optics (AO) retinal image montaging algorithm using classic scale invariant feature transform with random sample consensus for outlier removal. Our approach is capable of using information from multiple AO modalities (confocal, split detection, and dark field) and can accurately detect discontinuities in the montage. The algorithm output is compared to manual montaging by evaluating the similarity of the overlapping regions after montaging, and calculating the detection rate of discontinuities in the montage. Our results show that the proposed algorithm has high alignment accuracy and a discontinuity detection rate that is comparable (and often superior) to manual montaging. In addition, we analyze and show the benefits of using multiple modalities in the montaging process. We provide the algorithm presented in this paper as open-source and freely available to download.

Characterizing humans' ability to discriminate changes in illumination provides information about the visual system's representation of the distal stimulus. We have previously shown that humans are able to discriminate illumination changes and that sensitivity to such changes depends on their chromatic direction. Probing illumination discrimination further would be facilitated by the use of computer-graphics simulations, which would, in practice, enable a wider range of stimulus manipulations. There is no a priori guarantee, however, that results obtained with simulated scenes generalize to real illuminated scenes. To investigate this question, we measured illumination discrimination in real and simulated scenes that were well-matched in mean chromaticity and scene geometry. Illumination discrimination thresholds were essentially identical for the two stimulus types. As in our previous work, these thresholds varied with illumination change direction. We exploited the flexibility offered by the use of graphics simulations to investigate whether the differences across direction are preserved when the surfaces in the scene are varied. We show that varying the scene's surface ensemble in a manner that also changes mean scene chromaticity modulates the relative sensitivity to illumination changes along different chromatic directions. Thus, any characterization of sensitivity to changes in illumination must be defined relative to the set of surfaces in the scene.

Human color constancy has been studied for over one hundred years, and there is extensive experimental data for the case where a spatially diffuse light source illuminates a set of flat matte surfaces. In natural viewing, however, three-dimensional objects are viewed in three-dimensional scenes. Little is known about color constancy for three-dimensional objects. We used a forced-choice task to measure the achromatic chromaticity of matte disks, matte spheres, and glossy spheres. In all cases, the test stimuli were viewed in the context of stereoscopically viewed graphics simulations of three-dimensional scenes, and we varied the scene illuminant. We studied conditions both where all cues were consistent with the simulated illuminant change (consistent-cue conditions) and where local contrast was silenced as a cue (reduced-cue conditions). We computed constancy indices from the achromatic chromaticities. To first order, constancy was similar for the three test object types. There was, however, a reliable interaction between test object type and cue condition. In the consistent-cue conditions, constancy tended to be best for the matte disks, while in the reduced-cue conditions constancy was best for the spheres. The presence of this interaction presents an important challenge for theorists who seek to generalize models that account for constancy for flat tests to the more general case of three-dimensional objects.

We seek a method to reconstruct mosaiced trichromatic images, using Bayesian methods in conjunction with a multivariate Cauchy prior. The Cauchy distribution is able to model the heavy-tailed distribution of spatial subband coefficients. Furthermore, the marginals of a multivariate Cauchy distribution are also Cauchy, making it useful for the color case where we must also capture correlations across sensors of different spectral classes. As proof of concept, we developed a method for spatially one-dimensional trichromatic images. Compared to an image estimate obtained via linear interpolation, the Cauchy-based Bayesian method has greater signal-to-noise ratio and exhibits reduced aliasing artifacts.

Accurate processing of color information requires knowledge of the spectral class of each light-sensitive receptor. Unsupervised learning algorithms can identify the class of individual sensors in a mosaic from the sensor responses to natural images. Article not available.

1. P.C. Glick, Fifty years of family demography: A record of social change, Journal of Marriage and the Family, 50, 861-873 (1988); J.A. Seltzer and S.M. Bianchi, Children's contact with absent par ents, Journal of Marriage and the Family, 50, 663 677(1988). 2. P. Bronstein and C.P. Cowan, Eds., Father hood Today: Men's Changing Role in the Family (Wiley, New York, 1988); M.E. Lamb, Ed., The Role of the Father in Child Development, rev. ed. (Wiley, New York, 1981); M.E. Lamb, Ed., The Father's Role: Cross-Cultural Perspectives (Wiley, New York, 1987). 3. P.j. Caplan, Don't Blame Mother: Mending the Mother-Daughter Relationship (Harper & Row, New York, 1989); P.J. Caplan and I. Hall McCorquodale, Mother-blaming in major clinical journals, American Journal of Orthopsychiatry, 55, 345-353 (1985). 4. V. Phares and B.E. Compas, The role of fa thers in child and adolescent psychopathology: Make room for daddy, Psychological Bulletin, 111, 387-412(1992). 5. V. Phares, Where's Poppa?: The relative lack of attention to the role of fathers in child and ado lescent psychopathology, American Psychologist, 47,656-664(1992). 6. K. Dodge, Developmental psychopathology in children of depressed mothers, Developmental Psychology, 26, 3-6 (1990); G. Downey and J.C. Coyne, Children of depressed parents: An integra tive review, Psychological Bulletin, 108, 50-76 (1990).

There is a large literature characterizing human perception of the lightness and color of matte surfaces arranged in coplanar arrays. In the past ten years researchers have begun to examine perception of lightness and color using wider ranges of stimuli intended to better approximate the conditions of everyday viewing. One emerging line of research concerns perception of lightness and color in scenes that approximate the three-dimensional environment we live in, with objects that need not be matte or coplanar and with geometrically complex illumination. A second concerns the perception of material surface properties other than color and lightness, such as gloss or roughness. This special issue features papers that address the rich set of questions and approaches that have emerged from these new research directions. Here, we briefly describe the articles in the issue and their relation to previous work.

Color, lightness, and glossiness are perceptual attributes associated with object reflectance. For these perceptual representations to be useful, they must correlate with physical reflectance properties of objects and not be overly affected by changes in illumination or viewing context. We employed a matching paradigm to investigate the perception of lightness and glossiness under geometric changes in illumination. Stimuli were computer simulations of spheres presented on a high-dynamic-range display. Observers adjusted the diffuse and specular reflectance components of a test sphere so that its appearance matched that of a reference sphere simulated under a different light field. Diffuse component matches were close to veridical across geometric changes in light field. In contrast, specular component matches were affected by geometric changes in light field. We tested several independence principles and found (i) that the effect of changing light field geometry on the diffuse component matches was independent of the reference sphere specular component; (ii) that the effect of changing light field geometry on the specular component matches was independent of the reference sphere diffuse component; and (iii) that diffuse and specular components of the match depended only slightly on the roughness of the specular component. Finally, we found that equating simple statistics (i.e., standard deviation, skewness, and kurtosis) computed from the luminance histograms of the spheres did not predict the matches: these statistics differed substantially between spheres that matched in appearance across geometric changes in the light field.

Cones with peak sensitivity to light at long (L), medium (M) and short (S) wavelengths are unequal in number on the human retina: S cones are rare (, Author Summary Human color perception arises by comparing the signals from cones with peak sensitivities, at long (L), medium (M) and short (S) wavelengths. In dichromats, a characteristic distribution of S and M cones supports blue-yellow color vision: a few S and mostly M. When L cones are added, allowing red-green color vision, the S proportion remains low, increasing slowly with increasing retinal eccentricity, but the L/M proportion can vary 5-fold without affecting red-green color perception. We offer a unified explanation of these striking facts. First, we find that the spatial-chromatic statistics of natural scenes are largely symmetric between the L, M and S sensitivity bands. Thus, attenuation of blue light in the optical media, and chromatic aberration after long-wavelength accommodation of the lens, can give L/M cones an advantage. Quantitatively, information transmission by the cone array is maximized when the S proportion is low but increasing slowly with retinal eccentricity, accompanied by a lens accommodated to red light. After including blur by the lens, the optimum depends weakly on the red/green ratio, allowing large variations without loss of function. This explains the basic layout of the cone mosaic: for the resources invested, the organization maximizes information.

Across many scenes, local contrast provides a valid cue to surface reflectance, but it is not the only such cue. To generalize beyond theories of lightness that rely exclusively on local contrast, we need to know which other potential cues matter. We had observers make lightness matches between two scene locations, and varied the surface slant and local surround reflectance of one of the locations. When local contrast was a valid cue to reflectance, all observers were approximately lightness constant. When it was not, observers' lightness matches were intermediate between contrast matching and lightness constancy. For most observers, surface slant exerted an effect on perceived lightness beyond that explainable by local contrast.

Although lesions of the striate (V1) cortex disrupt conscious vision, patients can demonstrate surprising residual abilities within their affected visual field, a phenomenon termed blindsight. The relative contribution of spared “islands” of functioning striate cortex to residual vision, versus subcortical pathways to extrastriate areas, has implications for the role of early visual areas in visual awareness and performance. Here we describe the behavioral and neural features of residual cortical function in Patient M.C., who sustained a posterior cerebral artery stroke at the age of 15 years. Within her impaired visual field, we found preserved visual abilities characteristic of blindsight, including superior detection of motion, and above-chance discrimination of shape, color, and motion direction. Functional magnetic resonance imaging demonstrated a retinotopically organized representation of M.C.'s blind visual field within the lesioned occipital lobe, specifically within area V1. The incongruity of a well-organized cortex and M.C.'s markedly impaired vision was resolved by measurement of functional responses within her damaged occipital lobe. Attenuated neural contrast-response functions were found to correlate with M.C.'s impaired psychophysical performance. These results demonstrate that the behavioral features of blindsight may arise in the presence of residual striate responses that are spatially organized and sensitive to contrast variation.

We describe the design philosophy and image representation of a calibrated color image processing system. The design emphasizes the representation of the spectral functions necessary for device-independent acquisition and display of color data. These basic design principles can be incorporated into a new generation of image processing software that integrates both spatial and spectral image processing.

Color vision supports two distinct visual functions: discrimination and constancy. Discrimination requires that the visual response to distinct objects within a scene be different. Constancy requires that the visual response to any object be the same across scenes. Across changes in scene, adaptation can improve discrimination by optimizing the use of the available response range. Similarly, adaptation can improve constancy by stabilizing the visual response to any fixed object across changes in illumination. Can common mechanisms of adaptation achieve these two goals simultaneously? We develop a theoretical framework for answering this question and present several example calculations. In the examples studied, the answer is largely yes when the change of scene consists of a change in illumination and considerably less so when the change of scene consists of a change in the statistical ensemble of surface reflectances in the environment.

Observers use a wide range of color names, including white, to describe monochromatic flashes with a retinal size comparable to that of a single cone. We model such data as a consequence of information loss arising from trichromatic sampling. The model starts with the simulated responses of the individual L, M, and S cones actually present in the cone mosaic and uses these to reconstruct the L-, M-, and S-cone signals that were present at every image location. We incorporate the optics and the mosaic topography of individual observers, as well as the spatio-chromatic statistics of natural images. We simulated the experiment of H. Hofer, B. Singer, & D. R. Williams (2005) and predicted the color name on each simulated trial from the average chromaticity of the spot reconstructed by our model. Broad features of the data across observers emerged naturally as a consequence of the measured individual variation in the relative numbers of L, M, and S cones. The model's output is also consistent with the appearance of larger spots and of sinusoidal contrast modulations. Finally, the model makes testable predictions for future experiments that study how color naming varies with the fine structure of the retinal mosaic.

Background RPE65 is an essential molecule in the retinoid-visual cycle, and RPE65 gene mutations cause the congenital human blindness known as Leber congenital amaurosis (LCA). Somatic gene therapy delivered to the retina of blind dogs with an RPE65 mutation dramatically restores retinal physiology and has sparked international interest in human treatment trials for this incurable disease. An unanswered question is how the visual cortex responds after prolonged sensory deprivation from retinal dysfunction. We therefore studied the cortex of RPE65-mutant dogs before and after retinal gene therapy. Then, we inquired whether there is visual pathway integrity and responsivity in adult humans with LCA due to RPE65 mutations (RPE65-LCA). Methods and Findings RPE65-mutant dogs were studied with fMRI. Prior to therapy, retinal and subcortical responses to light were markedly diminished, and there were minimal cortical responses within the primary visual areas of the lateral gyrus (activation amplitude mean ± standard deviation [SD] = 0.07% ± 0.06% and volume = 1.3 ± 0.6 cm3). Following therapy, retinal and subcortical response restoration was accompanied by increased amplitude (0.18% ± 0.06%) and volume (8.2 ± 0.8 cm3) of activation within the lateral gyrus (p < 0.005 for both). Cortical recovery occurred rapidly (within a month of treatment) and was persistent (as long as 2.5 y after treatment). Recovery was present even when treatment was provided as late as 1–4 y of age. Human RPE65-LCA patients (ages 18–23 y) were studied with structural magnetic resonance imaging. Optic nerve diameter (3.2 ± 0.5 mm) was within the normal range (3.2 ± 0.3 mm), and occipital cortical white matter density as judged by voxel-based morphometry was slightly but significantly altered (1.3 SD below control average, p = 0.005). Functional magnetic resonance imaging in human RPE65-LCA patients revealed cortical responses with a markedly diminished activation volume (8.8 ± 1.2 cm3) compared to controls (29.7 ± 8.3 cm3, p < 0.001) when stimulated with lower intensity light. Unexpectedly, cortical response volume (41.2 ± 11.1 cm3) was comparable to normal (48.8 ± 3.1 cm3, p = 0.2) with higher intensity light stimulation. Conclusions Visual cortical responses dramatically improve after retinal gene therapy in the canine model of RPE65-LCA. Human RPE65-LCA patients have preserved visual pathway anatomy and detectable cortical activation despite limited visual experience. Taken together, the results support the potential for human visual benefit from retinal therapies currently being aimed at restoring vision to the congenitally blind with genetic retinal disease., The study by Samuel Jacobson and colleagues suggests that retinal gene therapy can improve retinal, visual pathway, and visual cortex responses to light stimulation, even after prolonged periods of blindness and in congenitally blind patients., Editors' Summary Background. The eye captures light but the brain is where vision is experienced. Treatments for childhood blindness at the eye level are ready, but it is unknown whether the brain will be receptive to an improved neural message. Normal vision begins as photoreceptor cells in the retina (the light-sensitive tissue lining the inside of the eye) convert visual images into electrical impulses. These impulses are sent along the optic nerve to the visual cortex, the brain region where they are interpreted. The conversion of light into electrical impulses requires the activation of a molecule called retinal, which is subsequently recycled by retinal pigment epithelium (RPE) cells neighboring the retina. One of the key enzymes of the recycling reactions is encoded by a gene called RPE65. Genetic changes (mutations) in RPE65 cause an inherited form of blindness called Leber congenital amaurosis (LCA). In this disease, retinal is not recycled and as a result, the photoreceptor cells cannot work properly and affected individuals have poor or nonexistent vision from birth. Previous studies in dog and mouse models of the human disease have demonstrated that the introduction of a functional copy of RPE65 into the RPE cells using a harmless virus (gene therapy) dramatically restores retinal activity. Very recently, a pioneering gene therapy operation took place in London (UK) where surgeons injected a functional copy of RPE65 into the retina of a man with LCA. Whether this operation results in improved vision is not known at this time. Why Was This Study Done? Gene therapy corrects the retinal defects in animal models of LCA but whether the visual pathway from the retina to the visual cortex of the brain can respond normally to the signals sent by the restored retina is not known. Early visual experience is thought to be necessary for the development of a functional visual cortex, so replacing the defective RPE65 gene might not improve the vision of people with LCA. In this study, the researchers have studied the visual cortex of RPE65-deficient dogs before and after gene therapy to see whether the therapy affects the activity of the visual cortex. They have also investigated visual pathway integrity and responsiveness in adults with LCA caused by RPE65 mutations. If the visual pathway is disrupted in these patients, they reasoned, gene therapy might not restore their vision. What Did the Researchers Do and Find? The researchers used a technique called functional magnetic resonance imaging (fMRI) to measure light-induced brain activity in RPE65-deficient dogs before and after gene therapy. They also examined the reactions of the dogs' pupils to light (in LCA, the pupils do not contract normally in response to light because there is reduced signal transmission along the visual pathway). Finally, they measured the electrical activity of the dogs' retinas in response to light flashes—the retinas of patients with LCA do not react to light. Gene therapy corrected the defective retinal and visual pathway responses to light in the RPE65-deficient dogs and, whereas before treatment there was no response in the visual cortex to light stimulation in these dogs, after treatment, its activity approached that seen in normal dogs. The recovery of cortical responses was permanent and occurred soon after treatment, even in animals that were 4 years old when treated. Next, using structural MRI, the researchers studied human patients with LCA and found that the optic nerve diameter in young adults was within the normal range and that the structure of the visual cortex was very similar to that of normal individuals. Finally, using fMRI, they found that, although the visual cortex of patients with LCA did not respond to dim light, its reaction to bright light was comparable to that of normal individuals. What Do These Findings Mean? The findings from the dog study indicate that retinal gene therapy rapidly improves retinal, visual pathway, and visual cortex responses to light stimulation, even in animals that have been blind for years. In other words, in the dog model of LCA at least, all the components of the visual system remain receptive to visual inputs even after long periods of visual deprivation. The findings from the human study also indicate that the visual pathway remains anatomically intact despite years of disuse and that the visual cortex can be activated in patients with LCA even though these people have very limited visual experience. Taken together, these findings suggest that successful gene therapy of the retina might restore some functional vision to people with LCA but proof will have to await the outcomes of several clinical trials ongoing or being planned in Europe and the USA. Additional Information. Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040230. General information on gene therapy is available from the Oak Ridge National Laboratory Information is provided by the BBC about gene therapy for Leber congenital amaurosis (includes an audio clip from a doctor about the operation) The National Institutes of Health/National Eye Institute (US) provides information about an ongoing gene therapy trial of RPE65-Leber congenital amaurosis ClinicalTrials.gov gives details on treatment trials for Leber congenital amaurosis The Foundation Fighting Blindness has a fact sheet on Leber congenital amaurosis (site includes Microsoft Webspeak links that read some content aloud) The Foundation for Retinal Research has a fact sheet on Leber congenital amaurosis Find more detailed information on Leber congenital amaurosis and the gene mutations that cause it from GeneReviews WonderBaby, information for parents of babies with Leber congenital amaurosis

In daily life, we use color information to select objects that will best serve a particular goal (e.g., pick the best-tasting fruit or avoid spoiled food). This is challenging when judgments must be made across changes in illumination as the spectrum reflected from an object to the eye varies with the illumination. Color constancy mechanisms serve to partially stabilize object color appearance across illumination changes, but whether and to what degree constancy supports accurate cross-illumination object selection is not well understood. To get closer to understanding how constancy operates in real-life tasks, we developed a paradigm in which subjects engage in a goal-directed task for which color is instrumental. Specifically, in each trial, subjects re-created an arrangement of colored blocks (the model) across a change in illumination. By analyzing the re-creations, we were able to infer and quantify the degree of color constancy that mediated subjects' performance. In Experiments 1 and 2, we used our paradigm to characterize constancy for two different sets of block reflectances, two different illuminant changes, and two different groups of subjects. On average, constancy was good in our naturalistic task, but it varied considerably across subjects. In Experiment 3, we tested whether varying scene complexity and the validity of local contrast as a cue to the illumination change modulated constancy. Increasing complexity did not lead to improved constancy; silencing local contrast significantly reduced constancy. Our results establish a novel goal-directed task that enables us to approach color constancy as it emerges in real life.

Color names divide the fine-grained gamut of color percepts into discrete categories. A categorical transition must occur somewhere between the initial encoding of the continuous spectrum of light by the cones and the verbal report of the name of a color stimulus. Here, we used a functional magnetic resonance imaging (fMRI) adaptation experiment to examine the representation of hue in the early visual cortex. Our stimuli varied in hue between blue and green. We found in the early visual areas (V1, V2/3, and hV4) a smoothly increasing recovery from adaptation with increasing hue distance between adjacent stimuli during both passive viewing (Experiment 1) and active categorization (Experiment 2). We examined the form of the adaptation effect and found no evidence that a categorical representation mediates the release from adaptation for stimuli that cross the blue–green color boundary. Examination of the direct effect of stimulus hue on the fMRI response did, however, reveal an enhanced response to stimuli near the blue–green category border. This was largest in hV4 and when subjects were engaged in active categorization of the stimulus hue. In contrast with a recent report from another laboratory (Bird, Berens, Horner, & Franklin, 2014), we found no evidence for a categorical representation of color in the middle frontal gyrus. A post hoc whole-brain analysis, however, revealed several regions in the frontal cortex with a categorical effect in the adaptation response. Overall, our results support the idea that the representation of color in the early visual cortex is primarily fine grained and does not reflect color categories.

In guinea pig retina, immunostaining reveals a dual gradient of opsins: cones expressing opsin sensitive to medium wavelengths (M) predominate in the upper retina, whereas cones expressing opsin sensitive to shorter wavelengths (S) predominate in the lower retina. Whether these gradients correspond to functional gradients in postreceptoral neurons is essentially unknown. Using monochromatic flashes, we measured the relative weights with which M, S, and rod signals contribute to horizontal cell responses. For a background that produced 4.76 log10 photoisomerizations per rod per second (Rh*/rod/s), mean weights in superior retina were 52% (M), 2% (S), and 46% (rod). Mean weights in inferior retina were 9% (M), 50% (S), and 41% (rod). In superior retina, cone opsin weights agreed quantitatively with relative pigment density estimates from immunostaining. In inferior retina, cone opsin weights agreed qualitatively with relative pigment density estimates, but quantitative comparison was impossible because individual cones coexpress both opsins to varying and unquantifiable degrees. We further characterized the functional gradients in horizontal and brisk-transient ganglion cells using flickering stimuli produced by various mixtures of blue and green primary lights. Cone weights for both cell types resembled those obtained for horizontal cells using monochromatic flashes. Because the brisk-transient ganglion cell is thought to mediate behavioral detection of luminance contrast, our results are consistent with the hypothesis that the dual gradient of cone opsins assists achromatic contrast detection against different spectral backgrounds. In our preparation, rod responses did not completely saturate, even at background light levels typical of outdoor sunlight (5.14 log10 Rh*/rod/s).

What determines the color appearance of real objects viewed under natural conditions? The light reflected from different locations on a single object can vary enormously. This variation is enhanced when the material properties of the object are changed from matte to glossy. Yet humans have no trouble assigning a color name to most things. We studied how people perceive the color of spheres in complex scenes. Observers viewed graphics simulations of a three-dimensional scene containing two spheres, test and match. The observer's task was to adjust the match sphere until its color appearance was the same as that of the test sphere. The match sphere was always matte, and observers varied its color by changing the simulated spectral reflectance function. The surface gloss of the test spheres was varied across conditions. The data show that for fixed test sphere body reflectance, color appearance depends on surface gloss. This effect is small, however, compared to the variation that would be expected if observers simply matched the average of the light reflected from the test.

Vision is difficult because images are ambiguous about the structure of the world. For object color, the ambiguity arises because the same object reflects a different spectrum to the eye under different illuminations. Human vision typically does a good job of resolving this ambiguity-an ability known as color constancy. The past 20 years have seen an explosion of work on color constancy, with advances in both experimental methods and computational algorithms. Here, we connect these two lines of research by developing a quantitative model of human color constancy. The model includes an explicit link between psychophysical data and illuminant estimates obtained via a Bayesian algorithm. The model is fit to the data through a parameterization of the prior distribution of illuminant spectral properties. The fit to the data is good, and the derived prior provides a succinct description of human performance.

Color vision is useful for detecting surface boundaries and identifying objects. Are the signals used to perform these two functions processed by common mechanisms, or has the visual system optimized its processing separately for each task? We measured the effect of mean chromaticity and luminance on color discriminability and on color appearance under well-matched stimulus conditions. In the discrimination experiments, a pedestal spot was presented in one interval and a pedestal + test in a second. Observers indicated which interval contained the test. In the appearance experiments, observers matched the appearance of test spots across a change in background. We analyzed the data using a variant of Fechner's proposal, that the rate of apparent stimulus change is proportional to visual sensitivity. We found that saturating visual response functions together with a model of adaptation that included multiplicative gain control and a subtractive term accounted for data from both tasks. This result suggests that effects of the contexts we studied on color appearance and discriminability are controlled by the same underlying mechanism.

Pixel saturation, where the incident light at a pixel causes one of the color channels of the camera sensor to respond at its maximum value, can produce undesirable artifacts in digital color images. We present a Bayesian algorithm that estimates what the saturated channel's value would have been in the absence of saturation. The algorithm uses the non-saturated responses from the other color channels, together with a multivariate Normal prior that captures the correlation in response across color channels. The appropriate parameters for the prior may be estimated directly from the image data, since most image pixels are not saturated. Given the prior, the responses of the non-saturated channels, and the fact that the true response of the saturated channel is known to be greater than the saturation level, the algorithm returns the optimal expected mean square estimate for the true response. Extensions of the algorithm to the case where more than one channel is saturated are also discussed. Both simulations and examples with real images are presented to show that the algorithm is effective.

When a planar object is rotated with respect to a directional light source, the reflected luminance changes. If surface lightness is to be a reliable guide to surface identity, observers must compensate for such changes. To the extent they do, observers are said to be lightness constant. We report data from a lightness matching task that assesses lightness constancy with respect to changes in object slant. On each trial, observers viewed an achromatic standard object and indicated the best match from a palette of 36 grayscale samples. The standard object and the palette were visible simultaneously within an experimental chamber. The chamber illumination was provided from above by a theater stage lamp. The standard objects were uniformly-painted flat cards. Different groups of naive observers made matches under two sets of instructions. In the Neutral Instructions, observers were asked to match the appearance of the standard and palette sample. In the Paint Instructions, observers were asked to choose the palette sample that was painted the same as the standard. Several broad conclusions may be drawn from the results. First, data for most observers were neither luminance matches nor lightness constant matches. Second, there were large and reliable individual differences. To characterize these, a constancy index was obtained for each observer by comparing how well the data were accounted for by both luminance matching and lightness constancy. The index could take on values between 0 (luminance matching) and 1 (lightness constancy). Individual observer indices ranged between 0.17 and 0.63 with mean 0.40 and median 0.40. An auxiliary slant-matching experiment rules out variation in perceived slant as the source of the individual variability. Third, the effect of instructions was small compared to the inter-observer variability. Implications of the data for models of lightness perception are discussed.

In the companion study (C. Ripamonti et al., 2004), we present data that measure the effect of surface slant on perceived lightness. Observers are neither perfectly lightness constant nor luminance matchers, and there is considerable individual variation in performance. This work develops a parametric model that accounts for how each observer's lightness matches vary as a function of surface slant. The model is derived from consideration of an inverse optics calculation that could achieve constancy. The inverse optics calculation begins with parameters that describe the illumination geometry. If these parameters match those of the physical scene, the calculation achieves constancy. Deviations in the model's parameters from those of the scene predict deviations from constancy. We used numerical search to fit the model to each observer's data. The model accounts for the diverse range of results seen in the experimental data in a unified manner, and examination of its parameters allows interpretation of the data that goes beyond what is possible with the raw data alone.

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.

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.

The physical properties of color stimuli may be specified using spectral measurements or tristimulus coordinates. Such specification provides little intuition about how the stimuli will appear. For applications such as color selection, color is specified using appearance terms and an automatic method for computing the corresponding tristimulus coordinates. To do so, one needs to understand the relation between the physical description of a color stimulus and a quantitative description of its color appearance. Another aspect of practical importance is to specify the magnitude of differences between colored stimuli. This requires the understanding of the relation between changes in the physical description of a color stimulus and corresponding changes in appearance. This chapter provides an introduction to color specification systems and describes their use. The chapter also discusses the phenomenology of color appearance and describes the psychological attributes of hue, saturation/ chroma, and brightness/lightness.

Vision algorithms are often developed in a Bayesian framework. Two estimators are commonly used: maximum a posteriori (MAP), and minimum mean squared error (MMSE). We argue that neither is appropriate for perception problems. The MAP estimator makes insufficient use of structure in the posterior probability. The squared error penalty of the MMSE estimator does not reflect typical penalties. We describe a new estimator, which we call maximum local mass (MLM) [10, 26, 65], which integrates the local probability density. The MLM method is sensitive to local structure of the posterior probability, which MAP is not. The new method uses an optimality criterion that is appropriate for perception tasks: it finds the most probable approximately correct answer. For the case of low observation noise, we provide an efficient approximation. We apply this new estimator to color constancy. An unknown illuminant falls on surfaces of unknown colors. We seek to estimate both the illuminant spectrum and the surface spectra from photosensor responses which depend on the product of the unknown spectra. In simulations, we show that the MLM method performs better than the MAP estimator, and better than two standard color constancy algorithms. The MLM method may prove useful in other vision problems as well. >