Measurement of individual color space using a luminous vector field.

This study is intended to measure the geometry of the observer's color space when viewing a computer screen and to define individual variations from these data. A CIE photometric standard observer assumes that the eye's spectral efficiency function is constant, and photometry measurements correspond to vectors with fixed directions. By definition, the standard observer decomposes color space into planar surfaces of constant luminance. Using heterochromatic photometry with a minimum motion stimulus, we systematically measure the direction of luminous vectors for many observers and many color points. During the measurement process, the background and stimulus modulation averages are fixed to the given points to ensure that the observer is in a fixed adaptation mode. Our measurements result in a vector field or set of vectors (x,v), where x is the point's color space position, and v is the observer's luminosity vector. To estimate surfaces from vector fields, two mathematical hypotheses were used: (1) that surfaces are quadratic or, equivalently, that the vector field model is affine, and (2) that the metric of surfaces is proportional to a visual origin. Across 24 observers, we found that vector fields are convergent and the corresponding surfaces are hyperbolic. The equation of the surface in the display's color space coordinate system, and in particular the axis of symmetry, varied systematically from individual to individual. A hyperbolic geometry is compatible with studies that emphasize a modification of the photometric vector with changing adaptations.

The Predictive Role of Low Spatial Frequencies in Automatic Face Processing: A Visual Mismatch Negativity Investigation.

Visual processing is thought to function in a coarse-to-fine manner. Low spatial frequencies (LSF), conveying coarse information, would be processed early to generate predictions. These LSF-based predictions would facilitate the further integration of high spatial frequencies (HSF), conveying fine details. The predictive role of LSF might be crucial in automatic face processing, where high performance could be explained by an accurate selection of clues in early processing. In the present study, we used a visual Mismatch Negativity (vMMN) paradigm by presenting an unfiltered face as standard stimulus, and the same face filtered in LSF or HSF as deviant, to investigate the predictive role of LSF vs. HSF during automatic face processing. If LSF are critical for predictions, we hypothesize that LSF deviants would elicit less prediction error (i.e., reduced mismatch responses) than HSF deviants. Results show that both LSF and HSF deviants elicited a mismatch response compared with their equivalent in an equiprobable sequence. However, in line with our hypothesis, LSF deviants evoke significantly reduced mismatch responses compared to HSF deviants, particularly at later stages. The difference in mismatch between HSF and LSF conditions involves posterior areas and right fusiform gyrus. Overall, our findings suggest a predictive role of LSF during automatic face processing and a critical involvement of HSF in the fusiform during the conscious detection of changes in faces.

A new blind color watermarking based on a psychovisual model.

In this paper, we address the problem of the use of a human visual system (HVS) model to improve watermark invisibility. We propose a new color watermarking algorithm based on the minimization of the perception of color differences. This algorithm is based on a psychovisual model of the dynamics of cone photoreceptors. We used this model to determine the discrimination power of the human for a particular color and thus the best strategy to modify color pixels. Results were obtained on a color version of the lattice quantization index modulation (LQIM) method and showed improvements on psychovisual invisibility and robustness against several image distortions.

The Geometry of Noise in Color and Spectral Image Sensors.

Digital images are always affected by noise and the reduction of its impact is an active field of research. Noise due to random photon fall onto the sensor is unavoidable but could be amplified by the camera image processing such as in the color correction step. Color correction is expressed as the combination of a spectral estimation and a computation of color coordinates in a display color space. Then we use geometry to depict raw, spectral and color signals and noise. Geometry is calibrated on the physics of image acquisition and spectral characteristics of the sensor to study the impact of the sensor space metric on noise amplification. Since spectral channels are non-orthogonal, we introduce the contravariant signal to noise ratio for noise evaluation at spectral reconstruction level. Having definitions of signal to noise ratio for each steps of spectral or color reconstruction, we compare performances of different types of sensors (RGB, RGBW, RGBWir, CMY, RYB, RGBC).

Classical optics in France: introduction.

This special issue of the Journal of the Optical Society of America A (JOSA A) is devoted to the wide array of French researchers from universities and state research organisms, offering them the opportunity to share and showcase their current research in the fields of optics and imaging sciences to the global community.

Navigating from a Depth Image Converted into Sound.

Background. Common manufactured depth sensors generate depth images that humans normally obtain from their eyes and hands. Various designs converting spatial data into sound have been recently proposed, speculating on their applicability as sensory substitution devices (SSDs). Objective. We tested such a design as a travel aid in a navigation task. Methods. Our portable device (MeloSee) converted 2D array of a depth image into melody in real-time. Distance from the sensor was translated into sound intensity, stereo-modulated laterally, and the pitch represented verticality. Twenty-one blindfolded young adults navigated along four different paths during two sessions separated by one-week interval. In some instances, a dual task required them to recognize a temporal pattern applied through a tactile vibrator while they navigated. Results. Participants learnt how to use the system on both new paths and on those they had already navigated from. Based on travel time and errors, performance improved from one week to the next. The dual task was achieved successfully, slightly affecting but not preventing effective navigation. Conclusions. The use of Kinect-type sensors to implement SSDs is promising, but it is restricted to indoor use and it is inefficient on too short range.

Neurogeometry of color vision.

In neurogeometry, principles of differential geometry and neuron dynamics are used to model the representation of forms in the primary visual cortex, V1. This approach is well-suited for explaining the perception of illusory contours such as Kanizsa's figure (see Petitot (2008) for a review). In its current version, neurogeometry uses achromatic inputs to the visual system as the starting-point for form estimation. Here we ask how neurogeometry operates when the input is chromatic as in color vision. We propose that even when considering only the perception of form, the random nature of the cone mosaic must be taken into account. The main challenge for neurogeometry is to explain how achromatic information could be estimated from the sparse chromatic sampling provided by the cone mosaic. This article also discusses the non-linearity involved in a neural geometry for chromatic processing. We present empirical results on color discrimination to illustrate the geometric complexity for the discrimination contour when the adaptation state of the observer is not conditioned. The underlying non-linear geometry must conciliate both mosaic sampling and regulation of visual information in the visual system.

Hue discrimination, unique hues and naming.

The hue discrimination curve (HDC) that characterizes performances over the entire hue circle was determined by using sinusoidally modulated spectral power distributions of 1.5 c/300 nm with fixed amplitude and twelve reference phases. To investigate relationship between hue discrimination and appearance, observers further performed a free color naming and unique hue tasks. The HDC consistently displayed two minima and two maxima; discrimination is optimal at the yellow/orange and blue/magenta boundaries and pessimal in green and in the extra-spectral magenta colors. A linear model based on Müller zone theory correctly predicts a periodical profile but with a phase-opponency (minima/maxima at 180° apart) which is inconsistent with the empirical HDC's profile.

Residual abilities in age-related macular degeneration to process spatial frequencies during natural scene categorization.

Age-related macular degeneration (AMD) is characterized by a central vision loss. We explored the relationship between the retinal lesions in AMD patients and the processing of spatial frequencies in natural scene categorization. Since the lesion on the retina is central, we expected preservation of low spatial frequency (LSF) processing and the impairment of high spatial frequency (HSF) processing. We conducted two experiments that differed in the set of scene stimuli used and their exposure duration. Twelve AMD patients and 12 healthy age-matched participants in Experiment 1 and 10 different AMD patients and 10 healthy age-matched participants in Experiment 2 performed categorization tasks of natural scenes (Indoors vs. Outdoors) filtered in LSF and HSF. Experiment 1 revealed that AMD patients made more no-responses to categorize HSF than LSF scenes, irrespective of the scene category. In addition, AMD patients had longer reaction times to categorize HSF than LSF scenes only for indoors. Healthy participants' performance was not differentially affected by spatial frequency content of the scenes. In Experiment 2, AMD patients demonstrated the same pattern of errors as in Experiment 1. Furthermore, AMD patients had longer reaction times to categorize HSF than LSF scenes, irrespective of the scene category. Again, spatial frequency processing was equivalent for healthy participants. The present findings point to a specific deficit in the processing of HSF information contained in photographs of natural scenes in AMD patients. The processing of LSF information is relatively preserved. Moreover, the fact that the deficit is more important when categorizing HSF indoors, may lead to new perspectives for rehabilitation procedures in AMD.

Spatially coherent colour image reconstruction from a trichromatic mosaic with random arrangement of chromatic samples.

Recent high resolution imaging of the human retina confirms that the trichromatic cone mosaic follows a random arrangement. Moreover, both the cones' arrangements and proportion widely differ from individual to individual. These findings provide new insights to our understanding of colour vision as most of the previous vision models ignored the mosaic sampling. Here, we propose a cone mosaic sampling simulation applied to colour images. From the simulation, we can infer the processing needs for retrieving spatial and chromatic information from the mosaic without spatial ambiguity. In particular, the focus is on the ability of the visual system to reconstruct coherent spatial information from a plurality of local neighbourhoods. We show that normalized linear processing allows the recovery of achromatic and chromatic information from a mosaic of trichromatic samples arranged randomly. Also, low frequency components of achromatic information can serve to coarsely estimate orientation, which in turn improves the interpolation of chromatic information. An implication for the visual system is the possibility that, in the cortex, the low frequency achromatic spatial information of the magnocellular pathway helps separate chromatic information from the mixed achromatic/chromatic information carried by the parvocellular pathway.

Spatial bias induced by a non-conflictual task reveals the nature of space perception.

The aim of the present study was to show that space perception depends on sensori-motor experience. We induced spatial biases by a non-conflictual lateralized sensori-motor task on twenty seven right-handed healthy volunteers (left-to-right readers). After a pre-test and before a post-test, which assessed visuo-motor and perceptual subjective midpoint in line bisection, participants performed a short lateralized pointing task (towards the left or right hemispace). Results indicated that this lateralized pointing task induced deviations towards the stimulated hemispace in both the visuo-motor and the perceptual estimations of the subjective line centre. These spatial biases varied as a function of pointing direction (left or right pointing), spatial location and line lengths. These findings suggest that a preceding non-conflictual lateralized sensori-motor experience influences subsequent space perception. Accordingly, ecological sensori-motor experience could be involved in asymmetric perception exhibited by normal individuals and neglect patients.

Model of retinal local adaptation for the tone mapping of color filter array images.

We present a tone mapping algorithm that is derived from a model of retinal processing. Our approach has two major improvements over existing methods. First, tone mapping is applied directly on the mosaic image captured by the sensor, analogous to the human visual system that applies a nonlinearity to the chromatic responses captured by the cone mosaic. This reduces the number of necessary operations by a factor 3. Second, we introduce a variation of the center/surround class of local tone mapping algorithms, which are known to increase the local contrast of images but tend to create artifacts. Our method gives a good improvement in contrast while avoiding halos and maintaining good global appearance. Like traditional center/surround algorithms, our method uses a weighted average of surrounding pixel values. Instead of being used directly, the weighted average serves as a variable in the Naka-Rushton equation, which models the photoreceptors' nonlinearity. Our algorithm provides pleasing results on various images with different scene content and dynamic range.

Linear demosaicing inspired by the human visual system.

There is an analogy between single-chip color cameras and the human visual system in that these two systems acquire only one limited wavelength sensitivity band per spatial location. We have exploited this analogy, defining a model that characterizes a one-color per spatial position image as a coding into luminance and chrominance of the corresponding three colors per spatial position image. Luminance is defined with full spatial resolution while chrominance contains subsampled opponent colors. Moreover, luminance and chrominance follow a particular arrangement in the Fourier domain, allowing for demosaicing by spatial frequency filtering. This model shows that visual artifacts after demosaicing are due to aliasing between luminance and chrominance and could be solved using a preprocessing filter. This approach also gives new insights for the representation of single-color per spatial location images and enables formal and controllable procedures to design demosaicing algorithms that perform well compared to concurrent approaches, as demonstrated by experiments.