The paper proposes a number of models to examine through what mech-anisms a population of autonomous agents could arrive at a repertoire of perceptually grounded categories that is sufficiently shared to allow successful communication. The models are inspired by the main approaches to human categorisation being discussed in the literature: nativism, empiricism, and culturalism. Colour is taken as a case study. Although the paper takes no stance on which position is to be accepted as final truth with respect to hu-man categorisation and naming, it points to theoretical constraints that make each position more or less likely and contains clear suggestions on what the best engineering solution would be. Specifically, it argues that the collective choice of a shared repertoire must integrate multiple constraints, including constraints coming from communication.

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Visual stimuli contain a limited amount of information that could potentially be used to perform a given visual task. At successive stages of visual processing, some of this information is lost and some is transmitted to higher stages. This article describes a new analysis, based on the concept of the ideal observer in signal detection theory, that allows one to trace the (low of discrimination information through the initial physiological stages of visual processing, for arbitrary spatio-chromatic stimuli. This ideal-observer analysis provides a rigorous means of measuring the information content of visual stimuli and of assessing the contribution of specific physiological mechanisms to discrimination performance. Here, the analysis is developed for the physiological mechanisms up to the level of the photoreceptor. It is shown that many psychophysical phenomena previously attributed to neural mechanisms may be explained by variations in the information content of the stimuli and by preneural mechanisms. The purpose of vision is to extract and represent information about the physical environment from the light that is emitted, transmitted, or reflected by objects and surfaces. In order to extract useful information, a visual system must be able to encode

We have studied how contrast threshold sensitivity depends jointly on pattern and color. We measured sensitivitytocolored Gabor patches from 0.5 to 8 cycles per degree #cpd#. At each spatial frequency,we measured in many di#erent color directions. We analyze the sensitivity measurements using a series of nested models. We conclude that a model consisting of three pattern-color separable mechanisms predicts detection performance nearly as well as #tting psychometric functions independently. We derive the pattern and color sensitivities of the separable mechanisms from the experimental data. Two derived mechanisms are spatially lowpass and spectrally color-opponent. The third mechanism is spatially bandpass and spectrally broadband.

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Most systems used for creating and displaying colormap-based visualizations are not photometrically calibrated. That is, the relationship between RGB input levels and perceived luminance is usually not known, due to variations in the monitor, hardware configuration, and the viewing environment. However, the luminance component of perceptually based colormaps should be controlled, due to the central role that luminance plays in our visual processing. We address this problem with a simple and effective method for performing luminance matching on an uncalibrated monitor. The method is akin to the minimally distinct border technique (a previous method of luminance matching used for measuring luminous efficiency), but our method relies on the brain's highly developed ability to distinguish human faces. We present a user study showing that our method produces equivalent results to the minimally distinct border technique, but with significantly improved precision. We demonstrate how results from our luminance matching method can be directly applied to create new univariate colormaps.

Does the color of text influence its legibility? There are reasons why it may do so for specific groups of low-vision observers. We used psychophysical methods to measure the effects of wavelength on the reading performance of four normal observers, two dichromats, and 25 low-vision observers. Reading rates were measured for text scanned across the face of a television (TV) monitor. We compared performance under four luminance-matched conditions in which sets of neutral-density and Wratten color filters were placed in front of the TV screen-blue (λmax = 430 nm), green (λmax = 550 nm), red (λmax = 650 nm), and gray. Under photopic conditions, the reading rates of normal subjects were independent of wavelength, with the exception of characters near the acuity limit. At lower luminances, wavelength effects could be explained by the shift from photopic to scotopic vision. It was hypothesized that light scatter or absorption in eyes with cloudy ocular media would result in depressed performance in the blue. Only one of seven subjects demonstrated this effect, which we traced to wavelength-specific absorption. Observers with advanced photoreceptor disorders tended to read blue text faster than red text. This could not be explained on the basis of photopic spectral sensitivities alone. Finally, the presence of central or peripheral field loss was not predictive of wavelength-specific effects in reading. On the whole, wavelength only occasionally plays a significant role in reading. When it does, performance tends to be depressed either in the red or the blue and to be nearly optimal for green or gray.

In this paper we present an image similarity metric for content-based image database search. The similarity metric is based on a multiscale model of the human visual system. This multiscale model includes channels which account for perceptual phenomena such as color, contrast, color-contrast and orientation selectivity. From these channels, we extract features and then form an aggregate measure of similarity using a weighted linear combination of the feature di#erences. The choice of features and weights is made to maximize the consistency with similarity ratings made by human subjects. In particular, we use a visual test to collect experimental image matching data. We then define a cost function relating the distances computed by the metric to the choices made by the human subject. The results indicate that features corresponding to contrast, color-contrast and orientation can significantly improve search performance. Furthermore, the systematic optimization and evaluation strategy us...

By taking into account the properties and limitations of the human visual system (HVS), images can be more efficiently compressed, colors more accurately reproduced, prints better rendered, to mention a few major advantages. To achieve these goals it is necessary to build a computational model of the HVS. In this paper we give an introduction to the general issue of HVS-modeling and review the specific applications of visual quality assessment and HVS-based image compression, which are closely related. On one hand, these two examples demonstrate the common structure of HVS-models, on the other hand they also show how application-specific constraints influence model design. Recent vision models from these application areas are reviewed and summarized in a table for direct comparison.

Color embedded image compression is investigated by means of a set of core experiments that seek to evaluate the advantages of various color transformations, spatial orientation trees and the use of monochrome embedded coding schemes such as EZW and SPIHT. In order to take advantage of the interdependencies of the color components for a given color space, two new spatial orientation trees that relate frequency bands and color components are investigated. 1.