C.A. Párraga

Color and luminance information in natural scenes

The spatial filtering applied by the human visual system appears to be low pass for chromatic stimuli and band pass for luminance stimuli. Here we explore whether this observed difference in contrast sensitivity reflects a real difference in the components of chrominance and luminance in natural scenes. For this purpose a digital set of 29 hyperspectral images of natural scenes was acquired and its spatial frequency content analyzed in terms of chrominance and luminance defined according to existing models of the human cone responses and visual signal processing. The statistical 1/f amplitude spatial-frequency distribution is confirmed for a variety of chromatic conditions across the visible spectrum. Our analysis suggests that natural scenes are relatively rich in high-spatial-frequency chrominance information that does not appear to be transmitted by the human visual system. This result is unlikely to have arisen from errors in the original measurements. Several reasons may combine to explain a failure to transmit high-spatial-frequency chrominance: (a) its minor importance for primate visual tasks, (b) its removal by filtering applied to compensate for chromatic aberration of the eyes optics, and (c) a biological bottleneck blocking its transmission. In addition, we graphically compare the ratios of luminance to chrominance measured by our hyperspectral camera and those measured psychophysically over an equivalent spatial-frequency range.

Spatiochromatic Properties of Natural Images and Human Vision

The human visual system shows a relatively greater response to low spatial frequencies of chromatic spatial modulation than to luminance spatial modulation. However, previous work has shown that this differential sensitivity to low spatial frequencies is not reflected in any differential luminance and chromatic content of general natural scenes. This is contrary to the prevailing assumption that the spatial properties of human vision ought to reflect the structure of natural scenes. Now, colorimetric measures of scenes suggest that red-green (and perhaps blue-yellow) color discrimination in primates is particularly suited to the encoding of specific scenes: reddish or yellowish objects on a background of leaves. We therefore ask whether the spatial, as well as chromatic, properties of such scenes are matched to the different spatial-encoding properties of color and luminance modulation in human vision. We show that the spatiochromatic properties of a wide class of scenes, which contain reddish objects (e.g., fruit) on a background of leaves, correspond well to the properties of the red-green (but not blue-yellow) systems in human vision, at viewing distances commensurate with typical grasping distance. This implies that the red-green system is particularly suited to encoding both the spatial and the chromatic structure of such scenes.

The human visual system is optimised for processing the spatial information in natural visual images

A fundamental tenet of visual science is that the detailed properties of visual systems are not capricious accidents, but are closely matched by evolution and neonatal experience to the environments and lifestyles in which those visual systems must work. This has been shown most convincingly for fish and insects. For mammalian vision, however, this tenet is based more upon theoretical arguments than upon direct observations. Here, we describe experiments that require human observers to discriminate between pictures of slightly different faces or objects. These are produced by a morphing technique that allows small, quantifiable changes to be made in the stimulus images. The independent variable is designed to give increasing deviation from natural visual scenes, and is a measure of the Fourier composition of the image (its second-order statistics). Performance in these tests was best when the pictures had natural second-order spatial statistics, and degraded when the images were made less natural. Furthermore, performance can be explained with a simple model of contrast coding, based upon the properties of simple cells in the mammalian visual cortex. The findings thus provide direct empirical support for the notion that human spatial vision is optimised to the second-order statistics of the optical environment.

Use of a vision model to quantify the significance of factors effecting target conspicuity

When designing camouflage it is important to understand how the human visual system processes the information to discriminate the target from the background scene. A vision model has been developed to compare two images and detect differences in local contrast in each spatial frequency channel. Observer experiments are being undertaken to validate this vision model so that the model can be used to quantify the relative significance of different factors affecting target conspicuity. Synthetic imagery can be used to design improved camouflage systems. The vision model is being used to compare different synthetic images to understand what features in the image are important to reproduce accurately and to identify the optimum way to render synthetic imagery for camouflage effectiveness assessment. This paper will describe the vision model and summarise the results obtained from the initial validation tests. The paper will also show how the model is being used to compare different synthetic images and discuss future work plans.