Color and spatial structure in natural scenes.

Digitized records of terrain scenes were produced using a technique of photographic colorimetry. Each record consisted of three tristimulus images (X, Y, and Z) which were analyzed for their color statistics, spatial frequency content, and image correlation. Interactions between color and space were examined using a cone receptor transformation. It is shown that the scene amplitude spectra follow an approximate reciprocal variation with frequency, and that the correlation function can be described by a one-step autoregressive model. The results are discussed in terms of methods for optimum image coding in human and machine vision.

[1]  D. L. Macadam Visual Sensitivities to Color Differences in Daylight , 1942 .

[2]  W D Wright,et al.  The colour sensitivity of the retina within the central fovea of man , 1947, The Journal of physiology.

[3]  S. Hecht,et al.  The colors of natural objects and terrains, and their relation to visual color deficiency. , 1949, Journal of the Optical Society of America.

[4]  W. R. Brown,et al.  Statistics of Color-Matching Data* , 1952 .

[5]  E. Kretzmer Statistics of television signals , 1952 .

[6]  G. Békésy Neural inhibitory units of the eye and skin. Quantitative description of contrast phenomena. , 1960, Journal of the Optical Society of America.

[7]  D. Hubel,et al.  Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.

[8]  J. Tukey,et al.  An algorithm for the machine calculation of complex Fourier series , 1965 .

[9]  D. Hubel,et al.  Spatial and chromatic interactions in the lateral geniculate body of the rhesus monkey. , 1966, Journal of neurophysiology.

[10]  C Blakemore,et al.  On the existence of neurones in the human visual system selectively sensitive to the orientation and size of retinal images , 1969, The Journal of physiology.

[11]  J. Robson,et al.  Spatial-frequency channels in human vision. , 1971, Journal of the Optical Society of America.

[12]  J. J. Vos,et al.  On the derivation of the foveal receptor primaries. , 1971, Vision research.

[13]  K. Ruddock The physics of colour vision , 1971 .

[14]  A. Y. Maudarbocus,et al.  Non-linearity of visual signals in relation to shape-sensitive adaptation responses. , 1973, Vision research.

[15]  B. G. Bender Spatial interactions between the red- and green-sensitive colour mechanisms of the human visual system. , 1973, Vision research.

[16]  J. Makhoul,et al.  Linear prediction: A tutorial review , 1975, Proceedings of the IEEE.

[17]  A. Robertson The CIE 1976 Color-Difference Formulae , 1977 .

[18]  P. Burt Fast filter transform for image processing , 1981 .

[19]  A.K. Jain,et al.  Advances in mathematical models for image processing , 1981, Proceedings of the IEEE.

[20]  S. Laughlin,et al.  Predictive coding: a fresh view of inhibition in the retina , 1982, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[21]  C. R. Ingling,et al.  The relationship between spectral sensitivity and spatial sensitivity for the primate r-g X-channel , 1983, Vision Research.

[22]  G. Buchsbaum,et al.  Trichromacy, opponent colours coding and optimum colour information transmission in the retina , 1983, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[23]  Rangasami L. Kashyap,et al.  Synthesis and Estimation of Random Fields Using Long-Correlation Models , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  Alex Pentland,et al.  Fractal-Based Description of Natural Scenes , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.