September 2005
Volume 5, Issue 8
Vision Sciences Society Annual Meeting Abstract  |   September 2005
A theoretical framework for texture parameterization
Author Affiliations
  • Jonathan D. Victor
    Weill Medical College of Cornell University, New York City, New York
  • Charles Chubb
    University of California at Irvine, Irvine, California
  • Mary M. Conte
    Weill Medical College of Cornell University, New York City, New York
Journal of Vision September 2005, Vol.5, 474. doi:
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      Jonathan D. Victor, Charles Chubb, Mary M. Conte; A theoretical framework for texture parameterization. Journal of Vision 2005;5(8):474.

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      © ARVO (1962-2015); The Authors (2016-present)

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It is well known that textures with sufficiently distinct power spectra are perceptually distinct, and that some higher-order spatial correlations also support texture discrimination and segmentation. However, a concise parameterization of the correlation structure relevant to perception is as yet elusive. We attempt to bring together a range of psychophysical and analytical results to suggest a minimal structure for the perceptual space of textures.

The motivation for the present approach is that the visual system is likely to represent image statistics in a manner that is efficient, but perhaps not comprehensive. We hypothesize that any texture is perceptually equivalent to a texture for which all statistics of all orders can be reconstructed from a small subset of image statistics. A natural formalization of this reconstruction is maximum entropy extension (Zhu et al., 1998).

Filtered Gaussian noises can always be set in this framework, consistent with the notion that second-order statistics typically support texture discrimination. For textures defined by high-order correlations extended along one dimension, discriminability appears to be based on induced differences in the luminance histogram of multicheck blocks, or induced long-range second-order statistics. In two dimensions, the simplest scenario is that of binary textures in 2x2 blocks. Only a small subset of assignments of block probabilities allows for maximum entropy extension. Two of these correspond to previously-recognized families of binary isodipole textures, but other components of this subset correspond to as-yet unrecognized isodipole textures that are highly discriminable. These observations suggest that perceptual texture space is usefully parameterized by maximum-entropy extension of pixel histogram and second-order statistics at many scales, and fourth-order statistics restricted to two-dimensional nearest-neighbor cliques. Predictions and shortcomings of this view will be discussed.

Victor, J. D. Chubb, C. Conte, M. M. (2005). A theoretical framework for texture parameterization [Abstract]. Journal of Vision, 5(8):474, 474a,, doi:10.1167/5.8.474. [CrossRef]

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