Maximum likelihood metameres for local 2nd order image structure of natural images

  • Authors:
  • Martin Lillholm;Lewis D. Griffin

  • Affiliations:
  • University College London, Department of Computer Science, London, United Kingdom;University College London, Department of Computer Science, London, United Kingdom

  • Venue:
  • SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
  • Year:
  • 2007

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Abstract

We investigate the maximum likelihood metameres of local pure 2nd order structure in natural images. Using the shape index, we re-parameterise the 2nd order structure and gain a one-parameter index which offers a qualitative description of local pure 2nd order image structure. Inspired by Koenderink and previous work within Geometric Texton Theory the maximum likelihood metameres are calculated for a quantised version of the shape index. Results are presented and discussed for natural images, Gaussian noise images, and Brownian or pink noise images. Furthermore, we present statistics for the shape index, principal direction, and curvedness of natural images. Finally, the results are discussed in the terms of their applicability to Geometric Texton Theory.