Recovering image structure by model-based interaction map

  • Georgy Gimel'farb
Document Image Analysis and Recognition
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1451)

Abstract

We address modelling of stochastic image textures by Gibbs random fields with a translation invariant structure of multiple pairwise pixel interactions. The characteristic interaction structure and strengths (Gibbs potentials) are learnt from a given training sample by analytic and stochastic approximation of the unconditional or conditional maximum likelihood estimates of the potentials. The interaction structure is revealed by a model-based interaction map showing the relative contributions of each interaction to a total Gibbs energy. Features of the interaction maps are discussed and illustrated by experiments with various natural textures.

Keywords

Interaction Structure Image Patch Stochastic Approximation Texture Type Pixel Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Georgy Gimel'farb
    • 1
  1. 1.CITR, Department of Computer Science, Tamaki CampusThe University of AucklandAucklandNew Zealand

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