Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Digital Image Processing
Fundamentals of Digital Optics: Digital Signal Processing in Optics and Holography
Fundamentals of Digital Optics: Digital Signal Processing in Optics and Holography
Contrast Enhancement of Badly Illuminated Images Based on Gibbs Distribution and Random Walk Model
CAIP '97 Proceedings of the 7th International Conference on Computer Analysis of Images and Patterns
A New Method of Texture Binarization
CAIP '97 Proceedings of the 7th International Conference on Computer Analysis of Images and Patterns
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In this paper a new approach to the problem of contrast enhancement of gray scale images is presented. The algorithms introduced here are based on a model of a virtual particle, which performs a random walk on the image lattice. It is assumed, that the probability of a transition of the walking particle from a lattice point to a point belonging to its neighbourhood is determined by the Gibbs distribution, defined on a specified neighbourhood system. In this work four algorithms of contrast enhancement are presented. The first algorithm traces the visits of the walking particle and determines their relative frequencies. The second operator assigns to each lattice point the probability of a stationary Markov chain, generated by the trajectory of the randomly walking particle. The third algorithm is based on a concept of a jumping particle and the last one uses the information contained in the statistical sum of the Gibbs distribution of the transition probabilities.