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Contrast enhancement of badly illuminated images based on Gibbs distribution and random walk model

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

In the paper a new approach to the problem of contrast enhancement of grey scale images is presented. The described method is based on a model, which treats the image as a toroidal, two dimensional lattice, the points of which possess a potential energy. On in this way defined lattice, a regular Markov chain of the positions of this particle can be investigated. The probability of a transition of the virtual particle from a fixed lattice point to a point belonging to its neighbourhood can be determined using the Gibbs canonical distribution, defined on an eight-connectiviy system. The idea of the presented algorithm consists in determininig the stationary probability vector of the Markow chain. The new algorithm registers the visits of the wandering particle and then determines their relative frequencies. It performs especially well in case of images with nonuniform brightness.

Original languageEnglish
Title of host publicationComputer Analysis of Images and Patterns - 7th International Conference, CAIP 1997, Proceedings
EditorsGerald Sommer, Kostas Daniilidis, Josef Pauli
PublisherSpringer Verlag
Pages271-278
Number of pages8
ISBN (Print)3540634606, 9783540634607
DOIs
Publication statusPublished - 1997
Event7th International Conference on Computer Analysis of Images and Patterns, CAIP 1997 - Kiel, Germany
Duration: 10 Sept 199712 Sept 1997

Publication series

NameLecture Notes in Computer Science
Volume1296 1296 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Computer Analysis of Images and Patterns, CAIP 1997
Country/TerritoryGermany
CityKiel
Period10/09/9712/09/97

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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