By Topic

Random walk approach to image enhancement

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
B. Smolka ; Dept. of Autom. Electron. & Comput. Sci., Silesian Univ. of Technol., Gliwice, Poland ; K. W. Wojciechowski ; M. Szczepanski

In the presented paper a new probabilistic approach to the problem of image enhancement has been 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 or median distribution, defined on a specified neighbourhood system. In this work two new algorithms of contrast enhancement has been presented. The first algorithm is based on a concept of a jumping particle and the second makes use of the information contained in the statistical sum of the Gibbs distribution of transition probabilities. The probabilistic algorithms of noise reduction presented in this paper constitute new efficient techniques of noise suppression, capable of preserving edges and other image features. They can can be seen as a generalization and refinement of the commonly used smoothing operations applied in the spatial domain

Published in:

Image Analysis and Processing, 1999. Proceedings. International Conference on

Date of Conference:

1999