By Topic

Fractal characterisation of non-Gaussian critical Markov random fields

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

1 Author(s)
R. Ghozi ; Dept. of Appl. Math & Digital Commun., Ecole Superieure de Commun. de Tunis, Tunisia

We characterize a class of self-similar non-Gaussian Markov random fields (MRFs) that we call critical MRFs (CMRFs). We show that since the partition function in a Gibbs distribution of a CMRF is necessarily scale invariant, all order statistics generated from the partition function are generalized homogenous functions. This implies that the correlation function has long-range memory since it decays as a power-law function, a very important characteristic of many textures. This characterization is potentially of great use in modeling a wide variety of multi-dimensional spatial phenomena

Published in:

Signal Processing and its Applications, Sixth International, Symposium on. 2001  (Volume:2 )

Date of Conference: