Cart (Loading....) | Create Account
Close category search window
 

Multiscale representations of 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
$31 $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

4 Author(s)
Luettgen, M.R. ; MIT Lab. for Inf. & Decision Syst., Cambridge, MA, USA ; Karl, W.C. ; Willsky, A.S. ; Tenney, R.R.

A framework for multiscale stochastic modeling was introduced (K.C. Chou et al., 1989) based on coarse-to-fine scale-recursive dynamics defined on trees. This model class has some attractive characteristics which lead to extremely efficient, statistically optimal signal and image processing algorithms. In the present work, the authors describe how 1-D Markov processes and 2-D Markov random fields (MRFs) can be represented within this framework. In addition, they propose a framework for reduced-order multiscale modeling of Gaussian MRFs.<>

Published in:

Acoustics, Speech, and Signal Processing, 1993. ICASSP-93., 1993 IEEE International Conference on  (Volume:5 )

Date of Conference:

27-30 April 1993

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.