Publication:
Markov random field textures and applications in image processing.

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Authors
Korn, Christopher A.
Subjects
Markov Random Fields
Image Compression
Textures
cliques
neighborhoods
Gibbs Distributions
Advisors
Borges, Carlos
Fredricksen, Hal
Date of Issue
1997-03
Date
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
In the field of image compression, transmission and reproduction, the foremost objective is to reduce the amount of information which must be transmitted. Currently the methods used to limit the amount of data which must be transmitted are compression algorithms using either lossless or lossy compression. Both of these methods start with the entire initial image and compress it using different techniques. This paper will address the use of Markov Random Field Textures in image processing. If there is a texture region in the initial image, the concept is to identify that region and match it to a suitable texture which can then be represented by a Markov random field. Then the region boundaries and the identifying parameters for the Markov texture can be transmitted in place of the initial or compressed image for that region
Type
Thesis
Description
Series/Report No
Department
Applied Mathematics
Other Units
Naval Postgraduate School
Identifiers
NPS Report Number
Sponsors
Funder
Format
xv, 91 p.;28 cm.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
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