Markov random field textures and applications in image processing
Contributors: Naval Postgraduate School (U.S.) 
Publisher: Naval Postgraduate School; Available from National Technical Information Service
Published: 1997
Place of publication: Monterey, Calif; Springfield, Va
Language: eng
Number of pages: 67
Subjects: IMAGE PROCESSING; MARKOV PROCESSES
Description: 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.
Notes: Thesis advisors, Carlos Borges, Hal Fredricksen.

AD-A331 947.

Thesis (M.S. in Applied Mathematics) Naval Postgraduate School, March 1997.

Includes bibliographical references (p. 65)

dk/dk cc:9116 11/17/97.