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Proceedings Paper

Image Synthesis And Coding Using Gaussian Markov Random Field Models
Author(s): R. Chellappa; R. Bagdazian
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Paper Abstract

The purpose of this paper is to illustrate the usefulness of two- dimensional (2-D) Gaussian Markov random field models for synthesis and coding of textures. The MRF models used are non causal; the mean of observation y(s) at position s is written as a linear weighted sum of observations surrounding s in all directions. The method of least squares is used to obtain estimates of the model parameters. The model is then used with appropriate boundary conditions to regenerate the original image. Results obtained indicate that this method could be used to code textures at low bit rates.

Paper Details

Date Published: 17 March 1983
PDF: 8 pages
Proc. SPIE 0359, Applications of Digital Image Processing IV, (17 March 1983); doi: 10.1117/12.965982
Show Author Affiliations
R. Chellappa, University of Southern California (United States)
R. Bagdazian, Hughes Aircraft Company (United States)

Published in SPIE Proceedings Vol. 0359:
Applications of Digital Image Processing IV
Andrew G. Tescher, Editor(s)

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