Share Email Print

Proceedings Paper

Image coding using multiresolution Markov random fields
Author(s): Michel Barlaud; Laure Blanc-Feraud; P. Charbonnier
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The purpose of this paper is to propose a new scheme for image coding from the point of view of inverse problems. The goal is to find an approximation of the image that preserves edges for a given bit rate. In order to achieve better visual quality and to save computation time, the image is first decomposed using biorthogonal wavelets. We assume that wavelet coefficient sub-images can be modeled by Markov random fields (MRF) with line process. The sub- images are then approximated so their entropy decrease and edges are preserved. Thus, the visual quality of the reconstructed image is controlled. We also look at the MRF model and a monoresolution image approximation method, along with a short overview of wavelet-based multiresolution analysis. Finally, we describe the multiresolution coding scheme and give some results.

Paper Details

Date Published: 19 May 1992
PDF: 12 pages
Proc. SPIE 1657, Image Processing Algorithms and Techniques III, (19 May 1992); doi: 10.1117/12.58310
Show Author Affiliations
Michel Barlaud, Univ. de Nice-Sophia Antipolis (France)
Laure Blanc-Feraud, Univ. de Nice-Sophia Antipolis (France)
P. Charbonnier, Univ. de Nice-Sophia Antipolis (France)

Published in SPIE Proceedings Vol. 1657:
Image Processing Algorithms and Techniques III
James R. Sullivan; Benjamin M. Dawson; Majid Rabbani, Editor(s)

© SPIE. Terms of Use
Back to Top