Image coding using multiresolution Markov random fields

Michel Barlaud; Laure Blanc-Feraud; P. Charbonnier

doi:10.1117/12.58310

19 May 1992 Image coding using multiresolution Markov random fields

Michel Barlaud, Laure Blanc-Feraud, P. Charbonnier

Proceedings Volume 1657, Image Processing Algorithms and Techniques III; (1992) https://doi.org/10.1117/12.58310
Event: SPIE/IS&T 1992 Symposium on Electronic Imaging: Science and Technology, 1992, San Jose, CA, United States

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.

Citation Download Citation

Michel Barlaud, Laure Blanc-Feraud, and P. Charbonnier "Image coding using multiresolution Markov random fields", Proc. SPIE 1657, Image Processing Algorithms and Techniques III, (19 May 1992); https://doi.org/10.1117/12.58310

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