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Proceedings Paper

Quasi-static algorithm for image restoration preserving discontinuities
Author(s): Donald Prevost; Philippe Lalanne; Line Garnero; Pierre H. Chavel
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Paper Abstract

In the case of image restoration preserving discontinuities, a priori information on image structure is represented (Geman and Geman 1984) in the form of a Markov random field consisting of a coupled field of intensity and binary line processes. We propose a new scheme achieving thermal equilibrium of the continuous intensity field. The scheme consists in adding a quasi-static noise process to the intensity field, i.e. a noise with dynamics much slower than characteristic relaxation times of the field, before going through a deterministic minimization. An algorithm is then devised upon this scheme. When associated with a classical Gibbs sampler algorithm for treatment of the line process, it performs global minimization of the energy. We show that the intensity field evolves in thermal equilibrium and we present simulations illustrating thermal equilibrium of the coupled, intensity and line, field. Our algorithm provides better energy minimization than the mixed annealing, a comparable algorithm in terms of computational loads, while retaining the same good parallel implementation perspectives.

Paper Details

Date Published: 30 June 1994
PDF: 9 pages
Proc. SPIE 2304, Neural and Stochastic Methods in Image and Signal Processing III, (30 June 1994); doi: 10.1117/12.179223
Show Author Affiliations
Donald Prevost, Univ. Paris-Sud (France)
Philippe Lalanne, Univ. Paris-Sud (France)
Line Garnero, Univ. Paris-Sud (France)
Pierre H. Chavel, Univ. Paris-Sud (France)

Published in SPIE Proceedings Vol. 2304:
Neural and Stochastic Methods in Image and Signal Processing III
Su-Shing Chen, Editor(s)

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