Bayesian restoration of image sequences using 3-D Markov random fields
- 13 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
The authors describe a method for restoring sequences of noisy images obtained by acquiring different views of the same scene. The method uses a 3-D Markov random field and a least-square-error matching to establish the temporal-spatial neighborhood of a pixel in an image under restoration. The problem of image sequence restoration is posed as the problem of maximizing the conditional probabilities. This task is accomplished by a modified version of the iterated conditional modes method where Gibbs distribution is used to model the prior probability.Keywords
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