Abstract
We describe an image reconstruction problem and the computational difficulties arising in determining the maximum a posteriori (MAP) estimate. Two algorithms for tackling the problem, iterated conditional modes (ICM) and simulated annealing, are usually applied pixel by pixel. The performance of this strategy can be poor, particularly for heavily degraded images, and as a potential improvement Jubb and Jennison (1991) suggest the cascade algorithm in which ICM is initially applied to coarser images formed by blocking squares of pixels. In this paper we attempt to resolve certain criticisms of cascade and present a version of the algorithm extended in definition and implementation. As an illustration we apply our new method to a synthetic aperture radar (SAR) image. We also carry out a study of simulated annealing, with and without cascade, applied to a more tractable minimization problem from which we gain insight into the properties of cascade algorithms.
Original language | English |
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Pages (from-to) | 175-190 |
Number of pages | 16 |
Journal | Statistics and Computing |
Volume | 5 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Sept 1995 |
Bibliographical note
Copyright:Copyright 2007 Elsevier B.V., All rights reserved.
Keywords
- Image analysis
- MAP estimation
- multi-resolution
- optimization
- simulated annealing
ASJC Scopus subject areas
- Theoretical Computer Science
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Computational Theory and Mathematics