Modeling Image Analysis Problems Using Markov Random Fields (2000)
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Stan Z. Li
| Citations: | 3 - 0 self |
BibTeX
@MISC{Li00modelingimage,
author = {Stan Z. Li},
title = {Modeling Image Analysis Problems Using Markov Random Fields},
year = {2000}
}
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Abstract
this article are addressed mainly from the computational viewpoint. The primary concerns are how to dene an objective function for the optimal solution for an image analysis problem and how to nd the optimal solution. The reason for dening the solution in an optimization sense is due to various uncertainties in imaging processes. It may be dicult to nd the perfect solution, so we usually look for an optimal one in the sense that an objective, into which constraints are encoded, is optimized







