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Optimal smoothing of binary Markov sequences by genetic algorithm and its application to image restoration

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3 Author(s)
Hatanaka, T. ; Dept. of Inf. & Knowledge Eng., Tottori Univ., Japan ; Uosaki, K. ; Ueta, T.

Two-state Markov models play important roles in analysis of physical and engineering phenomena. When the Markov sequence cannot be observed directly but through some noisy observation system, a “most likely” estimate of the underlying Markov sequence should be estimated from its noise-corrupted observation sequence. Although the estimate can be obtained by the integer programming approach, it is too tedious for long sequences. In this paper, a simple approach based on the genetic algorithm is proposed to obtain the estimate. A numerical example illustrates its applicability. The restoration of noisy binary images composed by N×M pixels is considered as an application of the proposed smoothing method

Published in:

Evolutionary Computation, 1996., Proceedings of IEEE International Conference on

Date of Conference:

20-22 May 1996