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An unsupervised method for segmenting noisy and blurred images is proposed. A Markov random field (MRF) model is used which is robust to degradation. Since this is computationally intensive, a hierarchical distributed genetic algorithm (HDGA) is used which is unsupervised and parallel. Experimental results show that the proposed method is effective at segmenting real images.
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Kim et al. (1998) studied this question.
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