Piya Bunyaratavej

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We develop an iterative, hillclimbing-based assignment algorithm for the approximate solution of discrete-parameter cost minimization problems defined on the pixel sites of an image. While the method is applicable to a number of problems including encoding, decoding, and segmentation, this article focuses on entropy-constrained encoding. For typical(More)
Mean-field annealing (MFA) is widely used for optimization tasks involving the determination of a set of discrete-valued assignment variables. One way of deriving MFA is via maximum entropy (ME), where one seeks the joint distribution over the (random) assignments subject to an average level of cost. MFA is obtained by assuming the individual assignments(More)
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