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- W2347550587 abstract "The method of threshold selection based on two-dimensional maximal Shannon or Tsallis entropy only depends on the probability information from gray histogram of image,and does not directly consider the uniformity of within-cluster gray level.The Shannon entropy defined by logarithm has the problem of undefined value and zero value.Thus,a one-dimensional and two-dimensional exponential gray entropy thresholding method is proposed.Firstly,a definition of the exponential gray entropy is given,and one-dimensional exponential gray entropy method for threshold selection is derived.Then,it is extended and two-dimensional exponential gray entropy thresholding method based on decomposition is proposed.The optimal threshold of one-dimensional exponential gray entropy method for pixel gray-level image or neighborhood average gray-level image is computed,respectively,and they are combined to obtain the optimal threshold of the two-dimensional exponential gray entropy method.As a result,the search space is significantly reduced.The computation complexity is reduced from O(L4) to O(L).The experimental results show that,compared with two-dimensional maximal Shannon or Tsallis entropy thresholding method based on particle swarm optimization(PSO) and two-dimensional cross entropy method with recursion,the method proposed in this paper has much superior segmentation performance and its running time is reduced significantly." @default.
- W2347550587 created "2016-06-24" @default.
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- W2347550587 date "2010-01-01" @default.
- W2347550587 modified "2023-09-23" @default.
- W2347550587 title "Two-dimensional exponential gray entropy image thresholding based on decomposition" @default.
- W2347550587 hasPublicationYear "2010" @default.
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