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• W2115479547 abstract "We develop, analyze, and apply a specific form of mixture modeling for density estimation within the context of image and texture processing. The technique captures much of the higher order, nonlinear statistical relationships present among vector elements by combining aspects of kernel estimation and cluster analysis. Experimental results are presented in the following applications: image restoration, image and texture compression, and texture classification." @default.
• W2115479547 created "2016-06-24" @default.
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• W2115479547 date "1997-02-01" @default.
• W2115479547 modified "2023-10-16" @default.
• W2115479547 title "Cluster-based probability model and its application to image and texture processing" @default.
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• W2115479547 doi "https://doi.org/10.1109/83.551697" @default.
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