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• W2157294354 abstract "In this paper, we analyze the applicability of Constant Modulus Algorithm (CMA), one of the most widely used and tested blind equalization technique to blind image deconvolution. With a detailed mathematical analysis, we show that the strong correlation between the neighboring spatial locations found in natural images becomes a major constraint on the convergence of CMA. In order to overcome this constraint, we introduce a novel image pixel correlation model in relation with natural image statistics. Based on this model, a segmented blind image deconvolution through CMA is proposed. The robustness of the proposed algorithm with natural images is discussed in terms of efficiency and effectiveness." @default.
• W2157294354 created "2016-06-24" @default.
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• W2157294354 date "2010-12-01" @default.
• W2157294354 modified "2023-09-26" @default.
• W2157294354 title "Blind deconvolution of natural images using segmentation based CMA" @default.
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• W2157294354 doi "https://doi.org/10.1109/icspcs.2010.5709712" @default.
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