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• W2950208209 abstract "We first establish a law of large numbers and a convergence theorem in distribution to show the rate of convergence of the non-local means filter for removing Gaussian noise. We then introduce the notion of degree of similarity to measure the role of similarity for the non-local means filter. Based on the convergence theorems, we propose a patch-based weighted means filter for removing impulse noise and its mixture with Gaussian noise by combining the essential idea of the trilateral filter and that of the non-local means filter. Our experiments show that our filter is competitive compared to recently proposed methods." @default.
• W2950208209 created "2019-06-27" @default.
• W2950208209 creator A5064692524 @default.
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• W2950208209 date "2014-03-11" @default.
• W2950208209 modified "2023-09-25" @default.
• W2950208209 title "Removing Mixture of Gaussian and Impulse Noise by Patch-Based Weighted Means" @default.
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• W2950208209 doi "https://doi.org/10.48550/arxiv.1403.2482" @default.
• W2950208209 hasPublicationYear "2014" @default.
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