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Title: Non-local means image denoising using shapiro-wilk similarity measure
Authors: Yamanappa, W.
Sudeep, P.V.
Sabu, M.K.
Rajan, J.
Issue Date: 2018
Citation: IEEE Access, 2018, Vol.6, , pp.66914-66922
Abstract: Most of the real-time image acquisitions produce noisy measurements of the unknown true images. Image denoising is the post-acquisition technique to improve the signal-to-noise ratio of the acquired images. Denoising is an essential pre-processing step for different image processing applications such as image segmentation, feature extraction, registration, and other quantitative measurements. Among different denoising methods proposed in the literature, the non-local means method is a preferred choice for images corrupted with an additive Gaussian noise. A conventional non-local means filter (CNLM) suppresses noise in a given image with minimum loss of structural information. In this paper, we propose modifications to the CNLM algorithm where the samples are selected statistically using Shapiro-Wilk test. The experiments on standard test images demonstrate the effectiveness of the proposed method. 2013 IEEE.
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