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https://idr.l1.nitk.ac.in/jspui/handle/123456789/12274
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DC Field | Value | Language |
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dc.contributor.author | Yamanappa, W. | - |
dc.contributor.author | Sudeep, P.V. | - |
dc.contributor.author | Sabu, M.K. | - |
dc.contributor.author | Rajan, J. | - |
dc.date.accessioned | 2020-03-31T08:38:54Z | - |
dc.date.available | 2020-03-31T08:38:54Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | IEEE Access, 2018, Vol.6, , pp.66914-66922 | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/12274 | - |
dc.description.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. | en_US |
dc.title | Non-local means image denoising using shapiro-wilk similarity measure | en_US |
dc.type | Article | en_US |
Appears in Collections: | 1. Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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1.Non-Local Means.pdf | 5.38 MB | Adobe PDF | View/Open |
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