Principle Component based Image De-Noising using Local Pixel Grouping |
Author(s): |
| Sangeeta Rani , GIMT Kanipla Kurukshetra Haryana; Pankaj Dev Chadha, GIMT Kanipla Kurukshetra Haryana |
Keywords: |
| Principal Component Analysis, Local Pixel Grouping, De-Noising, Filter and Discrete Wavelet Transform |
Abstract |
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This paper presents an efficient image de-noising scheme by using principal component analysis (PCA) with local pixel grouping (LPG). For a better preservation of image local structures, a pixel and its nearest neighbors are modeled as a vector variable, whose training samples are selected from the local window by using block matching based LPG. Such an LPG procedure guarantees that only the sample blocks with similar contents are used in the local statistics calculation for PCA transform estimation, so that the image local features can be well preserved after coefficient shrinkage in the PCA domain to remove the noise. This paper also describes how PCA best as compared to mean, median and dwt filters. |
Other Details |
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Paper ID: IJSRDV4I31138 Published in: Volume : 4, Issue : 3 Publication Date: 01/06/2016 Page(s): 1210-1212 |
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