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Decomposition of Images with Optimal Algorithmic Approach


Vaijayanti Ramesh Jadhav , MET'S BKC IOE adgaon,Nashik.; Dr. M. U. Kharat, MET'S BKC IOE adgaon,Nashik.


Image Denoising, Spectral Decomposition, Non-Local Filters, Nystrom Extension, Spatial Domain Filter, Risk Estimator


Image denoising can be performed by patch matching technique whereas patch-based methods are dependent on patch matching but their performance get degraded due to find sufficient similar patches. In patch matching, as the number of patches grows, performance improvement due to more patches is less because of finding sufficiently close matches. The effect of patch based methods, are better, because they are limited in how well they can do for larger images with increasing complexity. This paper address this disadvantage by developing global filtering where each pixel is estimated from all pixels in the image. Method of image denoising is applied in two fold First, The proposed filter gives statistical analysis, based on spectral decomposition of corresponding operator. Second, to derive an approximation to the spectral (principal) components using the Nystrom extension. This system demonstrates that this global filter can be implemented by sampling a fairly small percentage of the pixels in the image.

Other Details

Paper ID: IJSRDV5I50874
Published in: Volume : 5, Issue : 5
Publication Date: 01/08/2017
Page(s): 520-523

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