Optimal and Fast Denoising of AWGN using Cluster based and Filtering Approach
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10.5120/15529-4302 |
Mayuri D Kulkarni, Sitendra Tamrakar and Shatendra Dubey. Article: Optimal and Fast Denoising of AWGN using Cluster based and Filtering Approach. International Journal of Computer Applications 89(9):12-14, March 2014. Full text available. BibTeX
@article{key:article,
author = {Mayuri D. Kulkarni and Sitendra Tamrakar and Shatendra Dubey},
title = {Article: Optimal and Fast Denoising of AWGN using Cluster based and Filtering Approach},
journal = {International Journal of Computer Applications},
year = {2014},
volume = {89},
number = {9},
pages = {12-14},
month = {March},
note = {Full text available}
}
Abstract
This paper presents the novel framework, which provides the denoising of image which is corrupted because of additive white Gaussian Noise. This introduction of noise causes degradation of an image. In proposed framework, the image is preprocessed after preprocessing, similar clusters of are accumulated for the filtering. After getting similar clusters, Adaptive Wiener filtering is used to denoise an image. The image quality assessment factors used are Peak Signal-to-noise ratio (PSNR) and structural similarity index (SSIM).
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