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Review of Shrinkage Techniques for Image Denoising
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 42 - Number 19 |
| Year of Publication: 2012 |
| Authors: Rajesh Kumar Rai, Jyoti Asnani, T. R. Sontakke |
10.5120/5800-8009
|
Rajesh Kumar Rai, Jyoti Asnani, T. R. Sontakke . Review of Shrinkage Techniques for Image Denoising. International Journal of Computer Applications. 42, 19 ( March 2012), 13-16. DOI=10.5120/5800-8009
Abstract
Image denoising is a common procedure to suppress the quality degradation caused by noise. Several image denoising methods are proposed in literature. Amongst these Discrete Wavelet Transform-DWT Filters are very popular. Denoising using the DWT-Transform includes decomposition of the image into various sub bands and then modeling them as independent identically distributed random variables with Gaussian distribution. Shrinkage methods are often used for suppressing Additive White Gaussian Noise (AWGN), where thresholding is used to retain the larger wavelet coefficients alone. Minimum Mean Square Error estimation is a common practice for noise analysis and is thus included in this paper. Overall we discuss in this review briefly the various Shrinkage methods in DWT-Domain Filters and we assess them by posing a comparison between the efficiency of these filters.
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