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Research Article Open Access
The main challenge in digital image processing is to remove noise from the original image. This paper reviews the existing denoising algorithms and performs their comparative study. Different noise models including additive and multiplicative types are discussed in the paper.Selection of the denoising algorithm is application dependent. Hence, it is necessary to have knowledge about the noise present in the image so as to select the appropriate denoising algorithm. Here we put results of different approaches of wavelet based image denoising methods using several thresholding techniques such as BayesShrink,SureShrink, and VisuShrink.A quantitative measure of comparison is provided by SNR (signal to noise ratio) and mean square error (MSE).