Wavelet-based denoising: A brief review

The denoising of Gaussian additive white noise is a classical problem in signal and image processing. In this paper, we classify the most important wavelet denoising methods into different categories and give a brief overview of each method classified. In general, the recently developed block matching and 3D filtering (BM3D) algorithm performs much better than other existing methods published in the literature. We recommend using this method for image denoising because it is currently one of the state-of-the-art denoising methods. The non-local means method and the optimal spatial adaptation (OSA) method are also very successful methods in image denoising.

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