Noise reduction of images with multiple subband transforms (TA-L2)

Author(s) : Toshihisa Tanaka (Tokyo University of Agriculture and Technology, Japan) Laurent Duval (IFP, France)

Abstract : It is reported that the use of multiple subband transforms for thresholding-based denoising gains performance in the mean square error sense. In traditional thresholding-based methods, a noisy image is decomposed by linear transformations such as wavelets, FFT, and so on, and the transformed coefficients are hard-/soft-thresholded. In particular, it is well-known that wavelets work well for denoising. From the viewpoint that wavelets are in a class of subband transforms, we propose a strategy in which multiple subband transforms are switched region by region, i.e. block by block. For reconstruction, the projection-based iterative method is used. Experimental results are pretty good and promising.

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