Noise reduction of images with multiple subband transforms
Toshihisa Tanaka, Laurent C. Duval · 2005
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.