Improving K-SVD denoising by post-processing its method-noise
Yaniv Romano, Michael Elad · 2013
Various patch-based image denoising algorithms have been shown to be very effective. Nevertheless, in most cases the difference between the noisy image and its denoised version (called “method-noise”) still contains traces of the original image content. In this paper we propose a novel technique for improving the K-SVD denoising results. Our scheme starts by applying the K-SVD on the given noisy image. Then, for each patch, we recover the “stolen” image content information from the method-noise by performing iterations of de-noising using the same atoms that represent the first-stage de-noised patch. Experimental results demonstrate the efficiency of this technique.