SOS Boosting of Image Denoising Algorithms

2 Are built upon powerful patch-based (local) image models:  Non-Local Means (NLM): self-similarity within natural images  K-SVD: sparse representation modeling of image patches  BM3D: combines a sparsity prior and non local self-similarity  Kernel-regression: offers a local directional filter  EPLL: exploits a GMM model of the image patches  … Today we present a way to improve various such state-of-the-art image denoising methods, simply by applying the original algorithm as a " black-box " several times 3 Are built upon powerful patch-based (local) image models:  Non-Local Means (NLM): self-similarity within natural images  K-SVD: sparse representation modeling of image patches  BM3D: combines a sparsity prior and non local self-similarity  Kernel-regression: offers a local directional filter  EPLL: exploits a GMM model of the image patches  … Today we present a way to improve various such state-of-the-art image denoising methods, simply by applying the original algorithm as a " black-box " several times