A New Framework for Removing Impulse Noise in an Image

Nonlocal means filter (NLMF) or sparse representation based denoising technology has the remarkable performance in image denoising. In order to combine the advantages of the two methods together, a new image denoising framework is proposed. In this framework, the image containing impulse noise is processed firstly by NLMF to obtain a good temporary denoised image. Based on it, a number of patches are extracted for training a redundant dictionary which is adapted to the target signal. Finally, each noisy image patch in which the impulse noise is replaced by the values from the temporary denoised image is coded sparsely over the dictionary. Then, a clean image patch is reconstructed by multiplying the code efficient and the redundant dictionary. Verified by the extensive experiments, this denoising framework can not only obtain the better performance than that after use individually NLMF or sparse representation technology, but also get an obvious promotion in denoising texture images.