Image denoising is a fundamental and important task in image processing and computer vision fields. A lot of methods are proposed to reconstruct clean images from their noisy versions. These methods differ in both methodology and performance. On one hand, denoising methods can be classified into local and nonlocal methods. On the other hand, they can be marked as spatial and frequency domain methods. Sparse coding and low-rank are two popular techniques for denoising recently. This paper summarizes existing techniques and provides several promising directions for further studying in the future.
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