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Found 4 papers, 0 papers with code
Low rank prior and l0 norm to remove impulse noise in images
Patch-based low rank is an important prior assumption for image processing.
Spatial-Frequency Domain Nonlocal Total Variation for Image Denoising
Following the pioneering works of Rudin, Osher and Fatemi on total variation (TV) and of Buades, Coll and Morel on non-local means (NL-means), the last decade has seen a large number of denoising methods mixing these two approaches, starting with the nonlocal total variation (NLTV) model.
A note on patch-based low-rank minimization for fast image denoising
Patch-based low-rank minimization for image processing attracts much attention in recent years.
Removing Mixture of Gaussian and Impulse Noise by Patch-Based Weighted Means
We first establish a law of large numbers and a convergence theorem in distribution to show the rate of convergence of the non-local means filter for removing Gaussian noise.
