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Constrained low-tubal-rank tensor recovery for hyperspectral images mixed noise removal by bilateral random projections
In this paper, we propose a novel low-tubal-rank tensor recovery model, which directly constrains the tubal rank prior for effectively removing the mixed Gaussian and sparse noise in hyperspectral images.
Image Denoising by Gaussian Patch Mixture Model and Low Rank Patches
Local patch matching is to find similar patches in a large neighborhood which can alleviate noise effect, but the number of patches may be insufficient.
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