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A nonlocal low rank model for poisson noise removal
2020
Inverse Problems and Imaging
Patch-based methods, which take the advantage of the redundancy and similarity among image patches, have attracted much attention in recent years. However, these methods are mainly limited to Gaussian noise removal. In this paper, the Poisson noise removal problem is considered. Unlike Gaussian noise which has an identical and independent distribution, Poisson noise is signal dependent, which makes the problem more challenging. By incorporating the prior that a group of similar patches should
doi:10.3934/ipi.2021003
fatcat:vleeiqedcrarxbw5hyhmg3vi2q