redR: REgularization by Denoising (RED)

Regularization by Denoising uses a denoising engine to solve many image reconstruction ill-posed inverse problems. This is a R implementation of the algorithm developed by Romano (2016) <arXiv:1611.02862>. Currently, only the gradient descent optimization framework is implemented. Also, only the median filter is implemented as a denoiser engine. However, (almost) any denoiser engine can be plugged in. There are currently available 3 reconstruction tasks: denoise, deblur and super-resolution. And again, any other task can be easily plugged into the main function 'RED'.

Getting started

Package details

AuthorAdriano Passos [aut, cre]
MaintainerAdriano Passos <>
Package repositoryView on CRAN
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redR documentation built on May 2, 2019, 3:47 p.m.