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 et.al. (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'.
Package details |
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Author | person("Adriano", "Passos", email="adriano.utfpr@gmail.com", role=c("aut","cre")) |
Maintainer | Adriano G. Passos <adriano.utfpr@gmail.com> |
License | GPL-3 |
Version | 1.0.0 |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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