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redR  

REgularization by Denoising (RED)
View on CRAN: Click here


Download and install redR package within the R console
Install from CRAN:
install.packages("redR")

Install from Github:
library("remotes")
install_github("cran/redR")

Install by package version:
library("remotes")
install_version("redR", "1.0.1")



Attach the package and use:
library("redR")
Maintained by
Adriano Passos
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-06-14
Latest Update: 2018-09-03
Description:
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) . 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'.
How to cite:
Adriano Passos (2017). redR: REgularization by Denoising (RED). R package version 1.0.1, https://cran.r-project.org/web/packages/redR. Accessed 06 Nov. 2024.
Previous versions and publish date:
1.0.0 (2017-06-14 23:52), 1.0.1 (2018-09-03 13:20)
Other packages that cited redR R package
View redR citation profile
Other R packages that redR depends, imports, suggests or enhances
Functions, R codes and Examples using the redR R package
Some associated functions: RED . cameraman . degrade . error . fft_convolve . lenna . register . resample . shift . transform . 
Some associated R codes: RED_pkg.R . convolve.R . data.R . degrade.R . error.R . red.R . registration.R . resample.R . shift.R . transform.R .  Full redR package functions and examples
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