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'.
|Author||person("Adriano", "Passos", email="[email protected]", role=c("aut","cre"))|
|Maintainer||Adriano G. Passos <[email protected]>|
|Package repository||View on GitHub|
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