Regularization by Denoising: Clarifications and New Interpretations

@article{Reehorst2018RegularizationBD,
  title={Regularization by Denoising: Clarifications and New Interpretations},
  author={Edward T. Reehorst and Philip Schniter},
  journal={CoRR},
  year={2018},
  volume={abs/1806.02296}
}
Regularization by Denoising (RED), as recently proposed by Romano, Elad, and Milanfar, is powerful imagerecovery framework that aims to minimize an explicit regularization objective constructed from a plug-in image-denoising function. Experimental evidence suggests that the RED algorithms are state-of-the-art. We claim, however, that explicit regularization does not explain the RED algorithms. In particular, we show that many of the expressions in the paper by Romano et al. hold only when the… CONTINUE READING

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