- published
- 2015-01-28
- reference
- Marc Lebrun, Miguel Colom, and Jean-Michel Morel, The Noise Clinic: a Blind Image Denoising Algorithm, Image Processing On Line, 5 (2015), pp. 1–54. https://doi.org/10.5201/ipol.2015.125
Communicated by Jacques Froment
Demo edited by Miguel Colom
Abstract
This paper describes the complete implementation of a blind image algorithm, that takes any digital image as input. In a first step the algorithm estimates a Signal and Frequency Dependent (SFD) noise model. In a second step, the image is denoised by a multiscale adaptation of the Non-local Bayes denoising method. We focus here on a careful analysis of the denoising step and present a detailed discussion of the influence of its parameters. Extensive commented tests of the blind denoising algorithm are presented, on real JPEG images and scans of old photographs.
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History
- Note from the editor: the manuscript of the article was modified on 2022-01-01 to include information about its editors. The original version of the manuscript is available here.