The Noise Clinic: a Blind Image Denoising Algorithm

  • Lebrun M
  • Colom M
  • Morel J
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Abstract

This paper describes the complete implementation of a blind image denoising 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 adap- tation 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 on scans of old photographs.

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Lebrun, M., Colom, M., & Morel, J.-M. (2015). The Noise Clinic: a Blind Image Denoising Algorithm. Image Processing On Line, 5, 1–54. https://doi.org/10.5201/ipol.2015.125

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