Automatic parameter prediction for image denoising algorithms using perceptual quality features

Anish Mittal; Anush K. Moorthy; Alan C. Bovik

doi:10.1117/12.912243

17 February 2012 Automatic parameter prediction for image denoising algorithms using perceptual quality features

Anish Mittal, Anush K. Moorthy, Alan C. Bovik

Author Affiliations +

Proceedings Volume 8291, Human Vision and Electronic Imaging XVII; 82910G (2012) https://doi.org/10.1117/12.912243
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States

Abstract

A natural scene statistics (NSS) based blind image denoising approach is proposed, where denoising is performed without knowledge of the noise variance present in the image. We show how such a parameter estimation can be used to perform blind denoising by combining blind parameter estimation with a state-of-the-art denoising algorithm.1 Our experiments show that for all noise variances simulated on a varied image content, our approach is almost always statistically superior to the reference BM3D implementation in terms of perceived visual quality at the 95% confidence level.

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Anish Mittal, Anish Mittal, Anush K. Moorthy, Anush K. Moorthy, Alan C. Bovik, Alan C. Bovik, "Automatic parameter prediction for image denoising algorithms using perceptual quality features", Proc. SPIE 8291, Human Vision and Electronic Imaging XVII, 82910G (17 February 2012); doi: 10.1117/12.912243; https://doi.org/10.1117/12.912243

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