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.
Automatic parameter prediction for image denoising algorithms using perceptual quality features
Human Vision and Electronic Imaging XVII ; 2012 ; Burlingame,California,USA
Proc. SPIE ; 8291
2012-02-05
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Automatic parameter regulation of perceptual systems
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