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2011

Image Denoising in Mixed Poisson-Gaussian Noise

13 years 6 months ago
Image Denoising in Mixed Poisson-Gaussian Noise
—We propose a general methodology (PURE-LET) to design and optimize a wide class of transform-domain thresholding algorithms for denoising images corrupted by mixed Poisson–Gaussian noise. We express the denoising process as a linear expansion of thresholds (LET) that we optimize by relying on a purely data-adaptive unbiased estimate of the mean-squared error (MSE), derived in a non-Bayesian framework (PURE: Poisson–Gaussian unbiased risk estimate). We provide a practical approximation of this theoretical MSE estimate for the tractable optimization of arbitrary transform-domain thresholding. We then propose a pointwise estimator for undecimated filterbank transforms, which consists of subband-adaptive thresholding functions with signal-dependent thresholds that are globally optimized in the image domain. We finally demonstrate the potential of the proposed approach through extensive comparisons with state-of-the-art techniques that are specifically tailored to the estimation o...
Florian Luisier, Thierry Blu, Michael Unser
Added 15 May 2011
Updated 15 May 2011
Type Journal
Year 2011
Where TIP
Authors Florian Luisier, Thierry Blu, Michael Unser
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