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JEI
2008

Context adaptive image denoising through modeling of curvelet domain statistics

8 years 10 months ago
Context adaptive image denoising through modeling of curvelet domain statistics
We perform a statistical analysis of curvelet coefficients, distinguishing between two classes of coefficients: those that contain a significant noise-free component, which we call the "signal of interest," and those that do not. By investigating the marginal statistics, we develop a prior model for curvelet coefficients. The analysis of the joint intra- and inter-band statistics enables us to develop an appropriate local spatial activity indicator for curvelets. Finally, based on our findings, we present a novel denoising method, inspired by a recent wavelet domain method called ProbShrink. The new method outperforms its wavelet-based counterpart and produces results that are close to those of state-of-the-art denoisers.
Linda Tessens, Aleksandra Pizurica, Alin Alecu, Ad
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2008
Where JEI
Authors Linda Tessens, Aleksandra Pizurica, Alin Alecu, Adrian Munteanu, Wilfried Philips
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