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2000
IEEE

Spatially Adaptive Image Denoising Under OverComplete Expansion

9 years 11 months ago
Spatially Adaptive Image Denoising Under OverComplete Expansion
This paper presents a novel wavelet-based image denoising algorithm under overcomplete expansion. In order to optimize the denoising performance, we make a systematic study of both signal and noise characteristics under overcomplete expansion. Highband coefficients are viewed as the mixture of non-edge class and edge class observing different probability models. Based on improved statistical modeling of wavelet coefficients, we deriveoptimalMMSE estimation strategies to suppress noise for both non-edge and edge coefficients. We have achieved fairly better objective performance than most recently-published wavelet denoising schemes.
Xin Li, Michael T. Orchard
Added 25 Oct 2009
Updated 25 Oct 2009
Type Conference
Year 2000
Where ICIP
Authors Xin Li, Michael T. Orchard
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