This paper proposes a new image denoising method BlockShrink. BlockShrink is a completely data-driven block thresholding approach and is also easy to implement. It utilizes the pertinence of the neighbor wavelet coefficients by using the block thresholding scheme. It can decide the optimal block size and threshold for every wavelet subband by minimizing Stein's unbiased risk estimate (SURE). BlockShrink enjoys a number of advantages over the other conventional image denoising methods. Experimental results show that BlockShrink outperforms significantly classic SureShrink method and NeighShrink method proposed by Chen et al.
Image Denoising Using Block Thresholding
2008 Congress on Image and Signal Processing ; 3 ; 335-338
01.05.2008
867002 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Image Denoising by Statistical Area Thresholding
British Library Online Contents | 2005
|Adaptive wavelet domain thresholding denoising [5253-51]
British Library Conference Proceedings | 2003
|Entropic Thresholding Using a Block Source Model
British Library Online Contents | 1995
|Median-based image thresholding
British Library Online Contents | 2011
|British Library Conference Proceedings | 1999
|