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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Image Denoising Using Block Thresholding


    Contributors:


    Publication date :

    2008-05-01


    Size :

    867002 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Image Denoising by Statistical Area Thresholding

    Coupier, D. / Desolneux, A. / Ycart, B. | British Library Online Contents | 2005


    Adaptive wavelet domain thresholding denoising [5253-51]

    Shi, H. / Cai, Y. / Qiu, Z. et al. | British Library Conference Proceedings | 2003


    Entropic Thresholding Using a Block Source Model

    Beghdadi, A. / Le Negrate, A. / De Lesegno, P. V. | British Library Online Contents | 1995


    Median-based image thresholding

    Xue, J. H. / Titterington, D. M. | British Library Online Contents | 2011


    Scale-band-dependent thresholding for signal denoising using undecimated discrete wavelet packet transforms [3813-51]

    Zhang, H. / Nosratinia, A. / Burrus, C. S. et al. | British Library Conference Proceedings | 1999