T. T. Cai and H. H. Zhou, “A Data-Driven Block Thresholding Approach to Wavelet Estimation,” Annals of Statistics, Vol. 37, No. 2, 2009, pp. 569-595. doi:10.1214/07-AOS538

has been cited by the following article:

• TITLE: An Improved Image Denoising Method Based on Wavelet Thresholding

  AUTHORS: Hari Om, Mantosh Biswas

  KEYWORDS: Wavelet Transforms; Neighboring Coefficients; Wavelet Thresholding; Image Denosing; Neighbouring Coefficients; Peak Signal-to-Noise Ratio

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.3 No.1, February 29, 2012

  ABSTRACT: VisuShrink, ModineighShrink and NeighShrink are efficient image denoising algorithms based on the discrete wavelet transform (DWT). These methods have disadvantage of using a suboptimal universal threshold and identical neighbouring window size in all wavelet subbands. In this paper, an improved method is proposed, that determines a threshold as well as neighbouring window size for every subband using its lengths. Our experimental results illustrate that the proposed approach is better than the existing ones, i.e., NeighShrink, ModineighShrink and VisuShrink in terms of peak signal-to-noise ratio (PSNR) i.e. visual quality of the image.