Saifeng Hu
Nanchang Institute of Technology

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Total Variation based Multivariate Shearlet Shrinkage for Image Reconstruction Chengzhi Deng; Saifeng Hu; Wei Tian; Min Hu; Yan Li; Shengqian Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: January 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

Shearlet as a new multidirectional and multiscale transform is optimally efficient in representing images containing edges. In this paper, a total variation based multivariate shearlet adaptive shrinkage is proposed for discontinuity-preserving image denoising. The multivariate adaptive threshold is employed to reduce the noise. Projected total variation diffusion is used to suppress the pseudo-Gibbs and shearlet-like artifacts. Numerical experiments from piecewise-smooth to textured images demonstrate that the proposed method can effectively suppress noise and nonsmooth artifacts caused by shearlet transform. Furthermore, it outperforms several existing techniques in terms of structural similarity (SSIM) index, peak signal-to-noise ratio (PSNR) and visual quality. DOI: http://dx.doi.org/10.11591/telkomnika.v11i1.1868