Efficient general sparse denoising with non-convex sparse constraint and total variation regularization-Reference-Cited by-同舟云学术

Efficient general sparse denoising with non-convex sparse constraint and total variation regularization

Published:2018-07 Issue: Volume:78 Page:259-264
ISSN:1051-2004
Container-title:Digital Signal Processing
language:en
Short-container-title:Digital Signal Processing

Author:

Deng Shi-Wen^ORCID,Han Ji-Qing

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Signal Processing,Artificial Intelligence,Applied Mathematics,Computer Vision and Pattern Recognition,Statistics, Probability and Uncertainty,Computational Theory and Mathematics

Reference28 articles.

1. Translation-Invariant De-Noising;Coifman,1995

2. Combining the calculus of variations and wavelets for image enhancement;Coifman;Appl. Comput. Harmon. Anal.,2000

3. Reconstruction of wavelet coefficients using total variation minimization;Durand;SIAM J. Sci. Comput.,2003

4. Artifact free signal denoising with wavelets;Durand,2001

5. Total variation wavelet thresholding;Chan;J. Sci. Comput.,2007

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