Iterative adaptive nonconvex low-rank tensor approximation to image restoration based on ADMM

DOI10.1007/s10851-018-0867-0zbMath1492.68138OpenAlexW2907128813WikidataQ113106926 ScholiaQ113106926MaRDI QIDQ1999470

Zhengwei Shen, Huitong Sun

Publication date: 27 June 2019

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10851-018-0867-0

zbMATH Keywords

ADMMimage restorationnonconvex penaltylow-rank tensor approximation

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Multilinear algebra, tensor calculus (15A69)

Related Items

A convex relaxation framework consisting of a primal-dual alternative algorithm for solving \(\ell_0\) sparsity-induced optimization problems with application to signal recovery based image restoration

Uses Software

• BM3D

Cites Work

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