Backtracking-based iterative regularization method for image compressive sensing recovery

DOI10.3390/a10010007zbMath1461.68243OpenAlexW2568895469MaRDI QIDQ1662590

Zhonghua Xie, Lingjun Liu, Jiuchao Feng

Publication date: 20 August 2018

Published in: Algorithms (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3390/a10010007

zbMATH Keywords

backtrackingcompressive sensing (CS)iterative shrinkage-thresholding (IST)nonlocal regularization

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) (aspects in computer science) (68P30)

Uses Software

• TwIST

Cites Work

• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• From Denoising to Compressed Sensing
• Compressive Imaging Using Approximate Message Passing and a Markov-Tree Prior
• Compressive Sensing via Nonlocal Low-Rank Regularization
• An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
• Fast Image Recovery Using Variable Splitting and Constrained Optimization

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