Deep sparse representation driven network for compressive imaging

•We propose a novel deep sparse representation model-driven network termed DeSRNet.•The local and global features are explicitly exploited to generate adaptive thresholds.•The proposed unrolled iterative method termed DUN-DeSRNet can achieve high-quality reconstructions in CI tasks.•We prove that DU...

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Bibliographic Details

Published in:	Knowledge-based systems Vol. 330; p. 114577
Main Authors:	Shi, Baoshun, Li, Dan
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 25.11.2025
Subjects:	Compressed sensing magnetic resonance imaging Deep neural network Deep sparse representation Deep unfolding Snapshot compressive imaging Deep unfolding Deep neural network Deep sparse representation Snapshot compressive imaging Compressed sensing magnetic resonance imaging
ISSN:	0950-7051
Online Access:	Get full text
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