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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Vydané v:	Knowledge-based systems Ročník 330; s. 114577
Hlavní autori:	Shi, Baoshun, Li, Dan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 25.11.2025
Predmet:	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
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