Compressive Sensing Reconstruction of Correlated Images Using Joint Regularization

This letter proposes a novel compressive sensing reconstruction method for correlated images by using joint regularization, where a compensation-based adaptive total variation (CATV) regularization and a multi-image nonlocal low-rank (MNLR) regularization are included. In CATV, local weights are ass...

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Veröffentlicht in:	IEEE signal processing letters 2016-04, Vol.23 (4), p.449-453
Hauptverfasser:	Kan Chang, Ding, Pak Lun Kevin, Baoxin Li
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Compressed sensing Compressive sensing Correlation Detection Image reconstruction Minimization motion estimation/disparity estimation (ME/DE) nonlocal low-rank regularization (NLR) Reconstruction Regularization Reliability Signal processing algorithms Similarity total variation Video sequences
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