Learning Non-Locally Regularized Compressed Sensing Network With Half-Quadratic Splitting

Deep learning-based Compressed Sensing (CS) reconstruction attracts much attention in recent years, due to its significant superiority of reconstruction quality. Its success is mainly attributed to the employment of a large dataset for pre-training the network to learn a reconstruction mapping. In t...

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Veröffentlicht in:	IEEE transactions on multimedia 2020-12, Vol.22 (12), p.3236-3248
Hauptverfasser:	Sun, Yubao, Yang, Ying, Liu, Qingshan, Chen, Jiwei, Yuan, Xiao-Tong, Guo, Guodong
Format:	Artikel
Sprache:	eng
Schlagworte:	Compressed sensing Deep learning deep network prior Electronics packaging half-quadratic splitting Image reconstruction Image sequences Machine learning Noise measurement non-local prior Optimization Splitting Training Training data
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