Video Compressed Sensing Using a Convolutional Neural Network

Recently, a few image compressed sensing (CS) methods based on deep learning have been developed, which achieve remarkable reconstruction quality with low computational complexity. However, these existing deep learning-based image CS methods focus on exploring intraframe correlation while ignoring i...

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Veröffentlicht in:	IEEE transactions on circuits and systems for video technology Jg. 31; H. 2; S. 425 - 438
Hauptverfasser:	Shi, Wuzhen, Liu, Shaohui, Jiang, Feng, Zhao, Debin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.02.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Compensation Compressed sensing Computer architecture Convolution convolutional neural network Convolutional neural networks Correlation Deep learning Image reconstruction Machine learning Multilevel multilevel feature compensation Neural networks Reconstruction Sampling video compressed sensing Video compression video reconstruction Video sequences
ISSN:	1051-8215, 1558-2205
Online-Zugang:	Volltext
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