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Adaptive temporal compressive sensing for video

dc.contributor.author Yuan, X
dc.contributor.author Yang, J
dc.contributor.author Llull, P
dc.contributor.author Liao, X
dc.contributor.author Sapiro, G
dc.contributor.author Brady, DJ
dc.contributor.author Carin, L
dc.date.accessioned 2014-07-22T16:04:51Z
dc.date.issued 2013-12-01
dc.identifier.uri https://hdl.handle.net/10161/8941
dc.description.abstract This paper introduces the concept of adaptive temporal compressive sensing (CS) for video. We propose a CS algorithm to adapt the compression ratio based on the scene's temporal complexity, computed from the compressed data, without compromising the quality of the reconstructed video. The temporal adaptivity is manifested by manipulating the integration time of the camera, opening the possibility to realtime implementation. The proposed algorithm is a generalized temporal CS approach that can be incorporated with a diverse set of existing hardware systems. © 2013 IEEE.
dc.publisher IEEE
dc.relation.ispartof 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
dc.relation.isversionof 10.1109/ICIP.2013.6738004
dc.title Adaptive temporal compressive sensing for video
dc.type Journal article
duke.contributor.id Liao, X|0265811
duke.contributor.id Sapiro, G|0597407
duke.contributor.id Brady, DJ|0273771
duke.contributor.id Carin, L|0100049
pubs.begin-page 14
pubs.end-page 18
pubs.organisational-group Duke
pubs.organisational-group Duke Institute for Brain Sciences
pubs.organisational-group Electrical and Computer Engineering
pubs.organisational-group Institutes and Provost's Academic Units
pubs.organisational-group Mathematics
pubs.organisational-group Pratt School of Engineering
pubs.organisational-group Trinity College of Arts & Sciences
pubs.organisational-group University Institutes and Centers
pubs.publication-status Published


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