NDLI: Spatial-temporal recovery for hierarchical frame based video compressed sensing

Content Provider	IEEE Xplore Digital Library
Author	Wenbin Che Xinwei Gao Xiaopeng Fan Feng Jiang Debin Zhao
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China (Wenbin Che; Xinwei Gao; Xiaopeng Fan; Feng Jiang; Debin Zhao)
Abstract	In this paper, the hierarchical frame based video compressed sensing (CS) framework is proposed, which outperforms the traditional framework through the better exploitation of frames correlation with reference frames, the unequal sample subrates setting among frames in different layers and the reduction of the error propagation. By considering the spatial and temporal correlations of the video sequence, a spatial-temporal sparse representation based recovery is proposed for this framework. The similar blocks in both the current frame and these recovered reference frames are composed as a spatial-temporal group, which is defined as the unit of the sparse representation. By exploiting the low dimensional subspace description of each group, the video CS recovery is converted as a low-rank matrix approximation problem, which can be solved by exploiting the hard thresholding and the gradient descent. Experimental results show that the proposed method achieves better performance against both the state-of-art still-image CS recovery algorithms and the existing residual domain based video CS reconstruction approaches.
Starting Page	1110
Ending Page	1114
File Size	574926
Page Count	5
File Format	PDF
e-ISBN	9781479983391
DOI	10.1109/ICIP.2015.7350972
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Video sequences Compressed sensing Correlation Image reconstruction Sparse matrices Approximation methods Wavelet domain spatial-temporal sparse representation Video compressed sensing hierarchical structure framework
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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