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2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW) (2014)
Chengdu, China
July 14, 2014 to July 18, 2014
ISSN: 1945-7871
ISBN: 978-1-4799-4717-1
pp: 1-5
Zongxin Yu , School of Communication & Information Engineering, Shanghai University, China
Rui Wang , School of Communication & Information Engineering, Shanghai University, China
Haiyan Zhang , School of Communication & Information Engineering, Shanghai University, China
Yanliang Jin , School of Communication & Information Engineering, Shanghai University, China
Yixing Fu , School of Communication & Information Engineering, Shanghai University, China
ABSTRACT
Distributed compressed sensing (DCS) is able to exploit both intra-and inter-signal correlation structures of multi-signal ensemble. This paper proposes a DCS scheme for image signal compression and reconstruction. The key idea is to exploit the inter-correlation of the blocks that split from the image. Significantly, joint sparse model was employed to compress the intra- and inter-redundancy of the image signal. Moreover, our scheme allocates more sensing resources to common component while fewer measurements for innovation component. In order to improve the performance, we also utilize variable sizes method to replace the uniform size approach for image split. Experimental results on natural images validate that the proposed DCS scheme validly improves the reconstructed image quality with fewer measurements compared to the existing CS schemes.
INDEX TERMS
Image coding, Image reconstruction, Compressed sensing, Joints, Correlation, Vectors, Sensors
CITATION

Zongxin Yu, Rui Wang, Haiyan Zhang, Yanliang Jin and Yixing Fu, "Distributed compressed sensing for image signals," 2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), Chengdu, China, 2014, pp. 1-5.
doi:10.1109/ICMEW.2014.6890579
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