Projection Matrix Design for Co-Sparse Analysis Model Based Compressive Sensing
Keyword(s):
Co-sparse analysis model based-compressive sensing (CAMBCS) has gained attention in recent years as alternative to conventional sparse synthesis model based (SSMB)-CS. The equivalent operator as counterpart of the equivalent dictionary in the SSMB-CS is introduced in the CAMB-CS as the product of projection matrix and transpose of the analysis dictionary. This paper proposes an algorithm for designing suitable projection matrix for CAMB-CS by minimizing the mutual coherence of the equivalent operator based on equiangular tight frames design. The simulation results show that the CAMB-CS with the proposed projection matrix outperforms the SSMB-CS in terms of the signal quality reconstruction.
2021 ◽
Vol 69
(11)
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pp. 113-121
2012 ◽
Vol 263-266
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pp. 1008-1011
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2012 ◽
Vol 436
(5)
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pp. 1014-1027
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Keyword(s):
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2009 ◽
Vol 157
(6)
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pp. 789-815
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