低冗余的压缩感知观测

doi:10.3969/j.issn.1001-2400.2012.04.026

Abstract

Abstract:

To solve the difficult problem that it is difficult for traditional compression methods to efficiently reduce compressed sensing measurements, this paper proposes a method for obtaining the low-redundancy compressed sensing measurements based on the mutual coherence theory, set theory and sequential compressed sensing. In the proposed method, according to the mutual coherence theory, a smaller measurement set is obtained by removing some redundant measurements from the original measurement set in the premise of ensuring signal reconstruction. Then, the smaller measurement set obtained above is classified into the key set (only including key measurement) or the non-key set (only including non-key measurement) according to the important degree of each measurement for signal reconstruction. And some non-key measurements are eliminated iteratively in the premise of ensuring signal reconstruction until the measurement set does not contain a non-key measurement again. Experimental results show that the proposed method can only take 40 to 70 percent of the original measurement set to obtain almost the same reconstruction quality as that by the original measurement set.

Key words: compressed sensing, mutual coherence, signal reconstruction, sparse representation, measurement matrix

CLC Number:

TN911. 72

SONG Xiaoxia;SHI Guangming. Low-redundancy compressed sensing measurements[J].J4, 2012, 39(4): 144-148+171.

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Low-redundancy compressed sensing measurements

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