Acta Optica Sinica, Volume. 33, Issue 2, 220001(2013)

Separation Research of Measurement Matrices Based on 0-1 Sparse Circulant Matrix

Cheng Tao1,2、*, Zhu Guobin1, and Liu Yu′an1
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  • 1[in Chinese]
  • 2[in Chinese]
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    Current optimization of measurement matrix of compressive sensing is optimization beforehand by using the same matrix in measurement and reconstruction stages. Transition matrix and optimization algorithm mainly based on row transformation are proposed to separate the measurement matrix and reconstruction matrix of compressive sensing. 0-1 sparse matrix of single-pixel camera is adopted during measurement, while approximate matrix is adopted during reconstruction. It is a kind of afterwards optimization method of measurement data and measurement matrix, different from traditional thinking. Theory analysis and experiment results demonstrate that the characteristics of optimal matrix are better than circulant sparse matrix, and approximate matrix and optimal matrix have similar characteristics. The research results reduce the difficulty of engineering design and implementation of measurement matrix.

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    Cheng Tao, Zhu Guobin, Liu Yu′an. Separation Research of Measurement Matrices Based on 0-1 Sparse Circulant Matrix[J]. Acta Optica Sinica, 2013, 33(2): 220001

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    Paper Information

    Category: Optics in Computing

    Received: Aug. 1, 2012

    Accepted: --

    Published Online: Nov. 9, 2012

    The Author Email: Tao Cheng (ctnp@163.com)

    DOI:10.3788/aos201333.0220001

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