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Chinese Conference on Image and Graphics Technologies

IGTA 2016: Advances in Image and Graphics Technologies pp 160–166Cite as

A Construction Algorithm of Measurement Matrix with Low Coherence for Compressed Sensing

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 634))

Abstract

In order to improve the accuracy and range for application of signal reconstruction, a new measurement matrix optimization method is proposed based on the Gram matrix. The new method can reduce the mutual coherence between the measurement matrix and the sparse transform matrix. Numerical experiments verify the success of the optimized method. Compared with the original Gaussian random matrix and other optimized measurement matrices, the performance and stability of our proposed have a slight increase.

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Author information

Authors and Affiliations

  1. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China

    Shengqin Bian, Zhengguang Xu & Shuang Zhang

Authors
  1. Shengqin Bian
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  2. Zhengguang Xu
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  3. Shuang Zhang
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Corresponding author

Correspondence to Shengqin Bian .

Editor information

Editors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  2. Peking University, Beijing, China

    Guoping Wang

  3. Tsinghua University, Beijing, China

    Shengjin Wang

  4. Beijing Institute of Technology, Beijing, China

    Yue Liu

  5. Peking University, Beijing, China

    Xiaoru Yuan

  6. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Ran He

  7. Peking University, Beijing, China

    Sheng Li

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© 2016 Springer Science+Business Media Singapore

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Cite this paper

Bian, S., Xu, Z., Zhang, S. (2016). A Construction Algorithm of Measurement Matrix with Low Coherence for Compressed Sensing. In: Tan, T., et al. Advances in Image and Graphics Technologies. IGTA 2016. Communications in Computer and Information Science, vol 634. Springer, Singapore. https://doi.org/10.1007/978-981-10-2260-9_18

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  • DOI: https://doi.org/10.1007/978-981-10-2260-9_18

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2259-3

  • Online ISBN: 978-981-10-2260-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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