Infrared and Laser Engineering, Volume. 44, Issue 12, 3825(2015)

Joint reconstruction algorithm for distributed compressed sensing

Cui Ping* and Ni Lin
Author Affiliations
  • [in Chinese]
  • show less

    Distributed compressed sensing is concerned with representing an ensemble of jointly sparse signals using as few linear measurements as possible. Joint reconstruction algorithm for distributed compressed perception was based on the idea of using one of the signals as side information, and then reconstruct other signals by the correlation between the side information and other signals. To resolve the complexity of reconstruction algorithms and reduce the measurements, two novel joint reconstruction algorithms for distributed compressed sensing based on joint sparse models were presented in this paper. Its application in signals and images processing was presented which are on the basis of demonstrating its feasibility. The result represent that the two novel joint reconstruction algorithms need fewer measurements for getting the same quality.

    Tools

    Get Citation

    Copy Citation Text

    Cui Ping, Ni Lin. Joint reconstruction algorithm for distributed compressed sensing[J]. Infrared and Laser Engineering, 2015, 44(12): 3825

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: 信息处理

    Received: Apr. 7, 2015

    Accepted: May. 10, 2015

    Published Online: Jan. 26, 2016

    The Author Email: Ping Cui (cuiapple@mail.ustc.edu.cn)

    DOI:

    Topics