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Signal Reconstruction Based on Block Compressed Sensing

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Book cover Artificial Intelligence and Computational Intelligence (AICI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7003))

Abstract

Compressed sensing (CS) is a new area of signal processing for simultaneous signal sampling and compression. The CS principle can reduce the computation complexity at the encoder side and transmission costs, but has huge computation load at the decoder. In this paper, a simple block-based compressed sensing reconstruction for still images is proposed. Firstly, original image is divided into small blocks, and each block is sampled independently. Secondly, the image block is divided into flat and non-flat block, and processed with different ways. Finally, mean filter and an improvement total-variation (TV) method is sued to optimize image. Simulation results show that the proposed algorithm can effectively remove the blocking artifacts and reduce the computation complexity.

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Author information

Authors and Affiliations

  1. Tianjin Key Laboratory of Intelligence Computing and, Novel Software Technology, Tianjin University of Technology, 300191, Tianjin, China

    Liqing Sun, Xianbin Wen, Ming Lei, Haixia Xu, Junxue Zhu & Yali Wei

Authors
  1. Liqing Sun
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  2. Xianbin Wen
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  3. Ming Lei
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  4. Haixia Xu
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  5. Junxue Zhu
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  6. Yali Wei
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Editor information

Editors and Affiliations

  1. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, VIC, Australia

    Hepu Deng

  2. School of Electronics and Information, Tongji University, 201804, Shanghai, China

    Duoqian Miao

  3. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  4. Department of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Sun, L., Wen, X., Lei, M., Xu, H., Zhu, J., Wei, Y. (2011). Signal Reconstruction Based on Block Compressed Sensing. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7003. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23887-1_39

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  • DOI: https://doi.org/10.1007/978-3-642-23887-1_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23886-4

  • Online ISBN: 978-3-642-23887-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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