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International Conference on Communications and Networking in China

ChinaCom 2019: Communications and Networking pp 37–46Cite as

Analog Images Communication Based on Block Compressive Sensing

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Abstract

Recently, owing to graceful performance degradation for various wireless channels, analog visual transmission has attracted considerable attention. The pioneering work about analog visual communication is SoftCast, and many advanced works are all based on the framework of SoftCast. In this paper, we propose a novel analog image communication system called CSCast based block compressive sensing. Firstly, we present the system framework and detailed design of CSCast, which consists of discrete wavelet transform, power scaling, compressive sampling and analog modulation. Furthermore, we discuss how to determine the appropriate value of scaling factor \(\alpha \) in power allocation, and block size of measurement matrix in compressive sampling. Simulations show that the performance of CSCast better than Softcast in all SNR range, and better than Cactus in high SRN range. In particular, CSCast outperforms over Softcast about 1.72 dB. And CSCast achieves the maximum average PSNR gain 1.8 dB over Cacuts and 2.03 dB over SoftCast when SNR = 25 dB, respectively. In addition, our analyses shows CSCast can save about 75% overhead comparing to SoftCast and Cactus.

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Acknowledgment

This work was supported in part by the National Nature Science Foundation of China (No. 61601128, 61762053, 61962003), the Science and Technology Plan Funding of Jiangxi Province of China (No. 20151BBE50076), the Research Foundations of Education Bureau of Jiangxi Province (No. GJJ151001, No. GJJ150984), and the Open Project Funding of Key Laboratory of Jiangxi Province for Numerical Simulation and Emulation Techniques, China.

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Authors and Affiliations

  1. School of Mathematics and Computer Science, Gannan Normal University, Ganzhou, China

    Min Wang, Jiamei Luo & Qin Zou

  2. College of Electronics and Information Engineering, Jinggangshan University, Ji’an, China

    Bin Tan

  3. Key Laboratory of Jiangxi Province for Numerical Simulation and Emulation Techniques, Ganzhou, China

    Min Wang

Authors
  1. Min Wang
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  2. Bin Tan
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  3. Jiamei Luo
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  4. Qin Zou
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Corresponding author

Correspondence to Qin Zou .

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Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Honghao Gao

  2. School of Computer Software, Tianjin University, Tianjin, China

    Zhiyong Feng

  3. Hangzhou Dianzi University, Hangzhou, China

    Jun Yu

  4. Tongji University, Shanghai Shi, China

    Jun Wu

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Wang, M., Tan, B., Luo, J., Zou, Q. (2020). Analog Images Communication Based on Block Compressive Sensing. In: Gao, H., Feng, Z., Yu, J., Wu, J. (eds) Communications and Networking. ChinaCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 313. Springer, Cham. https://doi.org/10.1007/978-3-030-41117-6_4

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  • DOI: https://doi.org/10.1007/978-3-030-41117-6_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41116-9

  • Online ISBN: 978-3-030-41117-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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