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Noisy image reconstruction based on low-rank in UAV wireless transmission

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Abstract

Compressed sensing changes the conventional image processing model of full collection-sampling-compression-transmission-reconstruction and provides a more feasible way to the UAV wireless transmission. Existing matching pursuit algorithms cannot simultaneously meet the requirements of reconstruction accuracy and reconstruction efficiency in UAV wireless transmission, especially when the images are polluted by some noise. Hence, we propose an effective noisy image reconstruction algorithm based on low-rank which introduces the low-rank matrix decomposition and the Augmented Lagrange Multiplier to realize the tradeoff between reconstruction accuracy and reconstruction efficiency. Experimental results verify that the proposed LR algorithm has a superior and stable reconstruction performance on noisy image reconstruction compared with the matching pursuit algorithms.

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Acknowledgements

The research work reported in this paper is supported by the Fundamental Research Funds for the Central Universities (2042017kf0044), China Postdoctoral Science Foundation (Grant Nos. 2016M592409, 2017M612511), the National Natural Science Foundation of China (Nos. 61701453, 61572372) and National Program on Key Basic Research Project (No. 2011CB302306). In addition, this work is partially supported by the LIESMARS Special Research Funding and Open Funding of NUIST, PAPD and CICAEET.

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Authors and Affiliations

  1. Faculty of Information Engineering, China University of Geosciences, Wuhan, 430074, China

    Shihong Yao & Qingfeng Guan

  2. Collaborative Innovation Center for Geospatial Technology, Wuhan University, Wuhan, 430079, China

    Tao Wang

  3. State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China

    Tao Wang

  4. Key Lab for Environmental Computation and Sustainability of Liaoning Province, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 10016, China

    Xiao Xie

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  1. Shihong Yao
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  2. Tao Wang
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  3. Qingfeng Guan
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  4. Xiao Xie
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Correspondence to Tao Wang.

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Yao, S., Wang, T., Guan, Q. et al. Noisy image reconstruction based on low-rank in UAV wireless transmission. Cluster Comput 22 (Suppl 5), 10717–10728 (2019). https://doi.org/10.1007/s10586-017-1163-2

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  • DOI: https://doi.org/10.1007/s10586-017-1163-2

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