Abstract
High reliable and efficient image transmission is of primary significance for the space image transmission systems. However, typical image compression techniques have the characteristics of high encoding complexity and limited resiliency to channel errors. And the typical channel decoding strategy is simply discarding the error data block. All of this results in the potential loss of the transmission performance. Due to the low encoding complexity and error-tolerance ability of the compressed sensing (CS), to improve the image transmission performance, this paper proposes a joint source-channel error protection transmission scheme based on CS for space image transmission. Meanwhile, we evaluate the performance of different CS reconstruction algorithms under the two schemes and solve the optimal decoding strategy under different conditions. Simulation results show that the proposed scheme can achieve a better performance than the typical transmission scheme that the error data block is simply discarded in the bottom layer.
D. Li, J. Luo and T. Zhang—These authors contributed equally to this work.
This research has been sponsored in part by the National Natural Science Foundation of China (Grant nos. 61371102, 61001092, 61201144 and 91638204) and the Natural Science Foundation of Guangdong Province (Grant no. 2015A030310343).
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Li, D., Luo, J., Zhang, T., Wu, S., Zhang, Q. (2018). A Joint Source-Channel Error Protection Transmission Scheme Based on Compressed Sensing for Space Image Transmission. In: Gu, X., Liu, G., Li, B. (eds) Machine Learning and Intelligent Communications. MLICOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-319-73447-7_49
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DOI: https://doi.org/10.1007/978-3-319-73447-7_49
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