Research Article
A Joint Source-Channel Error Protection Transmission Scheme Based on Compressed Sensing for Space Image Transmission
@INPROCEEDINGS{10.1007/978-3-319-73447-7_49, author={Dongqing Li and Junxin Luo and Tiantian Zhang and Shaohua Wu and Qinyu Zhang}, title={A Joint Source-Channel Error Protection Transmission Scheme Based on Compressed Sensing for Space Image Transmission}, proceedings={Machine Learning and Intelligent Communications. Second International Conference, MLICOM 2017, Weihai, China, August 5-6, 2017, Proceedings, Part II}, proceedings_a={MLICOM}, year={2018}, month={2}, keywords={Compressed sensing Error-tolerance Space image transmission Deep Learning}, doi={10.1007/978-3-319-73447-7_49} }- Dongqing Li
Junxin Luo
Tiantian Zhang
Shaohua Wu
Qinyu Zhang
Year: 2018
A Joint Source-Channel Error Protection Transmission Scheme Based on Compressed Sensing for Space Image Transmission
MLICOM
Springer
DOI: 10.1007/978-3-319-73447-7_49
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.