Visible to the public Biblio

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2021-02-15
Zhu, L., Zhou, X., Zhang, X..  2020.  A Reversible Meaningful Image Encryption Scheme Based on Block Compressive Sensing. 2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP). :326–330.
An efficient and reversible meaningful image encryption scheme is proposed in this paper. The plain image is first compressed and encrypted simultaneously by Adaptive Block Compressive Sensing (ABCS) framework to create a noise-like secret image. Next, Least Significant Bit (LSB) embedding is employed to embed the secret image into a carrier image to generate the final meaningful cipher image. In this scheme, ABCS improves the compression and efficiency performance, and the embedding and extraction operations are absolutely reversible. The simulation results and security analyses are presented to demonstrate the effectiveness, compression, secrecy of the proposed scheme.
2018-08-23
Ming, X., Shu, T., Xianzhong, X..  2017.  An energy-efficient wireless image transmission method based on adaptive block compressive sensing and softcast. 2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). :712–717.

With the rapid and radical evolution of information and communication technology, energy consumption for wireless communication is growing at a staggering rate, especially for wireless multimedia communication. Recently, reducing energy consumption in wireless multimedia communication has attracted increasing attention. In this paper, we propose an energy-efficient wireless image transmission scheme based on adaptive block compressive sensing (ABCS) and SoftCast, which is called ABCS-SoftCast. In ABCS-SoftCast, the compression distortion and transmission distortion are considered in a joint manner, and the energy-distortion model is formulated for each image block. Then, the sampling rate (SR) and power allocation factors of each image block are optimized simultaneously. Comparing with conventional SoftCast scheme, experimental results demonstrate that the energy consumption can be greatly reduced even when the receiving image qualities are approximately the same.