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An elastic net-based hybrid hypothesis method for compressed video sensing

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Abstract

Compressed Sensing, an emerging framework for signal processing, can be used in image and video application, especially when available resources at the transmitter side are limited, such as Wireless Multimedia Sensor Networks. For a low-cost and low-power demand, we consider the plain compressive sampling and low sampling rates and propose a Compressed Video Sensing scheme. As a result, most burden of video processing can be shifted to the decoder which employs a hybrid hypothesis prediction method in reconstruction. The Elastic net-based multi-hypothesis mode, one part of the prediction method, combines the multi-hypothesis prediction and the elastic net regression together. And in the process of decoding, either this mode or the single-hypothesis one is implemented based on the threshold which is selected from [1e-11, 1). Both of the prediction modes are carried out in the measurement domain and a residual reconstruction as the final step is executed to accomplish the recovery. According to the performance presented by the simulation results, the proposed multi-hypothesis mode provides a better reconstruction quality than the other multi-hypothesis ones and the proposed scheme outperforms the observed state-of-the-art schemes for compressed-sensing video reconstruction at low sampling rates.

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Acknowledgments

The authors would like to thank Dr. Eric W. Tramel for the helpful discussion on the MH-BCS-SPL method. This work was supported by the National Science Foundation China under grant 60972072 and the 111 Project of China (B08038).

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Authors and Affiliations

  1. School of Telecommunications Engineering, Xidian University, Xi’an, 710071, China

    Jian Chen, Yunzheng Chen & Yonghong Kuo

  2. School of Computer Science and Technology, Xidian University, Xi’an, 710071, China

    Dong Qin

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  1. Jian Chen
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  2. Yunzheng Chen
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  3. Dong Qin
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  4. Yonghong Kuo
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Correspondence to Jian Chen.

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Chen, J., Chen, Y., Qin, D. et al. An elastic net-based hybrid hypothesis method for compressed video sensing. Multimed Tools Appl 74, 2085–2108 (2015). https://doi.org/10.1007/s11042-013-1743-y

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