15 November 2016 Nonconvex compressive video sensing
Author Affiliations +
J. of Electronic Imaging, 25(6), 063003 (2016). doi:10.1117/1.JEI.25.6.063003
High-speed cameras explore more details than normal cameras in the time sequence, while the conventional video sampling suffers from the trade-off between temporal and spatial resolutions due to the sensor’s physical limitation. Compressive sensing overcomes this obstacle by combining the sampling and compression procedures together. A single-pixel-based real-time video acquisition is proposed to record dynamic scenes, and a fast nonconvex algorithm for the nonconvex sorted 1 regularization is applied to reconstruct frame differences using few numbers of measurements. Then, an edge-detection-based denoising method is employed to reduce the error in the frame difference image. The experimental results show that the proposed algorithm together with the single-pixel imaging system makes compressive video cameras available.
© 2016 SPIE and IS&T
Liangliang Chen, Ming Yan, Chunqi Qian, Ning Xi, Zhanxin Zhou, Yongliang Yang, Bo Song, Lixin Dong, "Nonconvex compressive video sensing," Journal of Electronic Imaging 25(6), 063003 (15 November 2016). https://doi.org/10.1117/1.JEI.25.6.063003


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