15 November 2016 Nonconvex compressive video sensing
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Abstract
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, Liangliang Chen, Ming Yan, Ming Yan, Chunqi Qian, Chunqi Qian, Ning Xi, Ning Xi, Zhanxin Zhou, Zhanxin Zhou, Yongliang Yang, Yongliang Yang, Bo Song, Bo Song, Lixin Dong, 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 . Submission:
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