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 ℓ1 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.

中文翻译：

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非凸压缩视频传感

摘要。高速摄像机在时间序列上比普通摄像机探索更多的细节，而传统的视频采样由于传感器的物理限制而在时间和空间分辨率之间进行权衡。压缩感知通过将采样和压缩过程结合在一起克服了这一障碍。提出了一种基于单像素的实时视频采集来记录动态场景，并应用了一种用于非凸排序 ℓ1 正则化的快速非凸算法来使用少量测量值重建帧差异。然后，采用基于边缘检测的去噪方法来减少帧差异图像中的误差。实验结果表明，所提出的算法与单像素成像系统一起使压缩摄像机可用。