A High-Efficiency Compressed Sensing-Based Terminal-to-Cloud Video Transmission System

With the rapid popularization of mobile intelligent terminals, mobile video and cloud services applications are widely used in people's lives. However, the resource-constrained characteristic of the terminals and the enormous amount of video information make the efficient terminal-to-cloud data upload a challenge. To solve the problem, this paper proposes an efficient compressed sensing-based high-efficiency video upload system for the terminal-to-cloud upload network. The system contains two main new components. First, to effectively remove the inter-frame redundant information, an encoder sampling scheme with high efficiency is developed by applying the skip block-based residual compressed sensing sampling technology. For the time-varying channel state, the encoder can adaptively allocate the sampling rate for different video frames by the proposed adaptive sampling scheme. Second, a local secondary reconstruction-based multi-reference frames cross-recovery algorithm is developed at the decoder. It further improves the reconstruction quality and reduces the quality fluctuation of the recovered video frames to improve the user experience. Compared with the state-of-the-art reference systems reported in the literature, the proposed system achieves the high-efficiency and high-quality terminal-to-cloud transmission.