ZHOU Jian,LIU Hao.Video compressive sensing reconstruction via long- short-term double-pattern prediction[J].Optoelectronics Letters,2020,16(3):230-236 Video compressive sensing reconstruction via long- short-term double-pattern prediction Author Name Affiliation ZHOU Jian  College of Information Science and Technology, Donghua University, Shanghai 201620, China  LIU Hao  College of Information Science and Technology, Donghua University, Shanghai 201620, China  Abstract:       The compressive sensing technology has a great potential in high-dimensional vision processing. The existing video reconstruction methods utilize the multihypothesis prediction to derive the residual sparse model from key frames. However, these methods cannot fully utilize the temporal correlation among multiple frames. Therefore, this paper proposes the video compressive sensing reconstruction via long-short-term double-pattern prediction, which consists of four main phases:the first phase reconstructs each frame independently; the second phase adaptively updates multiple reference frames; the third phase selects the hypothesis matching patches from current reference frames; the fourth phase obtains the reconstruction results by using the patches to build the residual sparse model. The experimental results demonstrate that as compared with the state-of-the-art methods, the proposed methods can obtain better prediction accuracy and reconstruction quality for video compressive sensing. Hits: 960 Download times: 0 View Full Text    Download reader