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基于双向预测的变采样率分块压缩视频感知 被引量:3

Block compressive video sensing based on bidirectional prediction and variable sampling rates
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摘要 目前现有的变采样率分块压缩视频感知方案仅使用了视频帧的前向预测,即先对参考帧进行测量,然后根据当前帧与参考帧各块之间相关性的大小自适应地分配采样率.这种方式只利用了当前帧与参考帧的帧间相关性,而忽视了自身与后面帧的相关性特点.针对这个问题,提出了一种基于双向预测的变采样率分块压缩视频感知方案,利用双向预测和双向运动估计为当前帧分配合理的采样率并重构视频图像.实验结果表明:相比较现有的变采样率方案,此方案可以适当降低帧的采样率并且提高视频的重构质量,获得1~3dB的峰值信噪比增益和0.02~0.06的结构相似性增益. At present,the existing block compression video sensing(CVS)scheme based on variable sampling rate only uses the forward prediction of video frames.In this way,firstly,the reference frame is measured,and then the sampling rate is adaptively allocated according to the correlation of blocks between the current frame and the reference frame.This method only uses the correlation between the current frame and the previous frame,but ignores the relevance between the current frame and the next frame.In order to solve this problem,a novel adaptive rate block compressive video sensing scheme with bidirectional prediction is proposed.In this scheme,reasonable sampling rate is allocated to the current frame and the video images are reconstructed by using bidirectional prediction and bidirectional motion estimation. The experimental results show that the proposed scheme can reduce the sampling rate properly and improve the quality of video reconstruction compared with the existing variable sampling rate scheme.It can obtain a peak signal-to-noise ratio gain of 1-3 dB and a structural similarity gain of0.02-0.06.
作者 孟利民 曹瑶爽 MENG Limin,CAO Yaoshuang(College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,china)
出处 《浙江工业大学学报》 CAS 北大核心 2018年第4期387-391,共5页 Journal of Zhejiang University of Technology
基金 国家自然科学基金资助项目(61372087) 浙江省科技厅公益项目(2016C33166)
关键词 视频图像处理 自适应采样 双向预测 压缩感知 video image processing adaptive sampling bidirectional prediction compression sensing(CS)
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  • 1张春梅,尹忠科,肖明霞.基于冗余字典的信号超完备表示与稀疏分解[J].科学通报,2006,51(6):628-633. 被引量:71
  • 2R Baraniuk.A lecture on compressive sensing[J].IEEE Signal Processing Magazine,2007,24(4):118-121. 被引量:1
  • 3Guangming Shi,Jie Lin,Xuyang Chen,Fei Qi,Danhua Liu and Li Zhang.UWB echo signal detection with ultra low rate sampling based on compressed sensing[J].IEEE Trans.On Circuits and Systems-Ⅱ:Express Briefs,2008,55(4):379-383. 被引量:1
  • 4Cand,S E J.Ridgelets:theory and applications[I)].Stanford.Stanford University.1998. 被引量:1
  • 5E Candès,D L Donoho.Curvelets[R].USA:Department of Statistics,Stanford University.1999. 被引量:1
  • 6E L Pennec,S Mallat.Image compression with geometrical wavelets[A].Proc.of IEEE International Conference on Image Processing,ICIP'2000[C].Vancouver,BC:IEEE Computer Society,2000.1:661-664. 被引量:1
  • 7Do,Minh N,Vetterli,Martin.Contourlets:A new directional multiresolution image representation[A].Conference Record of the Asilomar Conference on Signals,Systems and Computers[C].Pacific Groove,CA,United States:IEEE Computer Society.2002.1:497-501. 被引量:1
  • 8G Peyré.Best Basis compressed sensing[J].Lecture Notes in Ccmputer Science,2007,4485:80-91. 被引量:1
  • 9V Temlyakov.Nonlinear Methods of Approximation[R].IMI Research Reports,Dept of Mathematics,University of South Carolina.2001.01-09. 被引量:1
  • 10S Mallat,Z Zhang.Matching pursuits with time-frequency dictionaries[J].IEEE Trans Signal Process,1993,41(12):3397-3415. 被引量:1

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