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Research And Application Of Distributed Compressive Video Sensing Technology

Posted on:2019-12-06Degree:MasterType:Thesis
Country:ChinaCandidate:L XieFull Text:PDF
GTID:2428330566499279Subject:Electronic and communication engineering
Abstract/Summary:PDF Full Text Request
With the rapid development of information technology,varieties of video technologies are widely used in the Internet and wireless sensor networks.In order to solve the problems of traditional video coding,such as high computational complexity and poor error resilience capability,distributed compressive video sensing has become a hot research topic both at home and abroad in recent years and is the most competitive video application solution.The technical problems to be solved urgently are that the existing video coding and reconstruction methods still need to be further optimized,the reconstruction rate is increased,and the complexity of the algorithm is reduced.Firstly,when the video frame is reconstructed,a multi-hypothesis bidirectional best match strategy is proposed.The idea of motion alignment estimation is introduced,and the best matching block is selected from the reference frame by using the block structural similarity of the measured domain.The optimal video generation matrix is extracted pixel by pixel in the search window centered on the best matching block,and the residual compensation is applied to reconstruct the nonkey frame.Simulation results show that at the same sampling rate,the proposed algorithm can improve the quality of reconstructed video frames,and the reconstruction time does not increase significantly,and the subjective visual effect is better.Secondly,in order to solve the problem that the existing prediction reconstruction algorithm is not clear enough to reconstruct the video in the vigorous scene of the sport,the best matching interpolation reconstruction method in distributed compressive video sensing is proposed.The best matching interpolation dictionary is formed by the interpolation method in the searching window centered on the best matching block,and the interpolation method make the residual signal more sparse.Simulation results show that this method can obtain higher reconstruction quality.Finally,both bidirectional best matching strategy and the best matching interpolation method are applied in the distributed compressive video sensing.The key frame is reconstructed by the best matching interpolation method,and the nonkey frame is reconstructed by the bidirectional best matching method.Simulation results show that the proposed algorithm significantly improves the quality of reconstruction,and the reconstruction time does not increase significantly.
Keywords/Search Tags:Distributed Compressive Video Sensing, Multi-hypothesis Predictions, Best Matching, Interpolation Dictionary, Residual Compensation, Signal Recovery
PDF Full Text Request
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