Residual Distributed Compressive Video Sensing Based on Double Side Information

Q2 Computer Science

自动化学报 Pub Date : 2014-10-01 DOI:10.1016/S1874-1029(14)60363-3

Jian CHEN , Kai-Xiong SU , Wei-Xing WANG , Cheng-Dong LAN

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引用次数: 6

Abstract

Compressed sensing (CS) is a novel technology to acquire and reconstruct sparse signals below the Nyquist rate. It has great potential in image and video acquisition and processing. To effectively improve the sparsity of signal being measured and reconstructing efficiency, an encoding and decoding model of residual distributed compressive video sensing based on double side information (RDCVS-DSI) is proposed in this paper. Exploiting the characteristics of image itself in the frequency domain and the correlation between successive frames, the model regards the video frame in low quality as the first side information in the process of coding, and generates the second side information for the non-key frames using motion estimation and compensation technology at its decoding end. Performance analysis and simulation experiments show that the RDCVS-DSI model can rebuild the video sequence with high fidelity in the consumption of quite low complexity. About 1 ~ 5 dB gain in the average peak signal-to-noise ratio of the reconstructed frames is observed, and the speed is close to the least complex DCVS, when compared with prior works on compressive video sensing.

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基于双面信息的残差分布式压缩视频感知

压缩感知(CS)是一种获取和重构低于奈奎斯特速率的稀疏信号的新技术。它在图像和视频的采集和处理方面具有很大的潜力。为了有效提高被测信号的稀疏度和重构效率，本文提出了一种基于双面信息的残差分布式压缩视频感知编解码模型(RDCVS-DSI)。该模型利用图像本身的频域特性和连续帧之间的相关性，在编码过程中将低质量的视频帧作为第一边信息，在解码端利用运动估计和补偿技术生成非关键帧的第二边信息。性能分析和仿真实验表明，RDCVS-DSI模型能够以较低的复杂度重构出高保真度的视频序列。重构帧的平均峰值信噪比增益约为1 ~ 5db，速度接近于最不复杂的DCVS，与之前的压缩视频感知工作相比。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

自动化学报 Computer Science-Computer Graphics and Computer-Aided Design

CiteScore

4.80

自引率

0.00%

发文量

6655

期刊介绍： ACTA AUTOMATICA SINICA is a joint publication of Chinese Association of Automation and the Institute of Automation, the Chinese Academy of Sciences. The objective is the high quality and rapid publication of the articles, with a strong focus on new trends, original theoretical and experimental research and developments, emerging technology, and industrial standards in automation.