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1、AbstractThis work aims to based on compressed sensing theory analysis, implementation of distributed video coding. According to the requirements of distributed coding complexity, combined with compressed sensing theory and the traditional video coding and decoding technology, is put forward based on
2、 compressed sensing of distributed video coding: Encoding process that high dimensional signal be projected to a lower dimensional space; decoding project is no longer under the traditional manner of coding inverse process, but through the establishment of joint sparse model, solving the underdeterm
3、ined equations. The codec is relatively simple structure, not only the desired image fewer samples, the number of samples may be different according to the coding mode is selected, and can obtain higher compression ratio and better the quality of the reconstructed image. The experiment result shows
4、that, by introducing adaptive coding mechanism, not only can optimize the performance of RD, and without feedback channel is achieved close to the traditional inter-frame coding properties of reconstruction.Keywords: CS; Distributed decoding algorithm; Encoder; Decoder目录目录1.绪论 .6 1.1引言 .6 1.2研究背景及发展
5、现状 .7 1.2.1压缩感知 .7 1.2.2压缩感知技术在分布式编解码内.7 1.2.3分布式视频编解码 .8 1.3论文的主要内容和组织结构 .9 2压缩感知理论极其研究进展 .9 2.1奈奎斯特（ Nyquist）采样定理 .9 2.2压缩感知理论框架及其主要进展.10 2.2.1问题描述 .10 2.2.2信号的稀疏表示 .12 2.2.3观察矩阵的设计 .14 2.2.4信号重构 .16 2.3压缩感知理论的推广及应用 .22 2.3.1信号在冗余字典上的压缩感知理论.22 2.3.2压缩感知理论初步应用 .22 3基于压缩感知的分布式视频编解码.24 3.1基于压缩感知的视频编解码研究.24 3.1.1传统的视频编解码核心技术 .24 3.1.2基于压缩感知理论的编解码器 .25 3.2帧内与帧间采样率 .27 3.3分布式压缩感知研究 .27 3.4分布式视频编码 (DVC).28 3.5分布式压缩感知编解码 .29 3.6梯度投影稀疏重建 (GPSR).30 3.7结构化相似度 (SSIM).30 4实验介绍 .32 4.1系统模型 .32 4.1.1压缩感知初步算法 .32 4.1.2视频模型 .32 4.2内部视频编码帧的传输 .33 5实验仿真数据 .37 5.1视频解码实验 .37 5.2无线视频传输实验 .37 5.3实验结果数据 .
