低采样率下压缩视频感知编解码研究-通信与信息系统专业论文.docxVIP

万方数据 万方数据 摘 要 压缩感知采样突破了奈奎斯特采样速率的限制，实现了对于信息的直接采样。 压缩视频感知将压缩感知引入到视频编解码中，实现了一种低复杂度编码方式。 现有压缩视频感知编码方案大都在高采样率条件下性能优异，然而在底层节 点能量有限的无线网络中，提高采样率会增加编码端能耗，缩短网络生命周期。 本文结合压缩感知技术与分布式视频编解码技术，提出了一种适用于无线多媒体 传感器网络的压缩视频感知编解码系统，该系统通过同时提高关键帧和非关键帧 的解码质量，有效的改善了低采样率下系统的整体性能。在解码端，利用重采样 处理增加了非关键帧的测量值数目，从而提高了非关键帧的解码质量；借鉴非关 键帧解码时利用边信息进行辅助解码来提高解码质量的思想，系统对于关键帧进 行二次重构，提高了关键帧的解码质量。仿真结果表明，系统具有高质量的解码 性能，尤其是在低采样率的情况下，且无论是关键帧还是非关键帧的解码质量均 得到了有效改善。 关键字：压缩感知 压缩视频感知 低采样率 重采样 二次重构 万方数据 万方数据 Abstract Compressed sensing (CS) breaks the limits of Nyquist sampling rate and achieves a direct sampling for information. Compressed video sensing (CVS) introduces CS into video encoding and thus realizes a low-complexity method of encoding. The existed compressed video sensing schemes are mostly of great decoding quality at high sampling rate. However, in wireless networks whose bottom node with limited energy, enhancing sampling rate can increase the consumption of energy, leading to reducing the lifetime of the network. In this paper, a novel compressed video sensing system which is exactly suitable for wireless multimedia sensor networks is proposed by combining compressed sensing and distributed video coding. This system improves the performance at low sampling rate by enhancing the decoding quality of both Key and non-key frames. At the decoder, the amount of measurement is increased by resampling and thus improving the reconstruction quality of non-key frames. By the thought of using side information for assisted decoding to enhance the decoding performance of non-key frames, the quality of Key frames is enhanced by re-reconstruction. Simulation results show that the system has a high-quality decoding performance, especially in the case of low sampling rate. Both the quality of key frames and that of non-key frames can be effectively improved. Keywords： compressed sensing compressed video sensing low sampling rate resampling re-reconstruction 万方数据 万方数据 万方数据 万方数据 目录 HYPERLINK \l _bookmark0 第一章 绪论 1 HYPERLINK