多媒体传感器网络视频的帧分类联合重构

Frame Classification Based Joint Video Recovery Algorithm for Multimedia Sensor Networks

中文关键词:  多媒体传感器网络  压缩感知  视频重构  帧分类

英文关键词:multimedia sensor networks  compressed sensing  video recovery  frame classification

中文摘要:

      为降低多媒体传感器网络中视频压缩感知的计算复杂度，提出一种基于帧分类的多媒体传感器网络视频联合重构算法。依据视频数据的联合稀疏模型将视频帧分为关键帧和非关键帧。对于压缩感知重构中欠定线性方程组，可利用关键帧和非关键帧之间的相关边信息进行重构初始化，同时运用有界约束二次规划对其进行求解。从仿真结果可知，相对于传统的视频压缩感知算法而言，在保证视频重构质量的前提下，所提方法在重构算法复杂度上不但能有效降低，同时，在视频重构上能提高其实时性。

英文摘要:

      For reducing the computation complexity of compressed sensing (CS) based video recovery algorithm in multimedia sensor networks，a frame classification based joint recovery algorithm is proposed.The frames of network video are classified into two types，which are key frames and non-key frames，and the side information between two types of frames can be used in initialization of recovery.The under-determined linear equations in CS recovery are solved by bound-constrained quadratic programming.Simulation results demonstrate that the proposed algorithm can significantly reduce the complexity while the accuracy of recovery is ensured，thus improve the real-time performance of video recovery in multimedia sensor networks.