NMF (non-negative matrix factorization) video compression technology

一种nmf视频压缩技术

Abstract

The invention discloses an NMF (non-negative matrix factorization) video compression technology which includes the steps of firstly, burning an embedded video compression with algorithm of recognition and separation technology, and loading the video compression into a chip; secondly, pretreating collected data by connecting the chip with equipment; thirdly, finding significant nodes through an NMF method in mode recognition; fourthly, realizing node saving and time domain cutting of real-time video streams through the significant nodes; and fifthly, separating background and foreground through similarity comparison, saving the background as a static image, and saving the foreground as sparse matrix data. By MATLAB (matrix laboratory) programming, the NMF theory and software-hardware combination, compression of time domain and space domain redundant information is achieved, algorithm is optimized, data storage is compressed greatly, and data processing speed is improved.
本发明公开了一种NMF视频压缩技术,包括以下步骤:步骤1)识别与分离技术的算法烧制嵌入视频压缩片,将所述视频压缩片装入芯片;步骤2)所述芯片与设备连接,对收集到的数据进行预处理;步骤3)通过模式识别中的NMF方法找出显著性节点;步骤4)通过显著性节点实现实时视频流的节点保存和时域分割;步骤5)通过相似性比较,分离出背景和前景,所述背景作为静止画面保存,所述前景作为稀疏矩阵数据保存。本发明通过MATLAB编程以及非负矩阵分解理论,通过软硬件结合,实现时域和空域冗余信息压缩,优化算法,极大地压缩了数据的存贮量和数据处理速度。

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    CN-103873879-AJune 18, 2014中山大学深圳研究院一种基于双重奇异值分解的视频图像压缩方法