监控视频宏块级选择性背景差分编码

Xianguo Zhang, Yonghong Tian, Luhong Liang, Tiejun Huang, Wen Gao
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引用次数: 12

摘要

尽管目前有三种典型的方法:面向对象方法、基于背景预测方法和基于背景差异方法,但利用监控视频的特殊属性来提高编码效率仍有很大的发展空间。但是,由于前景分割不准确,背景帧质量低或不清晰,以及潜在的“前景污染”现象,仍有很大的改进空间。为了解决这一问题,本文提出了一种宏块级选择性背景差编码方法(MSBDC)。MSBDC对每个宏块(MB)选择以下两种编码方式:对原始MB进行编码,以及直接对MB与相应背景的差异数据进行编码。MSBDC的另一个特点是采用了mb的分类,便于选择,从而使前景和背景的预测和运动补偿变得更加准确。结果表明,与几种最先进的方法相比,MSBDC显著降低了总比特率,并在前景上获得了显著的性能增益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Macro-Block-Level Selective Background Difference Coding for Surveillance Video
Utilizing the special properties to improve the surveillance video coding efficiency still has much room, although there have been three typical paradigms of methods: object-oriented, background-prediction-based and background-difference-based methods. However, due to the inaccurate foreground segmentation, the low-quality or unclear background frame, and the potential "foreground pollution" phenomenon, there is still much room for improvement. To address this problem, this paper proposes a macro-block-level selective background difference coding method (MSBDC). MSBDC selects the following two ways to encode each macro-block (MB): coding the original MB, and directly coding the difference data between the MB and its corresponding background. MSBDC also features at employs the classification of MBs to facilitate the selection, through which, prediction and motion compensation turns more accurate, both on foreground and background. Results show that, MSBDC significantly decreases the total bitrate and obtains a remarkable performance gain on foreground compared with several state-of-the-art methods.
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