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首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >Fast Mode Decision for HD Scalable Video Coding via Statistical Content Analysis
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Fast Mode Decision for HD Scalable Video Coding via Statistical Content Analysis

机译:通过统计内容分析实现高清可扩展视频编码的快速模式决策

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摘要

Scalable video coding (SVC) can provide different bitrate, resolution, or quality formats of the same video through the one-time encoding process. However, SVC also increases encoding complexity significantly, making real-time implementations difficult especially when applied to high definition videos. In this work, we proposed to utilize a fast mode decision algorithm to speed up the SVC encoder. A simple model of the relationship of the video complexity is proposed, the rate-distortion (RD) cost and the statistical mode distribution of the enhancement layer (EL). The proposed mode decision algorithm evaluates the complexity of the video content, then sets the rate distortion RD cost thresholds for inter coding modes. The method also optimizes the process INTRA_BL for I slices. We demonstrate the method using four different resolutions (1080p, 720p, VGA and QVGA), four temporal layers, and two quality layers. We find that the proposed algorithm can reduce the computational complexity significantly while maintaining or even improving encoder efficiency.
机译:可伸缩视频编码(SVC)可通过一次性编码过程为同一视频提供不同的比特率,分辨率或质量格式。但是,SVC还极大地增加了编码复杂性,尤其是在应用于高清视频时,使实时实现变得困难。在这项工作中,我们建议利用快速模式决策算法来加快SVC编码器的速度。提出了视频复杂度,速率失真(RD)成本和增强层(EL)的统计模式分布之间关系的简单模型。提出的模式决策算法评估视频内容的复杂度,然后为帧间编码模式设置速率失真RD成本阈值。该方法还为I切片优化了过程INTRA_BL。我们演示了使用四个不同分辨率(1080p,720p,VGA和QVGA),四个时间层和两个质量层的方法。我们发现,所提出的算法可以在保持甚至提高编码器效率的同时显着降低计算复杂度。

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