A Novel Framework for Multi-objective Optimization of Video CODECs

Fatima Al-Abri, Xiongwen Li, E. Edirisinghe, C. Grecos
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引用次数: 3

Abstract

In this paper we propose a novel framework for the multi-objective optimization of a video CODEC based on genetic algorithms. The proposed framework is designed to jointly minimize the complexity, memory usage (both at the encoder and decoder), bit rate and to maximize the quality of the compressed video stream. In particular, in our present attempt the optimization strategy is designed to determine the optimum coding parameters for a H.264 AVC video codec in a memory and bandwidth constrained environment. This is demonstrated through extensive experiments and mathematical formulation that results in the optimum solution/s to the multi-objective optimisation problem being found. We show that such an approach is highly desirable in obtaining optimum coding parameters for video delivery over the internet, where a feedback channel from the decoder to the encoder is practical.
一种新的视频编解码器多目标优化框架
本文提出了一种基于遗传算法的视频编解码器多目标优化框架。所提出的框架旨在共同减少复杂性,内存使用(在编码器和解码器),比特率和最大限度地提高压缩视频流的质量。特别是,在我们目前的尝试中,优化策略被设计为在内存和带宽受限的环境中确定H.264 AVC视频编解码器的最佳编码参数。通过大量的实验和数学公式证明了这一点,从而找到了多目标优化问题的最佳解决方案。我们表明,这种方法在通过互联网获得视频传输的最佳编码参数方面是非常理想的,其中从解码器到编码器的反馈通道是实用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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