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渐近闭环方法在预测矢量量化器设计中的应用及其在视频编码中的应用。

The asymptotic closed-loop approach to predictive vector quantizer design with application in video coding.

机构信息

Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA 93106, USA.

出版信息

IEEE Trans Image Process. 2001;10(1):15-23. doi: 10.1109/83.892439.

Abstract

The basic vector quantization (VQ) technique employed in video coding belongs to the category of predictive vector quantization (PVQ), as it involves quantization of the (motion compensated) frame prediction error. It is well known that the design of PVQ suffers from fundamental difficulties, due to the prediction loop, which have an impact on the convergence and the stability of the design procedure. We propose an approach to PVQ design that enjoys the stability of open-loop design while it ensures ultimate optimization of the closed-loop system. The method is derived for general predictive quantization, and we demonstrate it on video compression at low bit rates, where it provides substantial improvement over standard open and closed loop design techniques. Further, the approach outperforms standard DCT-based video coding.

摘要

视频编码中使用的基本矢量量化 (VQ) 技术属于预测矢量量化 (PVQ) 类别,因为它涉及到(运动补偿)帧预测误差的量化。众所周知,由于预测环路的存在,PVQ 的设计存在根本性的困难,这会影响设计过程的收敛性和稳定性。我们提出了一种 PVQ 设计方法,该方法在具有开环设计的稳定性的同时,确保了闭环系统的最终优化。该方法适用于一般预测量化,并在低比特率的视频压缩中进行了演示,与标准的开环和闭环设计技术相比,它提供了实质性的改进。此外,该方法优于基于标准 DCT 的视频编码。

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