通过卡尔曼滤波的速率量化建模改进了速率控制

Din-Yuen Chan, Shou-Jen Lin, Chung-Wei Lin
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引用次数: 0

摘要

本文提出了一个基于自适应速率量化(R-Q)模型的H.263+速率控制框架。由指定的量化参数参数化的特征速率函数可以近似为macroblock (MB)活性的线性函数。在编码过程中,卡尔曼滤波同时对R-Q特征线的斜率进行细化,以跟踪两个连续聚类mb (COBS)之间R-Q关系的变化,并根据最新的细化R-Q模型确定位于同一COBS的mb的量化参数。为了满足实时性的要求,该方案采用了一种快速渐进的MB合并方法来确定COB的范围。在实验中,我们的框架可以获得比TMNB模块更高的客观和感知质量。关键词:H.263+,率量化模型,卡尔曼滤波。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved rate control via rate-quantization modeling with kalman filter
In this paper, we propose a rate control framework for H.263+ using an adaptive rate-quantization (R-Q) model. A characteristic rate function parameterized by a specified quantization parameter can be approximately a linear function of macroblock (MB) activity. During encoding, Kalman filter simultaneously refines the slopes of R-Q characteristic line to trace the change of R-Q relation between two successive clustered MBs (COBS), and the quantization parameters of MBs located in the same COB can be determined based on the latest refined R-Q model. For satisfying real-time demands, the proposed scheme employs a fast method of progressive MB mergence to determine the range of a COB. In the experiments, our framework can obtain higher objective and perceptual qualities over TMNB module. Keyword: H.263+, Rate-Quantization Model, Kalman filter.
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