量化阶梯函数的建模

S. Aslam, A. Bobick, C. Barnes
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引用次数: 0

摘要

量化在数据压缩中起着核心作用。在语音系统中,矢量量化器用于压缩语音参数。在视频系统中,标量量化器用于减少变换系数的可变性。更一般地说,量化器被用来压缩所有形式的数据。在大多数情况下,量化器是基于某种形式的阶梯函数。推导出均匀中量子器的解析表达式是众所周知的,也是直截了当的。在本文中,我们创建了一种推导这种解析表达式的替代方法,希望所涉及的步骤将有助于理解量化及其各种应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling the Quantization Staircase Function
Quantization plays a central role in data compression. In speech systems, vector quantizers are used to compress speech parameters. In video systems, scalar quantizers are used to reduce variability in transform coefficients. More generally, quantizers are used to compress all forms of data. In most cases, the quantizers are based on some form of staircase function. Deriving an analytical expression for a uniform midrise quantizer is well known and straightforward. In this paper, we create an alternate method of deriving such an analytical expression with the hope that the steps involved will be useful in understanding quantization and its various applications.
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