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Optimum Quantization of Flattened MDCT Coefficients*

机译:扁平MDCT系数的最佳量化*

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The performance of perceptual audio coders depends on the efficiency of the quantization operation in masking the quantization noise under the audio signal. This objective is better addressed by coding separately different signal components such as sinusoids, transients and stationary noise. In this paper we use an audio coder that normalizes the MDCT spectrum by a smooth spectral envelope and by periodicities due to sinusoids. The resulting flattened MDCT coefficients are shown to exhibit a probability density function with small uncertainty allowing the design of an optimum non-uniform scalar quantizer. Its distortion-rate function is derived, is compared to that of known quantizers, and is compared to that obtained under real audio coding conditions.
机译:感知音频编码器的性能取决于掩盖音频信号下的量化噪声的量化操作的效率。通过分别编码不同的信号分量(例如正弦波,瞬变和平稳噪声),可以更好地解决此目标。在本文中,我们使用一个音频编码器,该编码器通过平滑的频谱包络和正弦波引起的周期对MDCT频谱进行归一化。所显示的平坦的MDCT系数显示出具有小的不确定性的概率密度函数,从而允许设计最佳的非均匀标量量化器。推导其失真率函数,将其与已知量化器的失真率函数进行比较,并与在真实音频编码条件下获得的失真率函数进行比较。

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