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Distortion-rate models for entropy-coded lattice vector quantization

机译:熵编码格向量量化的失真率模型

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The increasing demand for real-time applications requires the use of variable-rate quantizers having good performance in the low bit rate domain. In order to minimize the complexity of quantization, as well as maintaining a reasonably high PSNR ratio, we propose to use an entropy-coded lattice vector quantizer (ECLVQ). These quantizers have proven to outperform the well-known EZW algorithm's performance in terms of rate-distortion tradeoff. We focus our attention on the modeling of the mean squared error (MSE) distortion and the prefix code rate for ECLVQ. First, we generalize the distortion model of Jeong and Gibson (1993) on fixed-rate cubic quantizers to lattices under a high rate assumption. Second, we derive new rate models for ECLVQ, efficient at low bit rates without any high rate assumptions. Simulation results prove the precision of our models.
机译:对实时应用的日益增长的需求要求使用在低比特率域中具有良好性能的可变速率量化器。为了最小化量化的复杂性,并保持合理的高PSNR比,我们建议使用熵编码的点阵矢量量化器(ECLVQ)。这些量化器已经证明在速率失真权衡方面优于著名的EZW算法。我们将注意力集中在ECLVQ的均方误差(MSE)失真和前缀码率的建模上。首先,在高速率假设下,我们将固定速率三次量化器上的Jeong和Gibson(1993)的失真模型推广到晶格。其次,我们导出了ECLVQ的新速率模型,该模型在低比特率下有效,而没有任何高速率假设。仿真结果证明了我们模型的准确性。

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