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Study on distortion-quantization models based on DCT coefficient distribution models

机译:基于DCT系数分布模型的失真量化模型研究

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In H.264/AVC, rate control and mode decision play important roles for efficient video compression. Usually, rate control employs R-D model to select the quantization parameter for precise bit rate control. R-D model which includes rate quantization (R-Q) model and distortion quantization (D-Q) model can be derived from mathematic modeling based on distribution of DCT coefficients. Therefore, the DCT coefficients distribution models are very important for D-Q modeling. Currently, some D-Q models have been proposed based on these three models, such as Laplacian, Cauchy and Generalized Gaussian Distribution (GGD), but there is no systematic and rigorous comparison on their accuracy. In this paper, we will have an analysis on three DCT coefficients distribution models. Also, we will test several existing D-Q models and give fair comparison on these models. This work is meaningful for efficient video coding algorithm optimization in the future.
机译:在H.264 / AVC,速率控制和模式决策中扮演有效的视频压缩的重要角色。 通常,速率控制采用R-D模型来选择用于精确比特率控制的量化参数。 包括速率量化(R-Q)模型和失真量化(D-Q)模型的R-D模型可以从基于DCT系数的分布来源的数学建模。 因此,DCT系数分布模型对于D-Q建模非常重要。 目前,已经基于这三种模型提出了一些D-Q模型,例如拉普拉斯,Cauchy和广义高斯分布(GGD),但没有对其准确性进行系统和严格的比较。 在本文中,我们将对三个DCT系数分布模型进行分析。 此外,我们将测试几种现有的D-Q模型,并在这些模型进行公平比较。 这项工作对于未来有效的视频编码算法优化是有意义的。

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