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Gaussian DCT Coefficient Models

机译:高斯DCT系数模型

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摘要

It has been known that the distribution of the discrete cosine transform (DCT) coefficients of most natural images follow a Laplace distribution. However, recent work has shown that the Laplace distribution may not be a good fit for certain type of images and that the Gaussian distribution will be a realistic model in such cases. Assuming this alternative model, we derive a comprehensive collection of formulas for the distribution of the actual DCT coefficient. The corresponding estimation procedures are derived by the method of moments and the method of maximum likelihood. Finally, the superior performance of the derived distributions over the Gaussian model is illustrated. It is expected that this work could serve as a useful reference and lead to improved modeling with respect to image analysis and image coding.
机译:已知大多数自然图像的离散余弦变换(DCT)系数的分布遵循拉普拉斯分布。但是,最近的工作表明,拉普拉斯分布可能不适用于某些类型的图像,并且在这种情况下,高斯分布将是一个现实的模型。假设使用此替代模型,我们将得出一系列实际DCT系数分布的公式。相应的估计程序通过矩量法和最大似然法导出。最后,说明了派生分布在高斯模型上的优越性能。期望这项工作可以作为有用的参考,并导致在图像分析和图像编码方面改进建模。

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