多媒体和科学图像的小波域PDF模型

J. Švihlík, P. Páta
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引用次数: 0

摘要

本文研究了小波域数字图像边缘概率密度函数(PDF)的统计模型。本文还介绍了用最小二乘法估计模型参数的方法。并矢分解是离散小波变换的一种特殊形式。给出了基于广义拉普拉斯算子的小波系数统计模型。PDF在小波域的建模是一种很好的方法,可用于多媒体数据的重构。多媒体数据以其图像内容为特征。机器人天文系统,即BOOTES(突发观测者光学瞬态探测系统)提供大量具有特定属性的数据(即比特深度,噪声,物体)。这些数据是非常特殊的,有必要在小波域分析它们的PDF,以便对它们进行其他处理。对科学数据和多媒体数据统计模型的参数进行了估计和比较。这对于正确设置重建算法具有重要意义
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PDF Model of Multimedia and Scientific Images in the Wavelet Domain
This work deals with a statistical model of the marginal probability density function (PDF) of digital images in the wavelet domain. Estimation of parameters of the model using least square method is also included. A dyadic decomposition as a special form of the discrete wavelet transform is used in this paper. There is described the statistical model of wavelet coefficients based on the generalized Laplacian. The modeling of PDF in the wavelet domain is well blown procedure, which is used for reconstruction of multimedia data. The multimedia data are characterized by their image content. The robotic astronomical systems, i.e. BOOTES (burst observer optical transient exploring system) provide a huge amount of a data with specific properties (i.e. bit depth, noise, objects). These data are very specific and it is necessary to analyze their PDF in the wavelet domain for their other processing. The parameters of the statistical model of scientific and multimedia data have been estimated and compared. It is very significant for proper setup of the reconstruction algorithms
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