2种非对称广义高斯分布模型的构造

Construction of Two Asymmetric Generalized Gaussian Distribution Models

广义高斯分布常被用于图像处理及视频信号的统计分析之中,非对称广义高斯分布突破了对称性的束缚,用于数据处理建模更为适宜.从高斯分布入手,分别对左右两侧的不同方差和不同概率密度的广义高斯分布进行了改进,从而构造出了2种非对称的广义高斯模型,且通过模拟实验实现了构造模型的效果.

The generalized Gaussian distribution is often used in image processing and video signal statistical analysis, while the asymmetric generalized Gaussian distribution breaks through the constraint of symmetry, so it is more suitable for data processing modeling. In this paper, starting with the Gaussian distribution, the generalized Gaussian distribution with different variance and different probability density on the left and right sides is improved respectively, so as to construct the asymmetric generalized Gaussian density models, and the model effect is achieved through simulation experiments.