核空间散度阈值法

提出了一种核空间散度阈值分割方法。首先定义了一种参数型Bregman散度;其次提出了参数型Bregman散度阈值法,并将现有交叉熵阈值法和Otsu阈值法统一起来;再次基于参数型Bregman散度构造了核空间中一种新的不对称核函数,将图像灰度级从欧氏空间变换到再生核空间,获得了一种核空间的散度阈值分割法;最后研究了该分割法中核函数参数选取方法。实验结果表明,基于核空间的散度分割法具有一定的普适性,并能改善现有交叉熵阈值法和Otsu阈值法的分割性能,同时也可将这两种经典阈值分割法看做核空间散度阈值法的特殊情形。

Divergence thresholding method in kernel space

A divergence thresholding method in kernel space is proposed.First,a new kind of Bregman divergence in parametric form is defined.Second,the new thresholding method based on Bregman divergence is presented.The new methed can unify cross entropy and Otsu’s thresholding method.Third,a new asymmetric kernel function in reproduced Hilbert space is constructed by means of Bregman divergence in parametric form.Image gray levels in Euclid space are transformed into the reproduced kernel space,and a divergence thresholding method in kernel space is obtained.Finally,the method for choosing parameters for the kernel function in the new thresholding method is analyzed.Experimental results show that the proposed divergence thresholding method in kernel space has a certain widespread adaptability.It can improve the segmentation performance of cross entropy and Otsu’s thresholding methods,and two kinds of classical thresholding methods based on cross entropy and Otsu are also regarded as the special cases of the kernel space divergence thresholding method proposed in this paper.