最大熵和最小交叉熵综合的交互式图像分割

Interactive image segmentation based on combining maximum entropy and minimum cross entropy

在图像分割中,使用某一种分割方法并不是总有效。最大熵和最小交叉熵阈值化方法是目前常用的两种图像分割方法,但在某些分割应用场合失效。针对此问题,提出基于最大熵和最小交叉熵综合的交互式图像分割方法。首先,利用一种简单的算法将前两种方法有机结合产生一种既满足最大熵原则,又满足最小交叉熵原则的新分割方法,然后通过人机交互,在这三种阈值方法中选择最好的图像分割。仿真实验结果表明,提出的方法不仅分割效果好,算法的普适性增强,而且更实用。

The segmentation approach on one criterion only does not work well for a lot of images.The thresholding methods based on maximum entropy and minimum cross entropy are used widely today in image segmentation,but they often fail to segment some images,so an interactive image segmentation method based on combining maximum entropy and minimum cross entropy is presented in this paper.Firstly it gets the third thresholding method by combining maximum entropy and minimum cross entropy using a simple algorithm so that the optimal threshold value can not only satisfy the former but also meet the latter,then the optimal segmentation is chosen by users in the three methods.Experimental results show that the proposed method can not only get better segmentation performance and better generalization,but is also more practical.