基于直方图重构的极大交叉熵图像分割方法  

Image segmentation of maximum cross entropy based on histogram reconstruction

作　　者：曹建农[1] 

机构地区：[1]长安大学地球科学与国土资源学院,西安710054

出　　处：《计算机应用》2011年第12期3373-3377,共5页journal of Computer Applications

基　　金：国家自然科学基金资助项目(40971217);地理空间信息工程国家测绘局重点实验室开发基金资助项目(200915)

摘　　要：针对图像分割阈值选择问题,提出用动态参数将原始图像直方图分成两部分,构造两个新的相关直方图,分别对应于同原始图像等尺寸的虚拟图像,其中等概率像素是原始图像的相似像素。聚集计算两个构造直方图概率分布的交叉熵,分析其函数曲线极大值的峰谷关系,实现图像最佳多阈值分割。实验结果表明该方法的有效性。Concerning the thresholds selection in image segmentation,this paper proposed a method that used dynamic threshold to divide the histogram of original image into two new independent histograms.The two new histograms correspond to two fictitious images whose sizes are the same to original one,and pixels of the same probability are similar pixels of original image.The cross entropy can be assembled and calculated between probability distribution of the two new histograms.By analyzing the relationship between peak and valley of the maximum of entropy functional curve,the best multi-thresholds for segmentation image can be achieved.This method is simple and clear,and the experiment shows this method is effective.

关 键 词：图像分割 交叉熵 直方图重构 虚拟图像 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]