红外技术2016，Vol.38Issue(9)：774-778,5.
一种基于改进 Chan-Vese 模型的红外图像分割方法
A Kind of Infrared Image Segment Method Using Improved Chan-Vese Model
摘要
Abstract
To solve the problem that the traditional Chan-Vese(CV) model-based level set method was difficult to segment infrared images with inhomogeneous intensity, a kind of level set method based on improved CV model was proposed in this paper. By adding the local term which can deal with the local area information, the improved CV model can effectively avoid the interference of the inhomogeneous background to the level set evolution process. In addition, by adding the signed distance penalizing energy term, this model does not need to re-initialize the process, thus improving the evolution efficiency of the level set function. Experimental results show that this method has high precision for infrared image segmentation.关键词
红外图像分割/水平集/CV模型/LCV模型Key words
infrared image segmentation/level set/CV model/LCV model分类
信息技术与安全科学引用本文复制引用
赵晓理,周浦城,薛模根..一种基于改进 Chan-Vese 模型的红外图像分割方法[J].红外技术,2016,38(9):774-778,5.基金项目
国家自然科学基金资助项目（61379105，41606109）；中国博士后基金资助项目（2013M532208）。 （）
