基于小波多分辨率分析和改进窄带法的C-V水平集图像分割模型  

THE IMPROVED C-V LEVEL SET IMAGE SEGMENTATION MODEL BASED ON WAVELET ANALYSIS AND NARROW BAND

作　　者：付金明[1,2] 羿旭明[2] 

机构地区：[1]华中农业大学理学院,湖北武汉430070 [2]武汉大学数学与统计学院,湖北武汉430072

出　　处：《数学杂志》2016年第4期867-874,共8页Journal of Mathematics

摘　　要：本文研究了基于小波分析改进的C-V模型图像分割问题.利用小波多分辨率分析和改进的窄带水平集方法,获得了比传统C-V模型分割速度更快、准确度更高、算法复杂度更低的分割结果.推广了C-V水平集模型如何快速准确地分割灰度不均匀的图像和窄带水平集法等结果.In this paper,we study the problem of image segmentation of C-V model.By using the wavelet transform and the improved level set and narrow band method,image edge information and the initial segmentation curve are obtained.We get a segmentation result which is faster in segmentation speed,higher in accuracy and lower in algorithm complexity than traditional C-V model.The results of the C-V level set model for the segmentation of gray uneven images and the initialization of the zero level set and the narrow band method are generalized.

关 键 词：图像分割 C-V水平集 小波变换 窄带法 

分 类 号：O29[理学—应用数学]