节点文献
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
【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.
【Abstract】 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;
【Key words】 image segmentation; C-V level set; wavelet transform; narrow band method;
【Key words】 image segmentation; C-V level set; wavelet transform; narrow band method;
- 【文献出处】 数学杂志 ,Journal of Mathematics , 编辑部邮箱 ,2016年04期
- 【分类号】TP391.41
- 【被引频次】3
- 【下载频次】102