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基于水平集的新型彩色图像分割算法
引用本文:陈沅涛,徐蔚鸿,吴佳英.基于水平集的新型彩色图像分割算法[J].计算机应用,2012,32(3):749-751.
作者姓名:陈沅涛  徐蔚鸿  吴佳英
作者单位:1.南京理工大学 计算机科学与技术学院,南京 210094; 2.长沙理工大学 计算机与通信工程学院,长沙 410004
基金项目:湖南省教育厅科研基金,湖南省科技计划基金,长沙市科技局基金重点项目
摘    要:由于考虑的泛函变分形式是非凸性质,向量值图像分割模型的计算结果经常会陷入局部最小值。基于活动轮廓的向量值图像的全局图像分割方法,以新型变分形式将向量值图像分割和图像去噪融入具有全局极小能力泛函框架中。新模型具有容易构造和较少计算量的特点,对比经典的水平集方法,可以避免繁琐的距离重复化水平集过程。通过对人工图像和真实图像进行分析,验证新方法具有更好的图像分割效果。

关 键 词:活动轮廓    局部极小值    全局极小值    向量值图像    图像分割
收稿时间:2011-08-18
修稿时间:2011-12-08

New colorful images segmentation algorithm based on level set
CHEN Yuan-tao , XU Wei-hong , WU Jia-ying.New colorful images segmentation algorithm based on level set[J].journal of Computer Applications,2012,32(3):749-751.
Authors:CHEN Yuan-tao  XU Wei-hong  WU Jia-ying
Affiliation:1.School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing Jiangsu 210094, China;
2.School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha Hunan 410004, China
Abstract:Since the functional form in consideration is of non-convex variational nature,the calculation results of the image segmentation model often fall into local minimum.Based on the global vector-valued image segmentation of active contour,the global vector-valued image segmentation and image denoising were integrated in a new variational form within the framework of global minimum.The new model was easy to construct and of less computation.Compared to the classical level set method,tedious repetition of the level set could be avoided.With the analyses on artificial images and real images,the new method is verified to have better segmentation results.
Keywords:active contour  local minimum  global minimum  vector-valued image  image segmentation
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