计算机应用研究2017，Vol.34Issue(12)：3889-3894,6.DOI:10.3969/j.issn.1001-3695.2017.12.083
结合全局和局部信息的水平集图像分割方法
Level set image segmentation method by global and local information
摘要
Abstract
LBF model is very sensitive to the size and location of outline,and it only considers the local information,without considering the global information of the image.CV models consider global image information,it is robust to the initial profile.LBF and CV model can't obtain satisfactory segmentation results for salt and pepper noise pollution image.To solve these problems,thispaper defined a new energy fitting items respectively based on the original CV model and LBF energy function to enhance noise immunity for Gaussian noise and salt & pepper noise.It employed the improved CV model to obtain coarse segmentation,and employed the improved LBF model to obtain accurately segmentation result with the initial contour based on the coarse result.This paper proposed a new edge detection operator to redefine the edge stop function to further improve the noise immunity of the model.Compared to the CV model,LBF model,Wang model and Qi model using global and local information,the proposed model can get better segmentation results,with strong noise immunity.关键词
图像分割/图像噪声/拟合项/全局和局部信息/边缘检测算子Key words
image segmentation/image noise/fitting term/global and local information/edge detection operator分类
信息技术与安全科学引用本文复制引用
刘晨,池涛,李丙春,张宗虎..结合全局和局部信息的水平集图像分割方法[J].计算机应用研究,2017,34(12):3889-3894,6.基金项目
国家自然科学基金资助项目(61561027) （61561027）
国家教育部青年专项资助项目(ECA150375) （ECA150375）
新疆高校科研计划青年资助项目(XJEDU2016S076) （XJEDU2016S076）
