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浙江大学学报(工学版)
J4  2010, Vol. 44 Issue (12): 2236-2240    DOI: 10.3785/j.issn.1008-973X.2010.12.002
自动化技术、计算机技术     
用于图像分割的边界保持局部拟合模型
孔丁科1,2, 汪国昭1
1.浙江大学 计算机图像图形研究所,浙江 杭州 310027; 2.浙江工商大学 计算机与信息工程学院,
浙江 杭州 310018
Edge-preserving local fitting model for image segmentation
KONG Ding-ke1,2, WANG Guo-zhao1
1. Institute of Computer Graphics and Image Processing, Zhejiang University, Hangzhou 310027, China; 2. College of
Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China
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摘要：

针对局部二值拟合变分水平集模型(LBF模型)的分割质量很大程度上取决于核带宽的选取,容易造成冗余轮廓、边界模糊等问题,提出一种基于边界保持局部拟合的变分水平集模型.该模型引入图像相依的测地时间定义核函数,结合空间距离和图像梯度,自适应地选取邻域采样点;同时,采用基于多波段的图像梯度,并相应地调整图像点的相异性测度,将模型的应用范围扩展至彩色及多光谱图像.实验结果表明：该模型能选取较大核带宽并有效保留潜在的边界信息,从而避免了核带宽的选取问题,较好地应用于灰度异质图像的精确分割;而且,该模型对彩色及多光谱图像的分割也同样有效.
Abstract:

Due to the fact that the segmentation accuracy of local binary fitting energy based variational model (LBF model) is highly dependent on kernel bandwidth, and it always leads to unsatisfactory segmentation results (e.g., unnecessary contours, rough boundaries) of inhomogeneous images because of inappropriate bandwidth, an novel edge-preserving local fitting model was proposed and well adapted to segment images with intensity inhomogeneity. First, a geodesic time based kernel using spatial location and spectral gradient was defined, and it provided an adaptive geodesic neighborhood for every pixel. Then, an efficient multichannel gradient based extension combined with adjusted dissimilarity measure was enforced to segment color and multispectral images. Experimental results showed that the proposed model can remain potential edge information while using larger bandwidth, and desirable segmentation results of both gray and color images can be obtained.
出版日期: 2010-12-01
:  TP 391  
基金资助:

国家自然科学基金资助项目(60773179,60933008,60970079).
通讯作者: 汪国昭,男,教授,博导.     E-mail: wanggz@zju.edu.cn
作者简介: 孔丁科（1980—）,男,浙江舟山人,博士,讲师,从事计算机图像图形方面的研究.E-mail: dinckong@gmail.com
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引用本文:

孔丁科, 汪国昭. 用于图像分割的边界保持局部拟合模型[J]. J4, 2010, 44(12): 2236-2240.

KONG Ding-ke, WANG Guo-zhao. Edge-preserving local fitting model for image segmentation. J4, 2010, 44(12): 2236-2240.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2010.12.002    或    http://www.zjujournals.com/eng/CN/Y2010/V44/I12/2236

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