电子学报 ›› 2015, Vol. 43 ›› Issue (10): 1994-2000.DOI: 10.3969/j.issn.0372-2112.2015.10.017

• 学术论文 • 上一篇    下一篇

多源影像融合与分割的协同方法

陈荣元1,2, 郑晨3, 申立智1, 李广琼1, 谭利娜1   

  1. 1. 湖南商学院计算机与信息工程学院, 湖南长沙 410205;
    2. 国防科学技术大学计算机学院, 湖南长沙 410073;
    3. 河南大学数学与信息科学学院, 河南开封 475000
  • 收稿日期:2014-09-23 修回日期:2014-11-18 出版日期:2015-10-25 发布日期:2015-10-25
  • 通讯作者: 申立智
  • 作者简介:陈荣元 男,1976年6月生,江苏兴化人,2010年于武汉大学获得博士学位,计算机学会高级会员,现为湖南商学院高级实验师、国防科学技术大学计算机学院博士后,主要研究方向为图像处理和数据挖掘.E-mail:chenrongyuan@126.com.
  • 基金资助:

    国家自然科学基金(No.41101425,No.41301470,No.61471170);湖南省教育厅资助科研项目(No.12B071,No.13A048);湖南省科技计划项目 (No.2012FJ3060);湖南省自然科学基金(No.13JJ3111);湖南省重点学科建设项目

Cooperation between Fusion and Segmentation for Multisource Image

CHEN Rong-yuan1,2, ZHENG Chen3, SHEN Li-Zhi1, LI Guang-Qiong1, TAN Li-Na1   

  1. 1. School of computer and Information Engineering, Hunan University of Commerce, Changsha, Hunan 410205, China;
    2. School of Computer, National University of Defense Technology, Changsha, Hunan, 410073, China;
    3. School of Mathematics and Information Sciences, Henan University, Kaifeng, Henan, 475000, China
  • Received:2014-09-23 Revised:2014-11-18 Online:2015-10-25 Published:2015-10-25

摘要:

针对现有影像融合与分割方法之间缺乏协同的问题,借鉴数据同化系统能够协同其模型算子和观测算子,并且能够自适应地优化其本身的思想,提出一个多源影像融合与分割的协同框架.在该框架下,以基于对比度金字塔变换和基于非下采样的Contourlet变换的两种融合方法分别模拟模型算子和观测算子,以评价分割效果的概率随机系数为目标函数,以带交叉算子的粒子群算法作为数据同化系统的优化算法.该框架可根据融合结果影像来调整分割算法的参数,利用分割结果来指导融合结果的优化,从而使得影像融合与分割协同工作.二组实验验证了该框架的有效性.

关键词: 影像分割, 影像融合, 粒子群优化算法, 数据同化

Abstract:

In order to solve the problem that lack of coordination between image fusion and segmentation methods.A cooperation framework for multisource remote sensing images fusion and segmentation was proposed in view of the advantage that data assimilation system can integrate its model operator and observation operator, and it can be optimized itself.Under this framework, two fusion methods based on contrast Pyramid transform and nonsubsampled contourlet transform were used as model operator and observation operator, the objective function was composed of probabilistic rand index to evaluate segmentation effect and particle swarm optimization with crossover operator was employed.The framework can adaptively adjust the parameters of segmentation algorithm according to fused images, and can use the segmentation results to guide the optimization of fused images, so as to make image fusion and image segmentation cooperate with each other.Two groups of experiments validate the effectiveness of the framework.

Key words: image segmentation, image fusion, particle swarm optimization algorithm, data assimilation

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