华南理工大学学报(自然科学版) ›› 2010, Vol. 38 ›› Issue (12): 50-55.doi: 10.3969/j.issn.1000-565X.2010.12.010

• 电子、通信与自动控制 • 上一篇    下一篇

基于分布质量的遥感图像配准控制点筛选方法

郭琰 谷延锋 关卓威 张晔   

  1. 哈尔滨工业大学 图像与信息技术研究所, 黑龙江 哈尔滨 150001
  • 收稿日期:2010-03-08 修回日期:2010-08-03 出版日期:2010-12-25 发布日期:2010-12-25
  • 通信作者: 郭琰(1980-),男,博士生,主要从事多传感器图像配准与变化检测研究. E-mail:guoyan3000@gmail.com
  • 作者简介:郭琰(1980-),男,博士生,主要从事多传感器图像配准与变化检测研究.
  • 基金资助:

    国家自然科学基金资助项目(60872098 60972143 60972144)

Method for Selecting Control Points for Remote Sensing Image Registration Based on Distribution Quality

Guo Yan  Gu Yan-feng  Guan Zhuo-wei  Zhang Ye   

  1. Institute of Image and Information Technology,Harbin Institute of Technology,Harbin 150001,Heilongjiang,China
  • Received:2010-03-08 Revised:2010-08-03 Online:2010-12-25 Published:2010-12-25
  • Contact: 郭琰(1980-),男,博士生,主要从事多传感器图像配准与变化检测研究. E-mail:guoyan3000@gmail.com
  • About author:郭琰(1980-),男,博士生,主要从事多传感器图像配准与变化检测研究.
  • Supported by:

    国家自然科学基金资助项目(60872098 60972143 60972144)

摘要: 为提高遥感图像配准精度,提出了一种基于均匀分布质量的配准控制点筛选方法.首先,以尺度不变特征变换获取控制点,采用随机抽样一致性筛除误匹配控制点,然后对配准图像公共区域分块进行基于分布质量的控制点筛选,采用最小二乘估计仿射变换模型参数,最后对输入图像坐标变换后完成配准.对多种遥感图像的实验结果表明,所提出的方法能有效删除误匹配控制点,使控制点均匀分布,减小配准误差.

关键词: 遥感图像, 图像配准, 控制点, 分布质量, 尺度不变特征变换, 随机抽样一致性

Abstract:

In order to improve the registration accuracy of remote sensing image,a method for selecting control points is proposed based on uniform distribution quality.In this method,first,control points are extracted via the scale-invariant feature transform,and wrong matched control points are deleted by means of random sample consensus(RANSAC).Then,the common area of the image pair is divided into several sub-regions and suitable control points are selected according to the distribution quality.Finally,the parameters of the affine transformation model are estimated through the least squares approximation and the registration is conducted via the coordinate transformation of the input image.Experimental results of various kinds of remote sensing images prove that the proposed method effectively removes the wrong matched control points,guarantees the distribution uniformity of control points and reduces the registration error.

Key words: remote sensing image, image registration, control point, distribution quality, scale-invariant feature transform, random sample consensus