摄影测量学与遥感

SAR影像与光学影像的高斯伽玛型边缘强度特征匹配法

  • 陈敏 ,
  • 朱庆 ,
  • 朱军 ,
  • 徐柱 ,
  • 黄澜心
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  • 1. 西南交通大学地球科学与环境工程学院, 四川 成都 611756;
    2. 四川省应急测绘与防灾减灾工程技术研究中心, 四川 成都 610041;
    3. 教育部轨道交通安全协同创新中心, 四川 成都 610031;
    4. 高速铁路运营安全空间信息技术国家地方联合工程实验室, 四川 成都 610031
陈敏(1986-),男,博士,讲师,研究方向为多源遥感影像处理与分析。

收稿日期: 2015-02-06

  修回日期: 2015-09-15

  网络出版日期: 2016-03-25

基金资助

国家自然科学基金(41471320;41501492);四川省科技支撑计划(2014SZ0106;2015SZ0046);四川省应急测绘与防灾减灾工程技术研究中心开放基金(K2015B006);测绘遥感信息工程国家重点实验室开放基金((14)Key03)

Feature Matching for SAR and Optical Images Based on Gaussian-Gamma-shaped Edge Strength Map

  • CHEN Min ,
  • ZHU Qing ,
  • ZHU Jun ,
  • XU Zhu ,
  • HUANG Lanxin
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  • 1. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China;
    2. Sichuan Engineering Research Center for Emergency Mapping & Disaster Reduction, Chengdu 610041, China;
    3. Collaborative Innovation Center for Rail Transport Safety, Chengdu 610031, China;
    4. State-Province Joint Engineering Laboratory of Spatial Information Technology for High-speed Railway Safety, Chengdu 610031, China

Received date: 2015-02-06

  Revised date: 2015-09-15

  Online published: 2016-03-25

Supported by

The National Natural Science Foundation of China(Nos.41471320;41501492);The Science and Technology Program of Sichuan Province of China(Nos.2014SZ0106;2015SZ0046);The Open Research Fund by Sichuan Engineering Research Center for Emergency Mapping & Disaster Reduction(No.K2015B006);The Open Research Fund of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing(No.(14) Key 03)

摘要

提出了一种基于影像边缘强度图描述的SAR影像与光学影像匹配方法。首先对影像进行粗纠正,消除影像之间的尺度和旋转变化;其次,改进相位一致性特征检测方法,提取对影像相干斑噪声稳健的特征点;然后基于高斯伽玛型双边窗口比值算子计算影像边缘强度图,在此基础上构造不变特征描述符;最后联合几何约束条件,实现SAR影像与光学影像匹配。试验结果证明,与现有方法相比,本文方法能够大幅提高SAR影像与光学影像匹配结果中的正确匹配特征数量以及影像配准精度。

本文引用格式

陈敏 , 朱庆 , 朱军 , 徐柱 , 黄澜心 . SAR影像与光学影像的高斯伽玛型边缘强度特征匹配法[J]. 测绘学报, 2016 , 45(3) : 318 -325 . DOI: 10.11947/j.AGCS.2016.20150084

Abstract

A matching method for SAR and optical images, robust to pixel noise and nonlinear grayscale differences, is presented. Firstly, a rough correction to eliminate rotation and scale change between images is performed. Secondly, features robust to speckle noise of SAR image are detected by improving the original phase congruency based method. Then, feature descriptors are constructed on the Gaussian-Gamma-shaped edge strength map according to the histogram of oriented gradient pattern. Finally, descriptor similarity and geometrical relationship are combined to constrain the matching processing.The experimental results demonstrate that the proposed method provides significant improvement in correct matches number and image registration accuracy compared with other traditional methods.

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