测绘学报 ›› 2021, Vol. 50 ›› Issue (10): 1390-1403.doi: 10.11947/j.AGCS.2021.20200587

• 摄影测量学与遥感 • 上一篇    下一篇

SAR影像和光学影像梯度方向加权的快速匹配方法

樊仲藜1, 张力1, 王庆栋1, 刘思婷1,2, 叶沅鑫3   

  1. 1. 中国测绘科学研究院, 北京 100039;
    2. 兰州交通大学测绘与地理信息学院, 甘肃 兰州 730070;
    3. 西南交通大学地球科学与环境工程学院, 四川 成都 611756
  • 收稿日期:2020-12-08 修回日期:2021-07-21 发布日期:2021-11-09
  • 通讯作者: 王庆栋 E-mail:wangqd@casm.ac.cn
  • 作者简介:樊仲藜(1997-),男,硕士生,研究方向为星载多源传感器数据高精度协同处理。E-mail:fzl10466@163.com
  • 基金资助:
    国家重点研发计划(2019YFB1405600)

A fast matching method of SAR and optical images using angular weighted orientated gradients

FAN Zhongli1, ZHANG Li1, WANG Qingdong1, LIU Siting1,2, YE Yuanxin3   

  1. 1. Chinese Academy of Surveying and Mapping, Beijing 100039, China;
    2. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China;
    3. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
  • Received:2020-12-08 Revised:2021-07-21 Published:2021-11-09
  • Supported by:
    The National Key Research and Development Program of China (No. 2019YFB1405600)

摘要: 针对SAR影像与光学影像之间存在显著的非线性灰度差异导致影像匹配困难的问题,本文提出了一种基于影像结构特性的快速匹配方法(SAR-to-optical fast matching algorithm,SOFM)。传统基于影像灰度的匹配方法一般难以抵抗影像间的非线性灰度差异,而影像中的几何结构和形状特征在不同类型的影像之间较为稳定,因此本文综合利用影像的梯度幅值和梯度方向信息构建出一种能够有效表达影像结构的特征描述符—角度加权方向梯度(angular weighted orientated gradients,AWOG),随后基于模板匹配的策略,选择描述符之间的差值的平方和(sum of squared difference,SSD)建立用于匹配的相似性测度,并给出了在频率域中表达的影像匹配函数。基于SOFM方法建立了一套完整的影像匹配流程,随后选择多组影像进行匹配试验,结果表明,本文方法能够有效抵抗SAR影像与光学影像之间的非线性灰度差异,并且在匹配性能和匹配精度等方面都优于经典的基于影像灰度的匹配方法以及其他基于影像结构特性的匹配方法。

关键词: SAR影像, 光学影像, 结构特性, 影像梯度, 模板匹配

Abstract: To solve the problem of matching difficulty caused by the significant nonlinear grayscale differences between SAR and optical images, this paper proposes a fast matching algorithm based on image structural properties named SOFM(SAR-to-optical fast matching algorithm).The traditional methods based on image grayscale are generally difficult to resist the nonlinear grayscale differences between SAR and optical images, but the geometric constructs and shape features can exist stably among different types of images, so in our the proposed method both the magnitude and orientation information of image gradient are used to build a geometric structural feature descriptor named AWOG(angular weighted orientated gradients), then based on the template matching strategy, the sum of squared difference of the descriptors is used to define the similarity metric for matching and then the image matching function expressed in the frequency domain is given. A complete set of image matching process is established based on SOFM, and has been validated using multiple pairs of SAR and optical images, the results show that the proposed method can effectively resist the nonlinear grayscale differences between SAR and optical images, and outperforms the traditional classical image grayscale-based methods and existing image structural-based methods in matching performance and precision.

Key words: SAR images, optical images, structural properties, image gradient, template matching

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