测绘学报

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利用局部自相似的多光谱遥感图像自动配准

叶沅鑫1,单杰1,2,彭剑威1   

  1. 1. 武汉大学
    2. 美国普渡大学土木工程学院, 西拉法叶, 47907
  • 收稿日期:2012-11-19 修回日期:2013-12-06 出版日期:2014-03-20 发布日期:2013-12-19
  • 通讯作者: 叶沅鑫
  • 基金资助:

    精密工程与工业测量国家测绘局重点实验室资助项目;广西自然科学基金重点项目

Automated Multispectral Remote Sensing Image Registration Based on Local Self-similarity

  • Received:2012-11-19 Revised:2013-12-06 Online:2014-03-20 Published:2013-12-19

摘要:

为解决多光谱遥感图像间非线性灰度差异造成的配准困难问题,提出了一种基于局部自相似的自动配准方法。该方法首先引入局部自相似(local self-similarity, LSS)特征,并在对数极坐标系下建立反映图像内在几何布局和形状属性的特征描述子。之后结合LSS和归一化相关系数构建一种形状相似性测度,并通过模板匹配的策略实现图像的配准。试验结果表明,该方法能够较好地抵抗图像间的非线性灰度差异,并获得了可靠的配准精度,而且相比于传统方法,在顾及计算效率的同时获得了更高的匹配正确率。

关键词: 多光谱遥感图像, 自动配准, 局部自相似, 互信息, 匹配正确率

Abstract:

This paper proposes an automated registration method for multispectral remote sensing images to address the significant non-linear intensity differences among such images. The proposed method first introduces the local self-similarity (LSS) feature, and builds the feature descriptors capturing the internal geometric layouts and shape properties of images in the log-polar coordinate. Then, a shape similarity measure is defined by combining LSS and normalized correlation coefficient, followed by the template-matching scheme to achieve image registration. Experimental results show that the proposed method is robust to non-linear intensity differences among images and achieves reliable registration accuracy,and obtains a higher correct matching rate in consideration of the computational efficiency compared with state-of-art registration methods.

Key words: multispectral remote sensing image, automatic registration, LSS, mutual information, correct matching rate

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