测绘学报

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基于梯度径向夹角直方图的异源图像匹配

李壮1,雷志辉2,于起峰2   

  1. 1. 国防科技大学
    2. 国防科学技术大学
  • 收稿日期:2010-02-24 修回日期:2010-06-21 出版日期:2011-06-25 发布日期:2011-06-25
  • 通讯作者: 李壮

Matching Multi-sensor Images Based on Gradient Radius Angle Pyramid Histogram

  • Received:2010-02-24 Revised:2010-06-21 Online:2011-06-25 Published:2011-06-25

摘要: 异源图像匹配是视觉导航、多源图像融合分析的关键步骤之一,常用的匹配方法是分别从两幅图像中提取特征,再对特征进行匹配。但是对于成像机理差别较大的异源图像,如SAR图像和可见光图像,很难提取到同名特征。本文提出一种基于特征支持度的异源图像匹配方法,只需要从一幅图像中提取边缘特征,在变换空间中寻找另一幅图像对该特征的最大支持度。支持度的计算采用了标准化方向梯度强度和的形式。采用遗传算法对支持度函数解空间进行全局优化搜索来获取匹配解。实验结果表明,该方法能有效实现SAR图像和可见光图像的匹配。

Abstract: Traditional algorithm for matching multi-sensor images are mostly based on region information, which is sensitive to image rotation. This paper presents a new rotate-invariant feature named Gradient Radius Angle Pyramid Histogram(GRAPH), that can be used in matching multi-sensor images of arbitrary angle. We calculate the Gradient Radius Angle(GRA) based on normalized gradient vector and radius direction vector. The GRA is invariant to image rotation and robust to image noise, and illumination change. To get sparse description, we use circle region histogram to represent the statistic distribution of GRA. Pyramid Histogram(PH) is utilized to replace simple histogram for better distinctive capability. Experimental results show that the GRAPH feature can distinguish images of different scenes and accommodates to image rotation. Multi-sensor images are reliably matched based on GRAPH feature.