Multi-source matching of multi-sensor images based on edge line features

doi:10.3788/OPE.20152313.0753

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Multi-source matching of multi-sensor images based on edge line features

更新时间：2020-08-13

- Multi-source matching of multi-sensor images based on edge line features
- Optics and Precision Engineering Vol. 23, Issue 10z, Pages: 752-760(2015)
- 作者机构：
  
  西安电子科技大学机电工程学院, 陕西西安 710071
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20152313.0753
  CLC： TP391.4
- Received：02 June 2015，
  
  Revised：20 June 2015，
  
  Published：14 November 2015
- 稿件说明：
移动端阅览
方兰兰, 刘贵喜, 吕孟娇等. 利用边缘直线特征的异源图像配准[J]. 光学精密工程, 2015,23(10z): 752-760

FANG Lan-lan, LIU Gui-xi, L&#220 etc. Multi-source matching of multi-sensor images based on edge line features[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 752-760
方兰兰, 刘贵喜, 吕孟娇等. 利用边缘直线特征的异源图像配准[J]. 光学精密工程, 2015,23(10z): 752-760 DOI： 10.3788/OPE.20152313.0753.

FANG Lan-lan, LIU Gui-xi, L&#220 etc. Multi-source matching of multi-sensor images based on edge line features[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 752-760 DOI： 10.3788/OPE.20152313.0753.

摘要

针对异源异构图像中无法利用特征点进行图像匹配的问题

提出了一种基于直线的图像匹配方法。首先

检测出图像的边缘点并连接成曲线

利用多尺度策略提取边缘直线段;然后

根据空间接近性和相对显著性

将边缘直线段进行分组

每个组都被看作是直线的一个特征

称其为直线标签;最后

根据线段的几何形状计算线段之间的相似性

从而判断两个直线标签之间是否相似

并利用快速匹配算法进行匹配。类似于局部特征

直线特征具有鲁棒性

适用于视角的变化。与现有的局部特征匹配方法相比

本文的直线方法更适用于缺乏纹理

纹理不清晰

光照变化很大以及异源异构的场景图像。实验结果表明

本文的算法具有尺度不变性、旋转不变性以及光照不变性

能有效地解决无法用点特征匹配算法的场景图像之间的匹配

匹配精度在1 pixel以内。

Abstract

A novel multi-source image matching strategy based on line feature extraction algorithm was proposed to overcome the shortcoming of point feature matching algorithm. Firstly

image edge points were detected and connected into curves

and the edge line segment was extracted by utilizing multi-scale strategy. Then

based on the spatial proximity and relative significance

the edge line segment was divided into lots of groups

and each of them was regarded as a feature of line called line labels. Finally

the similarity between the lines was computed according to the line geometry. Consequently

whether the two line labels are similar could be verified and then they were matched by the fast matching algorithm. Similar to local feature

the line feature is robust and adapted to changes of angle of view. Compared to matching approaches based on existing local features

the proposed method is more suitable for the images with low-texture scenes

blurring-texture scenes

high changing of illumination or multi-source scenes. Experimental results indicate that the proposed algorithm has scale invariant

rotate invariant and illumination invariant and can solve the situation in which point feature matching algorithm is not available and the matching accuracy is within one pixel.

关键词

Keywords

references

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