基于几何不变量的形状上下文星图配准

庄幽文; 高昆; 卢岩; 韩璐

doi:10.3788/OPE.20152313.0631

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基于几何不变量的形状上下文星图配准

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- 基于几何不变量的形状上下文星图配准
- Star image matching by using geometric invariants
- 光学精密工程 2015年23卷第10z期页码：630-636
- 作者机构：
  
  北京理工大学光电学院北京,100081
- 作者简介：
- 基金信息：
  
  国家自然科学基金(No.61340018,No.61271427)和北京市自然科学基金项目(No.4152045)联合资助项目()
- DOI：10.3788/OPE.20152313.0631
  中图分类号： TP391.4
- 收稿日期：2015-05-28，
  
  修回日期：2015-06-12，
  
  纸质出版日期：2015-11-14
- 稿件说明：
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庄幽文, 高昆, 卢岩等. 基于几何不变量的形状上下文星图配准[J]. 光学精密工程, 2015,23(10z): 630-636

ZHUANG You-wen, GAO Kun, LU Yan etc. Star image matching by using geometric invariants[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 630-636
庄幽文, 高昆, 卢岩等. 基于几何不变量的形状上下文星图配准[J]. 光学精密工程, 2015,23(10z): 630-636 DOI： 10.3788/OPE.20152313.0631.

ZHUANG You-wen, GAO Kun, LU Yan etc. Star image matching by using geometric invariants[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 630-636 DOI： 10.3788/OPE.20152313.0631.

摘要

针对多画面天文星图的刚性配准

提出一种基于几何不变量的形状上下文配准算法。该算法首先对天文星图进行降噪预处理

并利用阈值分割与形态学算法提取天文星图中的星点及其质心坐标;然后利用星点质心间的几何不变量关系

对每个星点建立基于几何不变量的特征描述向量并由此构建了评价不同维数向量之间相似度的代价函数

以判断两个特征点之间特征描述向量的相似程度

从而得到两幅图像间的匹配星点对集合;最后

利用随机一致性鲁棒算法去除误匹配星点对

并计算得到空间变换配准参数。实验结果表明

该方法可对特征点数目、画面亮度等差异较大的两幅星图实现亚像素级精度的有效配准

性能及鲁棒性均好于传统配准方法。对于大小为46083072

曝光时间与ISO各不相同的两组实际拍摄图像

本文方法的配准精度在0.5 pixel左右

能够成功完成配准任务。

Abstract

To match rigidly star images with multi-screens

a shape context based registration method by using geometric invariants was proposed. First

denoise methods

segmented method and morphology method were applied to star images to extract star points

so that centroid of star points could be calculated. Then

feature descriptors for every star point were calculated based on geometric invariants among all stars. Each descriptor was used to represent the relationship between this star and others. A price function to evaluate the similarity between star points was constructed to get a star match pair set between the two images. Finally

random sample consensus robust method was used to remove wrong star match pairs and calculate registration parameters for the space transform. Experimental results demonstrate that proposed method can successfully match the image with different number of feature points and different brightnesses in a sub-pixel level. For two group images with the size of 4608*3072 and different ISOs

the proposed method can offer the registration accuracy near 0.5 pixel

which meets the requirements of the registration.

关键词

Keywords

references

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