计算机科学 ›› 2015, Vol. 42 ›› Issue (6): 57-60.doi: 10.11896/j.issn.1002-137X.2015.06.013

• 第十届和谐人机环境联合学术会议 • 上一篇    下一篇

基于信息熵与SIFT算法的天文图像配准

岳昕,尚振宏,强振平,刘 辉,付晓东,张志华   

  1. 昆明理工大学信息工程与自动化学院 昆明650504,昆明理工大学信息工程与自动化学院 昆明650504,西南林业大学计算机与信息学院 昆明650224,昆明理工大学信息工程与自动化学院 昆明650504,昆明理工大学信息工程与自动化学院 昆明650504,昆明理工大学信息工程与自动化学院 昆明650504
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金资助

Astronomical Image Registration Combining Information Entropy and SIFT Algorithm

YUE Xin, SHANG Zhen-hong, QIANG Zhen-ping, LIU Hui, FU Xiao-dong and ZHANG Zhi-hua   

  • Online:2018-11-14 Published:2018-11-14

摘要: 天文图像配准是研究天体运动的一项关键技术,图像内部结构往往存在轻微的不规则运动。但是图像配准涉及到计算整个图像的变换关系,在此情况下,无论是采用基于统计特征还是基于局部特征的配准方法,都难以取得理想的效果。为此,提出基于信息熵与SIFT算法的天文图像配准方法。该方法首先需对图像进行均匀分块并计算每块熵值,以熵值最大者作为配准的局部子图,然后通过尺度不变特征变换(Scale Invariant Feature Transform,SIFT)及仿射变换建立变换关系,继而利用局部子图变换关系完成图像的配准。该方法一方面能缩短变换关系的建立时间,另一方面能保证图像中信息熵最大区域配准,有效提高天文图像配准质量。

关键词: 信息熵,SIFT算法,均匀分割,仿射变换,变换关系

Abstract: Astronomical image registration is a key technology of astronomical movement study,and often there is some slight irregular motion of internal structures in the image.However,in image registration the transformation of an entire image needs to be calcu lated.In this case,no matter whether registration is based on statistical characteristics or local features,it is difficult to achieve the desired results.On this basis,image is divided into several small squares firstly,and the entropy is calculated.Then square with maximum entropy is considered as the local sub-graph to register.Scale invariant feature transform and the affine transformation are used to establish relationships between local sub-graphs to complete image registration.On the one hand,this method can reduce the time of building transform relationship.On the other hand,it ensures the registration of the image area with maximum information entropy,and it also improves the registration quality of astronomical images effectively.

Key words: Entropy,SIFT algorithm,Evenly split,Affine transformation,Transform relation

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