Computer Science ›› 2019, Vol. 46 ›› Issue (4): 280-284.doi: 10.11896/j.issn.1002-137X.2019.04.044

• Graphics ,Image & Pattern Recognition • Previous Articles     Next Articles

Multispectral Image Matching Algorithm Based on Improved SIFT

SUN Xue-qiang1,2, HUANG Min1, ZHANG Gui-feng1, ZHAO Bao-wei1, CONG Lin-xiao1,2   

  1. Key Laboratory of Computation Optical Imaging Technology,Academy of Opto-Electronics,Chinese Academy of Sciences,Beijing 100094,China1
    College of Materials Science and Optoelectronic Technology,University of Chinese Academy of Sciences,Beijing 100049,China2
  • Received:2018-03-17 Online:2019-04-15 Published:2019-04-23

Abstract: In order to solve the problem that the speed and accuracy need to be taken into account simultaneously when conducting multispectral image matching,this paper improved the SIFT algorithm from the following several aspects.Aiming at the problems such as the slow matching speed and low matching rate caused by high dimension of feature descriptors,this paper improved the structure of feature descriptors to reduce the dimensions of descriptors.In the aspect of SIFT feature matching,firstly,the feature point is determined as the maximum point or minimum point according to the trace of Hessian matrix,which can narrow subsequent search range for the feature vector matching.Then,the partial matching point pairs are eliminated based on the position information of feature points.The experimental results show that the improved algorithm not only preserves the invariance advantages of the traditional algorithm,such as rotation and brightness,but also can effectively reduce the running time,and improve the matching rate on a certain extent.

Key words: Feature descriptor, Feature vector matching, Multispectral image, SIFT

CLC Number: 

  • TP391
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