测绘通报 ›› 2018, Vol. 0 ›› Issue (2): 55-60,93.doi: 10.13474/j.cnki.11-2246.2018.0044

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A Method of SIFT Matching Error Elimination for Heterogeneous Optical Images Based on Neighborhood Voting

SHEN Yuzhen, LI Baishou, LI Lingzhi, YANG Lu   

  1. College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China
  • Received:2017-05-25 Online:2018-02-25 Published:2018-03-06

Abstract:

Heterogeneous remote sensing image matching is an important part of the high score image processing and key issues,but the current heterogeneous high score image matching accuracy needs to be improved.In this paper, a method of SIFT matching error rejection for heterogeneous optical images based on neighborhood voting is proposed.First this paper uses the scale invariant feature transform (SIFT) to extract the feature points.Then,the secondary constraint is applied to the matching feature points based on the neighborhood voting.Finally,this paper distinguishes the error to be removed from the matching point,and determines the exact match point.In order to evaluate the accuracy of the method, it researches on the buildings, roads, water body matching respectively. Experiments show that the method can improve the matching accuracy of the above three kinds of land types,compared to the traditional SIFT method increased by an average of 66%, while effectively maintaining the scale of the scale invariance.

Key words: neighborhood voting, heterogeneous, optical image, SIFT algorithm, image matching

CLC Number: