Volume XLI-B1
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 253-257, 2016
https://doi.org/10.5194/isprs-archives-XLI-B1-253-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 253-257, 2016
https://doi.org/10.5194/isprs-archives-XLI-B1-253-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  03 Jun 2016

03 Jun 2016

A NOVEL SUB-PIXEL MATCHING ALGORITHM BASED ON PHASE CORRELATION USING PEAK CALCULATION

Junfeng Xie1, Fan Mo1,2, Chao Yang1, Pin Li1,4, and Shiqiang Tian1,3 Junfeng Xie et al.
  • 1Satellite Surveying and Mapping Application Center of China, NO.1 Baisheng Village, Beijing
  • 2Information Engineering University, No.62 Kexue Road, Zhengzhou
  • 3Chang'an University, Middle-section of Nan'er Huan Road, Xi'an
  • 4Liaoning Project Technology University, People Street, Fuxin

Keywords: Image Matching, Phase Correlation, Peak Calculation, Window Constraint, Correlation Coefficient

Abstract. The matching accuracy of homonymy points of stereo images is a key point in the development of photogrammetry, which influences the geometrical accuracy of the image products. This paper presents a novel sub-pixel matching method phase correlation using peak calculation to improve the matching accuracy. The peak theoretic centre that means to sub-pixel deviation can be acquired by Peak Calculation (PC) according to inherent geometrical relationship, which is generated by inverse normalized cross-power spectrum, and the mismatching points are rejected by two strategies: window constraint, which is designed by matching window and geometric constraint, and correlation coefficient, which is effective for satellite images used for mismatching points removing. After above, a lot of high-precise homonymy points can be left. Lastly, three experiments are taken to verify the accuracy and efficiency of the presented method. Excellent results show that the presented method is better than traditional phase correlation matching methods based on surface fitting in these aspects of accuracy and efficiency, and the accuracy of the proposed phase correlation matching algorithm can reach 0.1 pixel with a higher calculation efficiency.