Remote sensing image matching algorithm based on the correlation coefficient-least square method

Yu Wang; Bo Li; Yufei Ding; Hongyan He

doi:10.1117/12.2666545

4 April 2023 Remote sensing image matching algorithm based on the correlation coefficient-least square method

Yu Wang, Bo Li, Yufei Ding, Hongyan He

Proceedings Volume 12617, Ninth Symposium on Novel Photoelectronic Detection Technology and Applications; 126175K (2023) https://doi.org/10.1117/12.2666545
Event: 9th Symposium on Novel Photoelectronic Detection Technology and Applications (NDTA 2022), 2022, Hefei, China

Abstract

Image matching is an important part of remote sensing image processing, since it is the basis for 3D reconstruction of ground objects. In this paper, the correlation coefficient-least square method was applied for an innovative image matching algorithm. With two aerial images as data, the feature points were firstly extracted and then the image pyramid was built. The correlation coefficient-least square method was carried out after that. According to experimental results, the correlation coefficient-least square method can respectively achieve one-pixel and sub-pixel image matching. The key point of this new proposed image matching is algorithms is to determine the appropriate threshold so that both the number of feature points and the matching time can be improved.

Citation Download Citation

Yu Wang, Bo Li, Yufei Ding, and Hongyan He "Remote sensing image matching algorithm based on the correlation coefficient-least square method", Proc. SPIE 12617, Ninth Symposium on Novel Photoelectronic Detection Technology and Applications, 126175K (4 April 2023); https://doi.org/10.1117/12.2666545

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