@inproceedings{7a74abf198884e239275ee32279e8708,
title = "A Remote Sensing Image Matching Algorithm Based on Anisotropic Scale Space",
abstract = "Aiming at the influence of nonlinear brightness difference and noise on remote sensing image matching algorithm, a remote sensing image matching algorithm based on anisotropic scale space is proposed. Firstly, we use the additiveoperator splitting (AOS) algorithm to build the anisotropics cale space; Then, we extract feature points in the nonlinear scale space by Harris algorithm, and use the improved SIFT descriptor to describe the features; Finally, the nearest neighbor distance ratio is used to filter the matching point pairs, and the fast sample consensus (FSC) algorithm is used to delete the mismatch to improve the matching accuracy. This method can maintain the matching accuracy while increase the number of points. Extensive experiments results on different sensors that our method can improve the matching accuracy.",
keywords = "AOS, Feature detection, image registration, scale-invariant feature transform (SIFT)",
author = "Manjun Yan and Zefu Tan and Weiming Tian and Aijun Tan and Yi Zhang",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019 ; Conference date: 11-12-2019 Through 13-12-2019",
year = "2019",
month = dec,
doi = "10.1109/ICSIDP47821.2019.9173406",
language = "English",
series = "ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019",
address = "United States",
}