An Image Registration Method for Multisource High-Resolution Remote Sensing Images for Earthquake Disaster Assessment
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College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
2
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
3
Hainan Key Laboratory of Earth Observation, Sanya 572029, China
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(8), 2286; https://doi.org/10.3390/s20082286
Received: 29 February 2020
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Revised: 15 April 2020
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Accepted: 16 April 2020
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Published: 17 April 2020
(This article belongs to the Section Remote Sensors)
For earthquake disaster assessment using remote sensing (RS), multisource image registration is an important step. However, severe earthquakes will increase the deformation between the remote sensing images acquired before and after the earthquakes on different platforms. Traditional image registration methods can hardly meet the requirements of accuracy and efficiency of image registration of post-earthquake RS images used for disaster assessment. Therefore, an improved image registration method was proposed for the registration of multisource high-resolution remote sensing images. The proposed method used the combination of the Shi_Tomasi corner detection algorithm and scale-invariant feature transform (SIFT) to detect tie points from image patches obtained by an image partition strategy considering geographic information constraints. Then, the random sample consensus (RANSAC) and greedy algorithms were employed to remove outliers and redundant matched tie points. Additionally, a pre-earthquake RS image database was constructed using pre-earthquake high-resolution RS images and used as the references for image registration. The performance of the proposed method was evaluated using three image pairs covering regions affected by severe earthquakes. It was shown that the proposed method provided higher accuracy, less running time, and more tie points with a more even distribution than the classic SIFT method and the SIFT method using the same image partitioning strategy.
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Keywords:
image registration; multisource high-resolution remote sensing image; earthquake damage assessment; Shi_Tomasi corner detection algorithm; SIFT
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MDPI and ACS Style
Zhao, X.; Li, H.; Wang, P.; Jing, L. An Image Registration Method for Multisource High-Resolution Remote Sensing Images for Earthquake Disaster Assessment. Sensors 2020, 20, 2286. https://doi.org/10.3390/s20082286
AMA Style
Zhao X, Li H, Wang P, Jing L. An Image Registration Method for Multisource High-Resolution Remote Sensing Images for Earthquake Disaster Assessment. Sensors. 2020; 20(8):2286. https://doi.org/10.3390/s20082286
Chicago/Turabian StyleZhao, Xin, Hui Li, Ping Wang, and Linhai Jing. 2020. "An Image Registration Method for Multisource High-Resolution Remote Sensing Images for Earthquake Disaster Assessment" Sensors 20, no. 8: 2286. https://doi.org/10.3390/s20082286
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