A Line Feature-Based Rotation Invariant Method for Pre- and Post-Damage Remote Sensing Image Registration

The accurate registration of pre- and post-damage images plays a vital role in the change analysis of the target area and the subsequent work of damage effect assessment. However, due to the impact of shooting time and damaged areas, there are large background and regional differences between pre- a...

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Main Authors: Yalun Zhao, Derong Chen, Jiulu Gong
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/17/2/184
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author Yalun Zhao
Derong Chen
Jiulu Gong
author_facet Yalun Zhao
Derong Chen
Jiulu Gong
author_sort Yalun Zhao
collection DOAJ
description The accurate registration of pre- and post-damage images plays a vital role in the change analysis of the target area and the subsequent work of damage effect assessment. However, due to the impact of shooting time and damaged areas, there are large background and regional differences between pre- and post-damage remote sensing images, and the existing image registration methods do not perform well. In this paper, a line feature-based rotation invariant image registration method is proposed for pre- and post-damage remote sensing images. First, we extract and screen straight line segments from the images before and after damage. Then, we design a new method to calculate the main direction of each line segment and rotate the image based on the current line segment’s main direction and the center coordinates. According to the spatial distribution (distance and angle) of the reference line segment relative to the remaining line segments, a line feature descriptor vector is constructed and matched for each line segment on the rotated image. Since the main edge contour can preserve more invariant features, this descriptor can be better applied to the registration of pre- and post-damage remote sensing images. Finally, we cross-pair the midpoints and endpoints of the matched line segments to improve the accuracy of subsequent affine transformation parameter calculations. In remote sensing images with large background and regional differences, the average registration precision of our method is close to 100%, and the root mean square error is about 1 pixel. At the same time, the rotation invariance of our method is verified by rotating the test images. In addition, the results of the comparative experiments show that the registration precision and error of the proposed method are better than those of the existing typical representative algorithms.
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spelling doaj-art-78423a0b98534243b2a6785edbf15b8d2025-01-24T13:47:39ZengMDPI AGRemote Sensing2072-42922025-01-0117218410.3390/rs17020184A Line Feature-Based Rotation Invariant Method for Pre- and Post-Damage Remote Sensing Image RegistrationYalun Zhao0Derong Chen1Jiulu Gong2School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaThe accurate registration of pre- and post-damage images plays a vital role in the change analysis of the target area and the subsequent work of damage effect assessment. However, due to the impact of shooting time and damaged areas, there are large background and regional differences between pre- and post-damage remote sensing images, and the existing image registration methods do not perform well. In this paper, a line feature-based rotation invariant image registration method is proposed for pre- and post-damage remote sensing images. First, we extract and screen straight line segments from the images before and after damage. Then, we design a new method to calculate the main direction of each line segment and rotate the image based on the current line segment’s main direction and the center coordinates. According to the spatial distribution (distance and angle) of the reference line segment relative to the remaining line segments, a line feature descriptor vector is constructed and matched for each line segment on the rotated image. Since the main edge contour can preserve more invariant features, this descriptor can be better applied to the registration of pre- and post-damage remote sensing images. Finally, we cross-pair the midpoints and endpoints of the matched line segments to improve the accuracy of subsequent affine transformation parameter calculations. In remote sensing images with large background and regional differences, the average registration precision of our method is close to 100%, and the root mean square error is about 1 pixel. At the same time, the rotation invariance of our method is verified by rotating the test images. In addition, the results of the comparative experiments show that the registration precision and error of the proposed method are better than those of the existing typical representative algorithms.https://www.mdpi.com/2072-4292/17/2/184image registrationline featurespost-damage imagesrotational invarianceremote sensing images
spellingShingle Yalun Zhao
Derong Chen
Jiulu Gong
A Line Feature-Based Rotation Invariant Method for Pre- and Post-Damage Remote Sensing Image Registration
Remote Sensing
image registration
line features
post-damage images
rotational invariance
remote sensing images
title A Line Feature-Based Rotation Invariant Method for Pre- and Post-Damage Remote Sensing Image Registration
title_full A Line Feature-Based Rotation Invariant Method for Pre- and Post-Damage Remote Sensing Image Registration
title_fullStr A Line Feature-Based Rotation Invariant Method for Pre- and Post-Damage Remote Sensing Image Registration
title_full_unstemmed A Line Feature-Based Rotation Invariant Method for Pre- and Post-Damage Remote Sensing Image Registration
title_short A Line Feature-Based Rotation Invariant Method for Pre- and Post-Damage Remote Sensing Image Registration
title_sort line feature based rotation invariant method for pre and post damage remote sensing image registration
topic image registration
line features
post-damage images
rotational invariance
remote sensing images
url https://www.mdpi.com/2072-4292/17/2/184
work_keys_str_mv AT yalunzhao alinefeaturebasedrotationinvariantmethodforpreandpostdamageremotesensingimageregistration
AT derongchen alinefeaturebasedrotationinvariantmethodforpreandpostdamageremotesensingimageregistration
AT jiulugong alinefeaturebasedrotationinvariantmethodforpreandpostdamageremotesensingimageregistration
AT yalunzhao linefeaturebasedrotationinvariantmethodforpreandpostdamageremotesensingimageregistration
AT derongchen linefeaturebasedrotationinvariantmethodforpreandpostdamageremotesensingimageregistration
AT jiulugong linefeaturebasedrotationinvariantmethodforpreandpostdamageremotesensingimageregistration