A robust registration method for UAV thermal infrared and visible images taken by dual-cameras

Meng, Lingxuan; Zhou, Ji; Liu, Shaomin; Wang, Ziwei; Zhang, Xiaodong; Ding, Lirong; Shen, Li; Wang, Shaofei

doi:10.1016/j.isprsjprs.2022.08.018

Cited by 10 publications

(3 citation statements)

References 62 publications

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“…The area-based approach fails to achieve location accuracy and robustness simultaneously, whereas the machine-learning-based method requires excessive computation [35][36][37]. To solve these problems, we referred to Meng et al (2022), who used the template matching with weights, multilevel local max-pooling and max index backtracking (TWMM) method to register the TIR & V images taken by the UAV equipped with a TIR & V sensor [38]. As a result, the correct matching rate for 1000 image groups was 96%.…”

Section: Registration and Automatic Identificationsmentioning

confidence: 99%

Automatic Identification of Earth Rock Embankment Piping Hazards in Small and Medium Rivers Based on UAV Thermal Infrared and Visible Images

Li,

Wang,

Sun

et al. 2023

Remote Sensing

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Piping is a major factor contributing to river embankment breaches, particularly during flood season in small and medium rivers. To reduce the costs of earth rock embankment inspections, avoid the need for human inspectors and enable the quick and widespread detection of piping hazards, a UAV image-acquisition function was introduced in this study. Through the collection and analysis of thermal infrared and visible (TIR & V) images from several piping field simulation experiments, temperature increases, and diffusion centered on the piping point were discovered, so an automatic algorithm for piping identification was developed to capture this phenomenon. To verify the identification capabilities, the automatic identification algorithm was applied to detect potential piping hazards during the 2022 flooding of the Dingjialiu River, Liaoning, China. The algorithm successfully identified all five piping hazard locations, demonstrating its potential for detecting embankment piping.

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Section: Registration and Automatic Identificationsmentioning

confidence: 99%

Automatic Identification of Earth Rock Embankment Piping Hazards in Small and Medium Rivers Based on UAV Thermal Infrared and Visible Images

Li,

Wang,

Sun

et al. 2023

Remote Sensing

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“…The number of 1 represents the Hamming distance between two strings. The calculation formula is shown in Equation (10).…”

Section: Matching Of Feature Point Descriptorsmentioning

confidence: 99%

“…Among them, the SURF algorithm is an improved version of the SIFT (Scale Invariant Features Transform) algorithm; it has a better registration effect and improves the detection speed of feature points [8,9]. However, when processing largescale remote sensing images, its calculation time can reach the order of minutes, so reducing the calculation requirements is a very urgent task in aerial image processing [10,11].…”

Section: Introductionmentioning

confidence: 99%

A Binary Fast Image Registration Method Based on Fusion Information

Liang,

Liu,

et al. 2023

Electronics

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In the field of airborne aerial imaging, image stitching is often used to expand the field of view. Registration is the foundation of aerial image stitching and directly affects its success and quality. This article develops a fast binary image registration method based on the characteristics of airborne aerial imaging. This method first integrates aircraft parameters and calculates the ground range of the image for coarse registration. Then, based on the characteristics of FAST (Features from Accelerated Segment Test), a new sampling method, named Weighted Angular Diffusion Radial Sampling (WADRS), and matching method are designed. The method proposed in this article can achieve fast registration while ensuring registration accuracy, with a running speed that is approximately four times faster than SURF (Speed Up Robust Features). Additionally, there is no need to manually select any control points before registration. The results indicate that the proposed method can effectively complete remote sensing image registration from different perspectives.

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UAV Cross-Modal Image Registration: Large-Scale Dataset and Transformer-Based Approach

Xiao,

Liu,

Zhu

et al. 2024

Lecture Notes in Computer Science

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A robust registration method for UAV thermal infrared and visible images taken by dual-cameras

Cited by 10 publications

References 62 publications

Automatic Identification of Earth Rock Embankment Piping Hazards in Small and Medium Rivers Based on UAV Thermal Infrared and Visible Images

Automatic Identification of Earth Rock Embankment Piping Hazards in Small and Medium Rivers Based on UAV Thermal Infrared and Visible Images

A Binary Fast Image Registration Method Based on Fusion Information

UAV Cross-Modal Image Registration: Large-Scale Dataset and Transformer-Based Approach

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