RI-MFM: A Novel Infrared and Visible Image Registration with Rotation Invariance and Multilevel Feature Matching

In the past ten years, multimodal image registration technology has been continuously developed, and a large number of researchers have paid attention to the problem of infrared and visible image registration. Due to the differences in grayscale distribution, resolution and viewpoint between two ima...

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Bibliographic Details
Published inElectronics (Basel) Vol. 11; no. 18; p. 2866
Main Authors Zhu, Depeng, Zhan, Weida, Fu, Jingqi, Jiang, Yichun, Xu, Xiaoyu, Guo, Renzhong, Chen, Yu
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.09.2022
Subjects
Accuracy
Algorithms
Centroids
Consistency
Dimensional analysis
Image processing
Image registration
Infrared imagery
Infrared imaging
Invariance
Localization
Matching
Methods
Optimization
Radiation
Registration
Researchers
Robustness
Rotation
Similarity measures
China
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Summary:In the past ten years, multimodal image registration technology has been continuously developed, and a large number of researchers have paid attention to the problem of infrared and visible image registration. Due to the differences in grayscale distribution, resolution and viewpoint between two images, most of the existing infrared and visible image registration methods are still insufficient in accuracy. To solve such problems, we propose a new robust and accurate infrared and visible image registration method. For the purpose of generating more robust feature descriptors, we propose to generate feature descriptors using a concentric-circle-based feature-description algorithm. The method enhances the description of the main direction of feature points by introducing centroids, and, at the same time, uses concentric circles to ensure the rotation invariance of feature descriptors. To match feature points quickly and accurately, we propose a multi-level feature-matching algorithm using improved offset consistency for matching feature points. We redesigned the matching algorithm based on the offset consistency principle. The comparison experiments with several other state-of-the-art registration methods in CVC and homemade datasets show that our proposed method has significant advantages in both feature-point localization accuracy and correct matching rate.
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics11182866