Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-06-19 Cooperative journals: 《计算机应用研究》
Abstract： To improve the robustness of the existing multi-spectral image registration algorithms, this paper proposed a new algorithm based on multi-scale support region descriptors. Firstly, the algorithm extracted the Harris corner points as feature points. Secondly, it constructed the descriptor by combining the edge direction histograms calculated respectively in the support regions of different sizes around a feature point. Then, the similarity criterion was the Euclidean distance, and it obtained the initial matches by the ratio method. Finally, this paper proposed an outlier removal algorithm based on RANSAC algorithm. The experimental results show that the proposed algorithm can match multi-spectral images effectively, be more robust than the existing algorithms, and obtain more matches that are correct.
Subjects: Physics >> Electromagnetism, Optics, Acoustics, Heat Transfer, Classical Mechanics, and Fluid Dynamics Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science Subjects: Mathematics >> Mathematics （General） submitted time 2017-11-26
Abstract： The infrared imaging grayscale variation caused by the influence of atmosphere on infrared radiation transmission is a problem that infrared target tracking application needs to cope with. The object of this paper is to model the law of infrared imaging grayscale variation in Lie group, which is important to design an efficient and robust target tracking algorithm. This paper firstly analyzes the infrared radiation transmission model, and then derives the brightness model of infrared imaging by considering the mechanism of infrared imaging. Furthermore, it is theoretically proved that the infrared imaging grayscale variation caused by the atmosphere obeys to the Lie group structure, and a non-Euclidean mathematical representation of the infrared imaging grayscale variation is proposed. Finally, according to the infrared imaging grayscale variation model, the field experimental data collected under different environments are fitted, and the regression analysis results demonstrate the correctness of the model, which validates the rationality of the Lie group representation of the infrared imaging grayscale variation.
Peer Review Status:
Awaiting Review
Hits
Hits
Downloads
Comment