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An Automatic Registration Algorithm of Infrared and Visible Images Based on Hybrid Image Features

机译:基于混合图像特征的红外可见图像自动配准算法

摘要

In this paper, a new method is presented to match a pair of visible and infrared images of same scene based on hybrid visual features including line segments and interest points. First, improved Harris corner extraction method and line segment detector method is used to extract feature points and segments .Then, a novel descriptor integrating the information of line segments and interest points is proposed. Finally, the nearest neighbor algorithm is utilized to match the descriptors, and the RANSAC(Random Sample Consensus) algorithm is employed to rule out the wrong match pairs.The performances are evaluated by extensive experiments on real images. The results show that the proposed algorithm can take advantage of similar structures between the multimodal images to realize automatic matching efficiently.
机译:本文提出了一种基于混合视觉特征(包括线段和兴趣点)来匹配同一场景的一对可见和红外图像的新方法。首先,使用改进的哈里斯角点提取方法和线段检测器方法提取特征点和线段,然后提出一种融合线段和兴趣点信息的新型描述符。最后,利用最近邻算法对描述符进行匹配,并采用RANSAC(Random Sample Consensus)算法排除错误的匹配对。通过对真实图像的大量实验对性能进行了评估。结果表明,该算法可以利用多峰图像之间的相似结构,有效地实现自动匹配。

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