Abstract

The registration of images from infrared sensors and visible color sensors is a quite difficult problem due to their different phenomena. In this paper, we propose a new method to register visible and infrared images. The proposed approach consists of three main steps. In the first step, SURF (Speeded-Up Robust Features) algorithm is applied for local feature extraction. In the second step, LSS (local self-similarity descriptor) is computed for each extracted feature. Finally, a cross matching process followed by a consistency check in the projective transformation model is performed for feature correspondence and mismatch elimination. Experimental results show the proposed method achieves better accuracy for registering visible and infrared images as compared to state-of-the-art approaches.

中文翻译：

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基于局部自相似和双向匹配的多模态图像配准

摘要

由于红外线传感器和可见光彩色传感器的图像现象不同，因此它们的配准是一个相当困难的问题。在本文中，我们提出了一种注册可见光和红外图像的新方法。提议的方法包括三个主要步骤。第一步，将SURF（加速鲁棒特征）算法应用于局部特征提取。在第二步中，为每个提取的特征计算LSS（局部自相似性描述符）。最后，执行交叉匹配过程，然后在投影变换模型中进行一致性检查，以进行特征对应和消除不匹配。实验结果表明，与最新技术相比，该方法在配准可见光图像和红外图像方面具有更高的精度。