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Multi-Modal Image Registration Based on Local Self-Similarity and Bidirectional Matching

机译:基于本地自相似性和双向匹配的多模态图像配准

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摘要

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.
机译:红外传感器和可见光颜色传感器的图像配准是一个非常困难的问题,因为它们的现象不同。本文提出了一种新的可见光和红外图像配准方法。建议的方法包括三个主要步骤。第一步,采用SURF算法进行局部特征提取。在第二步中,为每个提取的特征计算LSS(局部自相似描述符)。最后,在投影变换模型中执行交叉匹配过程,然后进行一致性检查,以实现特征对应和不匹配消除。实验结果表明,与现有方法相比,该方法在可见光和红外图像配准方面取得了更好的精度。

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