Abstract. Image registration is an essential prerequisite for multisource image fusion. To further improve the registration accuracy for long-wave infrared and visible images, a feature point descriptor construction method—edge-oriented log-Gabor descriptor is proposed. Initially, grayscale edge images are obtained by a structured random forests edge detector, which is more suitable for extracting features using multiscale and multioriented log-Gabor filters. Then, edge features are used for selecting orientation-stabilized feature points from speeded up robust feature points, and descriptors are constructed with a two-stage Gaussian weighting scheme. Finally, feature point pairs are matched by computing the difference of descriptors. Experimental results show that the proposed approach achieves better performance compared with state-of-the-art methods.

中文翻译：

---

EOLGD：一种基于边缘特征描述符的长波红外和可见光图像配准方法

摘要。图像配准是多源图像融合的必要前提。为了进一步提高长波红外和可见光图像的配准精度，提出了一种特征点描述符构建方法——面向边缘的log-Gabor描述符。最初，灰度边缘图像是通过结构化的随机森林边缘检测器获得的，它更适合使用多尺度和多方向的 log-Gabor 滤波器提取特征。然后，边缘特征用于从加速鲁棒特征点中选择方向稳定的特征点，并使用两阶段高斯加权方案构建描述符。最后，通过计算描述符的差异来匹配特征点对。