基于改进曲率尺度空间算法的电力设备红外与可见光图像配准  

Registration Method for Power Equipment Infrared and Visible Images Based on Improved Curvature Scale Space Algorithm

作　　者：李云红[1] 罗雪敏 苏雪平 朱耀麟[1] 姚兰 段姣姣 Li Yunhong;Luo Xuemin;Su Xueping;Zhu Yaolin;Yao Lan;Duan Jiaojiao(School of Electronics and Information,Xi’an Polytechnic University,Xi’an 710048,Shaanxi,China)

机构地区：[1]西安工程大学电子信息学院,陕西西安710048

出　　处：《激光与光电子学进展》2022年第12期128-135,共8页Laser & Optoelectronics Progress

基　　金：陕西省科技厅青年科学基金(2019JQ-255);陕西省科技厅自然科学基础研究重点项目(2022JZ-35);国家级大学生创新创业训练计划项目(202110709002)。

摘　　要：针对现有电力设备红外与可见光图像配准难度大、配准时间长等问题,提出一种改进曲率尺度空间(CSS)算法的电力设备红外与可见光图像配准方法。首先引入Freeman链码差提高CSS算法的特征点提取精度,其次为每个特征点分配点到弦的垂直距离特征主方向,采用加速稳健特征变换(SURF)算法获得特征描述算子,最后利用双边快速近似最近邻(FLANN)搜索匹配方法和随机抽样一致(RANSAC)方法得到正确的匹配点对,获得仿射变换模型参数。实验结果表明:改进CSS图像配准方法与SURF、尺度不变特征变换(SIFT)、CSS配准方法相比性能指标均有显著提升,平均均方根误差(RMSE)较其他3种算法分别降低了77.73%、80.32%、7.63%;平均匹配时间分别降低了30.82%、40.12%、10.57%,提高了电力设备红外与可见光图像配准的效率。Aiming at the problems of difficult registration and long registration time of existing power equipment infrared and visible images, a registration method for power equipment infrared and visible images based on improved curvature scale space(CSS) algorithm is proposed. Firstly, the Freeman chain code difference is introduced to improve the feature point extraction accuracy of the CSS algorithm;Secondly, each feature point is assigned the main direction of the vertical distance from the point to the string, and the feature description operator is obtained using the speed up robust features(SURF) algorithm;Finally, the two-sided fast library for approximate nearest neighbors(FLANN) search matching and random sample consensus(RANSAC) method are used to obtain the correct matching point pair, and the affine transformation model parameters are obtained. The experimental results show that compared with the SURF, scale invariant feature transform(SIFT), and CSS registration methods, the improved CSS image registration method has significantly improved performance indicators and its average root mean square error(RMSE) is reduced by 77. 73%, 80. 32% and 7. 63% and its average matching time is reduced by 30. 82%, 40. 12% and 10. 57%, respectively. It improves the registration efficiency of the power equipment infrared and visible images.

关 键 词：图像处理 图像匹配 电力设备 红外与可见光图像 FREEMAN链码 双边快速近似最近邻搜索匹配 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]