摘要
多模态图像配准能提供比单模态图像配准更加丰富和全面的信息,红外与可见光图像配准作为一种常见的多模态配准类型,在电力、遥感、军事以及人脸识别等领域具有重要的应用价值。首先介绍了红外与可见光图像配准的相关技术并阐述了配准中存在的难点与挑战,然后详细分析和总结了基于区域、基于特征和基于深度学习3种红外与可见光图像配准方法,并分别阐述了不同配准方法的优缺点,之后概述了红外与可见光图像配准技术的实际应用,最后对红外与可见光图像配准未来的发展趋势进行讨论。
Multi-modal image registration can provide richer and more comprehensive information than single-modal image registration. Among them, infrared and visible image registration, which is a common multi-modal form of registration, has important application value in fields such as electric power, remote sensing, military, and face recognition. In this paper, the correlation technique of infrared and visible image registration is introduced, and the existing difficulties and challenges involved in registration are analyzed.Subsequently, the advantages and disadvantages of different registration methods are evaluated in detail the three types based on area, feature, and deep learning, and a practical application of infrared and visible image registration technology is presented. Finally, the future development trend of infrared and visible image registration is discussed.
作者
李云红
刘宇栋
苏雪平
罗雪敏
姚兰
LI Yunhong;LIU Yudong;SU Xueping;LUO Xuemin;YAO Lan(School of Electronics and Information,Xi’an Polytechnic University,Xi’an 710048,China)
出处
《红外技术》
CSCD
北大核心
2022年第7期641-651,共11页
Infrared Technology
基金
国家自然科学基金(61902301)
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(S202110709002)。
关键词
图像配准
红外图像
可见光图像
深度学习
image registration
infrared image
visible image
deep learning