Computer Engineering and Applications ›› 2023, Vol. 59 ›› Issue (5): 14-27.DOI: 10.3778/j.issn.1002-8331.2208-0313

• Research Hotspots and Reviews • Previous Articles     Next Articles

Overview of Research on Spatial Registration Algorithms of Underwater Opti-Acoustic Images

GUO Yinjing, MA Xinrui, XU Yuecheng, KONG Fang, LYU Wenhong   

  1. 1.College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, China
    2.Qingdao Intelligence Ocean Technology Co., Ltd., Qingdao, Shandong 266590, China
    3.College of Transportation, Shandong University of Science and Technology, Qingdao, Shandong 266590, China
  • Online:2023-03-01 Published:2023-03-01

水下光声图像空间配准算法研究综述

郭银景,马新瑞,许越铖,孔芳,吕文红   

  1. 1.山东科技大学 电子信息工程学院,山东 青岛 266590
    2.青岛智海牧洋有限公司,山东 青岛 266590
    3.山东科技大学 交通学院,山东 青岛 266590

Abstract: Underwater opti-acoustic image alignment is a key technology for information fusion in underwater devices. Based on a brief description of the concept and examples of underwater opti-acoustic image alignment, the current relevant algorithms for underwater opti-acoustic image reconstruction and recovery are analysed, the research progress of region and feature-based alignment algorithms for underwater heterogenous images are reviewed in detail, the development status of two research directions with high accuracy based on the similarity of image domain and shape features is focused on, and according to the research hotspots of heterogenous images alignment in other fields. The development trend of underwater opti-acoustic image alignment research is foreseen in terms of increasing structural constraints on imaging models, introducing phase congruency, generative adversarial networks and other algorithms to improve the alignment accuracy.

Key words: underwater opti-acoustic images, image registration, image processing, feature detection, machine vision

摘要: 水下光声图像配准是水下设备实现信息融合的关键技术。在简述了水下光声图像配准的概念及实例的基础上,分析了目前水下光声图像重建与复原的相关算法,详细综述了水下异源图像基于区域和特征的配准算法研究进展,重点论述了基于图像域和形状特征相似度的两个准确度较高的研究方向的发展现状,并根据其他领域的异源图像配准的研究热点,从增加成像模型的结构性约束、引入相位一致性和生成对抗网络等算法提高配准精度,展望了水下声光图像配准研究的发展趋势。

关键词: 水下声光图像, 图像配准, 图像处理, 特征提取, 机器视觉