水下无人系统学报2025，Vol.33Issue(1)：84-91,8.DOI:10.11993/j.issn.2096-3920.2024-0066
基于结构张量的图像融合方法在海上探测的应用
Application of Structure Tensor-Based Image Fusion Method in Marine Exploration
马晓熠 1陈奕宏 2王飞 1谢硕1
作者信息
- 1. 中国船舶科学研究中心,江苏无锡,214026||深海技术科学太湖实验室,江苏无锡,214026
- 2. 中国船舶科学研究中心,江苏无锡,214026||深海技术科学太湖实验室,江苏无锡,214026||浙江大学航天航空学院,浙江杭州,310058
- 折叠
摘要
Abstract
A single sensor is insufficient for effective marine detection.Infrared light and visible light have strong complementarity,and fusing them can generate high-quality images that enable more accurate and comprehensive detection of marine targets.However,existing fusion methods have not been applied in marine detection and are not specifically developed for it,leading to poor fusion results.Additionally,there is a lack of deep learning datasets tailored for marine image fusion.To obtain high-quality color fusion images with a prominent performance in detecting targets and obtaining comprehensive information,the deep learning-based image fusion method using structure tensors was optimized based on the characteristics of marine targets.Multi-scale convolution was incorporated,and image fusion was performed according to channels.The collected data were used for comparative simulation experiments,with a variety of evaluation metrics applied.The results indicate that the improved image fusion method outperforms the original algorithm in six metrics,and its overall performance is better than the other ten commonly used image fusion algorithms.Furthermore,its generalization has been validated on other public datasets.The improved structure tensor-based image fusion method has an excellent performance in maritime situational awareness,with fusion results highlighting target features and surpassing the performance of other methods.关键词
海上探测/图像融合/深度学习/结构张量Key words
marine exploration/image fusion/deep learning/structure tensor分类
军事科技引用本文复制引用
马晓熠,陈奕宏,王飞,谢硕..基于结构张量的图像融合方法在海上探测的应用[J].水下无人系统学报,2025,33(1):84-91,8.
