注意力机制下多尺度特征融合生成对抗的日间海雾识别  

Daytime Sea Fog Recognition based on Multi-scale Feature Fusion Generation under Attention Mechanism

作　　者：黄彦慧 符冉迪[1] 方旭源 尹曹谦[1] 李纲[1] 金炜[1] HUANG Yanhui;FU Randi;FANG Xuyuan;YIN Caoqian;LI Gang;JIN Wei(Faculty of Electrical Engineering and Computer Science,Ningbo University,Ningbo 351211,China)

机构地区：[1]宁波大学信息科学与工程学院,浙江宁波315211

出　　处：《遥感技术与应用》2025年第1期258-264,共7页Remote Sensing Technology and Application

基　　金：宁波市公益类科技计划项目(202002N3104);国家自然科学基金项目(42071323)。

摘　　要：为了提升海雾识别的准确性,在注意力机制下,采用多尺度特征融合生成对抗网络,提出了一种日间海雾识别方法。该方法首先利用条件生成对抗网络生成中红外通道的云图,以消除原始日间中红外通道云图的太阳辐射影响,从而可以综合利用可见光、远红外和中红外通道云图在海雾监测中各自的优势。基于此,在UNet网络中引入金字塔切分注意力机制以提高3个输入通道数据特征提取的性能;同时,在编解码器过渡层采用多尺度空洞空间卷积池化金字塔,通过对多个路径进行多尺度特征融合,以增强对不同尺度海雾识别的泛化能力;最后,引入判别网络对生成网络进行监督,实现对海雾边缘的精准界定。实验结果表明:该方法的海雾检测精度较传统方法有所提升,命中率(POD)达到94.16%,误报率(FAR)为11.61%,临界成功指数(CSI)为83.59%,为日间海雾识别提供了一种新思路。To improve the accuracy of sea fog recognition,a daytime sea fog recognition method is proposed by using a generative adversarial network with multi-scale feature fusion under the attention mechanism.The method first generated cloud images for the mid-infrared channel using a conditional generation adversarial network to eliminate the solar radiation effects of the original daytime mid-infrared channel cloud images,allowing the visible,far-infrared,and mid-infrared channel cloud images to be comprehensively utilized for sea fog monitoring.On these grounds,the pyramid split attention mechanism was introduced into the UNet network to improve the performance of data feature extraction for the three input channels.At the same time,multi-scale atrous spatial pyramid pooling was used in the transition layer of the codec to enhance the generalization ability of sea fog recognition at different scales by multi-scale feature fusion of multiple paths.Finally,the discriminant network was introduced to supervise the generation network to achieve an accurate definition of the edge of sea fog.The experimental results show that the accuracy of sea fog detection in this method is improved compared with the traditional method,the Probability Of Detection(POD)reaches 94.16%,the False Alarm Ratio(FAR)is 11.61%,and the Critical Success Index(CSI)is 83.59%,which provides a new idea for daytime sea fog recognition.

关 键 词：葵花8号卫星 注意力机制 多尺度 日间海雾识别 生成对抗网络 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]