Fusing infrared and visible images taken by an unmanned aerial vehicle (UAV) is a challenging task, since infrared images distinguish the target from the background by the difference in infrared radiation, while the low resolution also produces a less pronounced effect. Conversely, the visible light spectrum has a high spatial resolution and rich texture; however, it is easily affected by harsh weather conditions like low light. Therefore, the fusion of infrared and visible light has the potential to provide complementary advantages. In this paper, we propose a multi-scale dense feature-aware network via integrated attention for infrared and visible image fusion, namely DFA-Net. Firstly, we construct a dual-channel encoder to extract the deep features of infrared and visible images. Secondly, we adopt a nested decoder to adequately integrate the features of various scales of the encoder so as to realize the multi-scale feature representation of visible image detail texture and infrared image salient target. Then, we present a feature-aware network via integrated attention to further fuse the feature information of different scales, which can focus on specific advantage features of infrared and visible images. Finally, we use unsupervised gradient estimation and intensity loss to learn significant fusion features of infrared and visible images. In addition, our proposed DFA-Net approach addresses the challenges of fusing infrared and visible images captured by a UAV. The results show that DFA-Net achieved excellent image fusion performance in nine quantitative evaluation indexes under a low-light environment.


    Access

    Download


    Export, share and cite



    Title :

    DFA-Net: Multi-Scale Dense Feature-Aware Network via Integrated Attention for Unmanned Aerial Vehicle Infrared and Visible Image Fusion


    Contributors:
    Sen Shen (author) / Di Li (author) / Liye Mei (author) / Chuan Xu (author) / Zhaoyi Ye (author) / Qi Zhang (author) / Bo Hong (author) / Wei Yang (author) / Ying Wang (author)


    Publication date :

    2023




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Unmanned aerial vehicle infrared visible light camera mount and unmanned aerial vehicle

    LI YONG / YANG JI / PAN YIFENG et al. | European Patent Office | 2021

    Free access

    Infrared camera module device for unmanned aerial vehicle image recognition and unmanned aerial vehicle

    ZHANG YANG / ZHOU CHAO / LI DANDAN et al. | European Patent Office | 2024

    Free access

    Integrated unmanned aerial vehicle wing rotating mechanism and integrated unmanned aerial vehicle

    WANG YANWEI / YANG LIGONG / WEN XI et al. | European Patent Office | 2024

    Free access

    SiamMAN: Siamese Multi-Phase Aware Network for Real-Time Unmanned Aerial Vehicle Tracking

    Faxue Liu / Xuan Wang / Qiqi Chen et al. | DOAJ | 2023

    Free access

    Unmanned aerial vehicle with infrared thermal imaging function and unmanned aerial vehicle system

    YAN ZHAO / FAN JIANGCHUAN | European Patent Office | 2022

    Free access