Infrared and visible image fusion technology aims to integrate the radiation information of infrared images and the details of visible images into one image, which is widely used in video surveillance, target tracking etc.. Thereinto, maritime surveillance often uses infrared and visible images to monitor ships. With the rapid development of deep learning technology, numerous image fusion algorithms have sprung up. However, maritime images can be affected by extreme illumination conditions during fused. Note that the quality of maritime images is extremely significant for identifying ship targets. Therefore, the quality of fused image is necessary for further investigation. Here, a progressive image fusion network with a lighting awareness module, named PIAFusion, is provided for maritime images fusion. Contributed by the light sensing subnetwork, PIAFusion can adaptively fuse the common information and complementary information of images. Evaluated with five operators in daytime and night cases, the results demonstrate that this method significantly improve the fused image quality, compared to common fusion methods (i.e., GTF and DenseFuse). In addition, this method preserves more details of the source image. The progressive fusion network illustrates better fusion performance for maritime images in different lighting cases.


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    Title :

    Infrared and visible maritime image fusion based on PIAFusion


    Contributors:
    Yang, Yue (editor) / Ni, Qian (author) / Cao, Chunyan (author) / Zhu, Hongna (author) / Wu, Yanqun (author) / Sui, Hao (author) / Ou, Mingyu (author) / Shi, Kequan (author) / Li, Qi (author)

    Conference:

    Fourteenth International Conference on Information Optics and Photonics (CIOP 2023) ; 2023 ; Xi’an, China


    Published in:

    Proc. SPIE ; 12935 ; 129350Q


    Publication date :

    2023-11-24





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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