To solve the problem of poor sample diversity of infrared ship image data, a method of infrared ship image data expansion is implemented based on CycleGAN. The method using the ideas of circulating, iterative approximation, there can be no noise of ship target infrared simulation image dataset maps to conform to the actual infrared detection scenario of ship target image dataset, according to the demand of the subsequent target detection identification, on the premise of the ship target itself form unchanged, injected with appropriate clutter interference, so as to realize the effective expansion of the image data, the method fully considers the target and background infrared characteristics, and are not influenced by whether the scale of the target alignment issues, which can effectively increase the image sample of diversification, for subsequent ship target detection identification algorithm, provides rich data support. The comparison experiment of image structure similarity and object detection accuracy verifies the effectiveness of the algorithm.


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    Title :

    Based on CycleGAN infrared ship image expansion method


    Contributors:
    Liu, Peijie (author) / Zhang, Yan (author) / Shi, Zhiguang (author) / Wei, Ming (author)

    Conference:

    2020 International Conference on Image, Video Processing and Artificial Intelligence ; 2020 ; Shanghai,China


    Published in:

    Proc. SPIE ; 11584


    Publication date :

    2020-11-10





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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