CNN-Enabled Visibility Enhancement Framework for Vessel Detection under Haze Environment
نویسندگان
چکیده
Maritime images captured under haze environment often have a terrible visual effect, making it easy to overlook important information. To avoid the failure of vessel detection caused by fog, is necessary preprocess collected hazy for recovering vital In this paper, novel CNN-enabled visibility dehazing framework proposed, consisting two subnetworks, that is, Coarse Feature Extraction Module (C-FEM) and Fine Fusion (F-FFM). Specifically, C-FEM multiscale feature extraction network, which can learn information from three scales. Correspondingly, F-FFM an improved encoder-decoder network fuse obtained enhance effect final output. Meanwhile, hybrid loss function designed monitoring output result simultaneously. It worth mentioning massive maritime are considered training dataset further adapt task environment. Comprehensive experiments on synthetic realistic verified superior effectiveness robustness our compared several state-of-the-art methods. Our method preprocesses before demonstrate has capacity promoting video surveillance.
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ژورنال
عنوان ژورنال: Journal of Advanced Transportation
سال: 2021
ISSN: ['0197-6729', '2042-3195']
DOI: https://doi.org/10.1155/2021/5598390