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人工光源条件下夜间雾天图像建模及去雾

杨爱萍 王南 庞彦伟 杨苏辉

杨爱萍, 王南, 庞彦伟, 杨苏辉. 人工光源条件下夜间雾天图像建模及去雾[J]. 电子与信息学报, 2018, 40(6): 1330-1337. doi: 10.11999/JEIT170704
引用本文: 杨爱萍, 王南, 庞彦伟, 杨苏辉. 人工光源条件下夜间雾天图像建模及去雾[J]. 电子与信息学报, 2018, 40(6): 1330-1337. doi: 10.11999/JEIT170704
YANG Aiping, WANG Nan, PANG Yanwei, YANG Suhui. Nighttime Haze Removal Based on New Imaging Model with Artificial Light Sources[J]. Journal of Electronics & Information Technology, 2018, 40(6): 1330-1337. doi: 10.11999/JEIT170704
Citation: YANG Aiping, WANG Nan, PANG Yanwei, YANG Suhui. Nighttime Haze Removal Based on New Imaging Model with Artificial Light Sources[J]. Journal of Electronics & Information Technology, 2018, 40(6): 1330-1337. doi: 10.11999/JEIT170704

人工光源条件下夜间雾天图像建模及去雾

doi: 10.11999/JEIT170704
基金项目: 

国家自然科学基金(61372145, 61472274, 61632081)

Nighttime Haze Removal Based on New Imaging Model with Artificial Light Sources

Funds: 

The National Natural Science Foundation of china (61372145, 61472274, 61632081)

  • 摘要: 夜间有雾图像光照不均匀,整体亮度较低,色偏严重,且人工光源周围存在光晕。现有的去雾模型和算法大多针对白天图像,其并不适用于夜间场景,夜间图像去雾颇具挑战性。该文深入分析夜间有雾图像的成像规律,建立含有人工光源的夜间雾天图像成像新模型,并在此基础上提出夜间图像去雾新算法。针对夜间图像光照不均问题,提出基于低通滤波的环境光估计方法,利用估计出的环境光可准确预测夜间场景传输率;针对目前夜间图像去雾后存在光源光晕问题,提出根据图像色度估计场景点属于近光源区域的程度,使算法能自适应地处理光源区域和非光源区域;针对非一致色偏问题,利用直方图匹配方法进行颜色校正。对大量图像进行实验,并与现有白天、夜晚图像去雾算法进行比较,验证了该文提出的夜间雾天图像成像模型及去雾算法的有效性。
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出版历程
  • 收稿日期:  2017-07-17
  • 修回日期:  2018-03-07
  • 刊出日期:  2018-06-19

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