Deep Video Dehazing with Semantic Segmentation

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 先进时空数据分析与学习

	Deep Video Dehazing with Semantic Segmentation
	Wenqi REN; Jingang ZHANG; Xiangyu XU; Lin MA; Xiaocun CAO; Gaofeng MENG; Wei LIU
发表期刊	IEEE TRANSACTIONS ON IMAGE PROCESSING
	2018
卷号	99 期号:99 页码:1-13
摘要	Recent research have shown the potential of using feed-forward convolutional neural networks to accomplish single image dehazing. In this work, we take one step further to explore the possibility of exploiting a feed-forward network to perform haze removal for videos. Unlike single image dehazing, video based approaches can take advantage of the abundant information that exists across neighboring frames. In this work, assuming that a scene point yields highly correlated transmission values between adjacent video frames, we develop a deep learning solution for video dehazing, where a CNN is trained end-toend to learn how to accumulate information across frames for transmission estimation. The estimated transmission map is subsequently used to recover a haze-free frame via atmospheric scattering model. In addition, as the semantic information of a scene provides a strong prior for image restoration, we propose to incorporate global semantic priors as input to regularize the transmission maps so that the estimated maps can be smooth in the regions of the same object and only discontinuous across the boundaries of different objects. To train this network, we generate a dataset consisted of synthetic hazy and haze-free videos for supervision based on the NYU depth dataset. We show that the features learned from this dataset are capable of removing haze that arises in outdoor scenes in a wide range of videos. Extensive experiments demonstrate that the proposed algorithm performs favorably against the state-of-theart methods on both synthetic and real-world videos.
关键词	Video Dehazing Defogging
WOS记录号	WOS:000453552100001
引用统计	被引频次：123[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/21761
专题	多模态人工智能系统全国重点实验室_先进时空数据分析与学习
推荐引用方式 GB/T 7714	Wenqi REN,Jingang ZHANG,Xiangyu XU,et al. Deep Video Dehazing with Semantic Segmentation[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2018,99(99):1-13.
APA	Wenqi REN.,Jingang ZHANG.,Xiangyu XU.,Lin MA.,Xiaocun CAO.,...&Wei LIU.(2018).Deep Video Dehazing with Semantic Segmentation.IEEE TRANSACTIONS ON IMAGE PROCESSING,99(99),1-13.
MLA	Wenqi REN,et al."Deep Video Dehazing with Semantic Segmentation".IEEE TRANSACTIONS ON IMAGE PROCESSING 99.99(2018):1-13.

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