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Alternative TitleReal-Time Video Dehazing Based on Absorption Transmission Compensation and Spatio-Temporal Guided Image Filtering
崔童1,2,3; 田建东1,2; 王强1,2,3; 任卫红1,2,3; 唐延东1,2; 崔童4,5,6; 田建东4,5; 王强4,5,6; 任卫红4,5,6; 唐延东4,5
Source Publication机器人
Indexed ByEI ; CSCD
EI Accession number20195207923164
Contribution Rank1
Funding Organization国家自然科学基金(91648118,61473280,61333019)
Keyword视频去雾 时空导向图像滤波 亮度饱和度比 吸收透射率补偿


Other Abstract

The difficulty of the video dehazing technology is to guarantee the spatial-temporal consistency of the video data. A spatio-temporal guided image filtering (ST-GIF) optimization algorithm is proposed to solve this problem. The spatial and temporal consistencies of the videos’ interframe information are taken into consideration in the algorithm. For one thing, the transmission texture is smoothed and the salient boundary is protected. And for another, the flicker noise in the videos are suppressed to ensure the fluency of the haze-free video. Since the classical dehazing model only concerns the influence of scattering on the fog formation, most of the dehazing algorithms based on this model usually generate over-saturated noise in the close shot. A transmission estimation algorithm based on absorption transmission compensation is proposed to solve this problem. This algorithm overcomes the defect that the classical model ignores atmospheric absorption attenuation, significantly improves the accuracy of transmission estimation, and effectively suppresses the over-saturations in the close shot. The proposed algorithm is experimentally compared with several state-of-the-art algorithms on both real-world and synthetic haze video data. The quantitative evaluation results with reference show that the proposed algorithm is at least 12% and 3.4% higher than the others in the two metrics of the signal-to-noise ratio and the structural similarity respectively. As an evaluation method without reference, the visible boundary restoration metric of the proposed algorithm is at least 5.7% higher than the others. Results demonstrate that the proposed real-time video dehazing algorithm can recover the high frequency information more effectively, and improve the image contrast more properly, and the colours of the obtained dehazing videos are more natural and authentic.

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Document Type期刊论文
Corresponding Author田建东; 田建东
Recommended Citation
GB/T 7714
崔童,田建东,王强,等. 基于吸收透射率补偿及时空导向图像滤波的实时视频去雾[J]. 机器人,2019,41(6):761-770.
APA 崔童.,田建东.,王强.,任卫红.,唐延东.,...&唐延东.(2019).基于吸收透射率补偿及时空导向图像滤波的实时视频去雾.机器人,41(6),761-770.
MLA 崔童,et al."基于吸收透射率补偿及时空导向图像滤波的实时视频去雾".机器人 41.6(2019):761-770.
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