Research Status and Prospect of Night Image Dehazing Algorithm

被引:0
|
作者
Liu Xia [1 ,2 ]
Hou Changlun [1 ,2 ]
机构
[1] Hangzhou Dianzi Univ, Sch Elect & Informat, Hangzhou 310018, Zhejiang, Peoples R China
[2] Hangzhou Dianzi Univ, Inst Carbon Neutral & New Energy, Hangzhou 310018, Zhejiang, Peoples R China
关键词
image dehazing; deep learning; atmospheric scattering model; physical model; non-physical model; COLOR TRANSFER;
D O I
10.3788/LOP230991
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Night image dehazing technology has become an important research content in the field of image processing technology. It has important significance for target tracking detection, video surveillance, remote sensing and so on. Haze images at night usually have the characteristics of low contrast, uneven illumination, color offset, etc., which makes haze removal for night images face great challenges. Through summarizing the research status of night image de-fogging algorithms at home and abroad in recent years, the classical algorithms from the perspective of the physical model, non-physical model and deep learning are summarized, and the algorithm process, advantages and disadvantages are elaborated. Finally, the future research direction of the night fog removal algorithm is prospected.
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页数:8
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