Variational Single Nighttime Image Haze Removal with a Gray Haze-Line Prior

2022 ◽  
pp. 1-1
Author(s):  
Wenhui Wang ◽  
Anna Wang ◽  
Chen Liu
Keyword(s):  
Haze Removal ◽  
Nighttime Image

Fast Haze Removal for Nighttime Image Using Maximum Reflectance Prior

2017 ◽  
Author(s):  
Jing Zhang ◽  
Yang Cao ◽  
Shuai Fang ◽  
Yu Kang ◽  
Chang Wen Chen
Keyword(s):  
Haze Removal ◽  
Nighttime Image

Lighting model construction and haze removal for nighttime image

2017 ◽  
Vol 25 (3) ◽  
pp. 729-734 ◽  
Author(s):  
余顺园 YU Shun-yuan ◽  
朱 虹 ZHU Hong
Keyword(s):  
Model Construction ◽  
Haze Removal ◽  
Nighttime Image

Superpixel-Based Single Nighttime Image Haze Removal

2018 ◽  
Vol 20 (11) ◽  
pp. 3008-3018 ◽  
Author(s):  
Minmin Yang ◽  
Jianchang Liu ◽  
Zhengguo Li
Keyword(s):  
Haze Removal ◽  
Nighttime Image

Single nighttime image dehazing based on image decomposition

2021 ◽  
Vol 183 ◽  
pp. 107986
Author(s):  
Yun Liu ◽  
Anzhi Wang ◽  
Hao Zhou ◽  
Pengfei Jia
Keyword(s):  
Image Decomposition ◽  
Image Dehazing ◽  
Nighttime Image

From Coarse to Fine: A Two-Stage Network for Dense Haze removal

2020 ◽  
Author(s):  
Tian Pan ◽  
Yueting Chen ◽  
Huajun Feng ◽  
Zhihai Xu ◽  
Qi Li ◽  
...  
Keyword(s):  
Two Stage ◽  
Haze Removal ◽  
Coarse To Fine

scholarly journals Single image haze removal considering sensor blur and noise

2013 ◽  
Vol 2013 (1) ◽  
Author(s):  
Xia Lan ◽  
Liangpei Zhang ◽  
Huanfeng Shen ◽  
Qiangqiang Yuan ◽  
Huifang Li
Keyword(s):  
Single Image ◽  
Haze Removal

scholarly journals A Review of Remote Sensing Image Dehazing

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3926
Author(s):  
Juping Liu ◽  
Shiju Wang ◽  
Xin Wang ◽  
Mingye Ju ◽  
Dengyin Zhang
Keyword(s):  
Remote Sensing ◽  
Data Driven ◽  
Future Research ◽  
Research Focus ◽  
Image Dehazing ◽  
Surface Information ◽  
Haze Removal ◽  
Advantages And Disadvantages ◽  
Extra Information ◽  
Removal Technique

Remote sensing (RS) is one of the data collection technologies that help explore more earth surface information. However, RS data captured by satellite are susceptible to particles suspended during the imaging process, especially for data with visible light band. To make up for such deficiency, numerous dehazing work and efforts have been made recently, whose strategy is to directly restore single hazy data without the need for using any extra information. In this paper, we first classify the current available algorithm into three categories, i.e., image enhancement, physical dehazing, and data-driven. The advantages and disadvantages of each type of algorithm are then summarized in detail. Finally, the evaluation indicators used to rank the recovery performance and the application scenario of the RS data haze removal technique are discussed, respectively. In addition, some common deficiencies of current available methods and future research focus are elaborated.

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