| Abstrakt: |
Haze is a local weather phenomenon in which very small droplets float in the atmosphere, and the amount and characteristics of haze may vary depending on the region. In particular, these haze reduce visibility, which can cause air traffic interference and vehicle traffic accidents, and degrade the quality of security CCTVs and so on. Therefore, in the past 10 years, research on haze removal has been actively conducted to reduce damage caused by haze. In this study, local haze removal is performed by weight generation using a haziness degree evaluator to adaptively respond to haze-free, homogeneous haze, and non-homogeneous haze cases. And the proposed method improves the limitations of the existing static haze removal method, which assumes that there is haze in the input image and removes the haze. We also demonstrate the superiority of the proposed method through quantitative and qualitative performance evaluations with benchmark algorithms. [ABSTRACT FROM AUTHOR] |
