TY - GEN
T1 - Haze removal Methods
T2 - 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018
AU - Reda, Mohamed
AU - Zhao, Yongqiang
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8
Y1 - 2018/8
N2 - Outdoor scenes are usually affected by air particles and water vapor in the atmosphere. Haze is such phenomena happened due to atmospheric absorption and scattering. Haze affects the visibility and causes a degradation in the images quality of outdoor scenes, which in turn affects various image processing applications. In this paper, a review of the recent haze removal methods and its applications is introduced. The haze removal methods are categorized according to the input of their algorithm into two categories: multiple images and single image. Afterward, the different strategies in each category of the haze removal techniques are discussed and their characteristics are illustrated. Eventually, the quantitative parameters that evaluate the quality of the haze removed image are presented. This review paper highlights the importance of the haze removal methods in restoring a high-quality image relative to the quality of the original haze-free image. This haze removed image is a vital key in many computer vision applications including the visual navigation and object recognition and target detection.
AB - Outdoor scenes are usually affected by air particles and water vapor in the atmosphere. Haze is such phenomena happened due to atmospheric absorption and scattering. Haze affects the visibility and causes a degradation in the images quality of outdoor scenes, which in turn affects various image processing applications. In this paper, a review of the recent haze removal methods and its applications is introduced. The haze removal methods are categorized according to the input of their algorithm into two categories: multiple images and single image. Afterward, the different strategies in each category of the haze removal techniques are discussed and their characteristics are illustrated. Eventually, the quantitative parameters that evaluate the quality of the haze removed image are presented. This review paper highlights the importance of the haze removal methods in restoring a high-quality image relative to the quality of the original haze-free image. This haze removed image is a vital key in many computer vision applications including the visual navigation and object recognition and target detection.
UR - https://www.scopus.com/pages/publications/85082487060
U2 - 10.1109/GNCC42960.2018.9018690
DO - 10.1109/GNCC42960.2018.9018690
M3 - 会议稿件
AN - SCOPUS:85082487060
T3 - 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018
BT - 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 10 August 2018 through 12 August 2018
ER -