TY - GEN
T1 - Study on Outdoor Fog Detection and Image Dehazing Algorithm
AU - Wang, Mingyuan
AU - Wang, Rui
AU - Wang, Chongwen
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/10/27
Y1 - 2023/10/27
N2 - This paper studies outdoor fog detection and image dehazing algorithms. Firstly, a random forest method is used to classify images into foggy or non-foggy based on the dark channel gray value distribution and saturation features of images. Then, an improved AOD-Net algorithm is used to remove haze from the foggy images. Finally, the effectiveness of the proposed methods is verified by experiments. Experimental results show that the random forest classifier based on the dark channel and saturation features can accurately detect foggy images, while the improved AOD-Net algorithm can effectively remove the haze in the images and improve their clarity and visibility. The proposed methods have practical value and can be widely used in aerial photography, security monitoring, and other fields.
AB - This paper studies outdoor fog detection and image dehazing algorithms. Firstly, a random forest method is used to classify images into foggy or non-foggy based on the dark channel gray value distribution and saturation features of images. Then, an improved AOD-Net algorithm is used to remove haze from the foggy images. Finally, the effectiveness of the proposed methods is verified by experiments. Experimental results show that the random forest classifier based on the dark channel and saturation features can accurately detect foggy images, while the improved AOD-Net algorithm can effectively remove the haze in the images and improve their clarity and visibility. The proposed methods have practical value and can be widely used in aerial photography, security monitoring, and other fields.
KW - AOD-Net
KW - Fog detection
KW - Image dehazing
KW - Random forest
UR - http://www.scopus.com/inward/record.url?scp=85196216468&partnerID=8YFLogxK
U2 - 10.1145/3653863.3653864
DO - 10.1145/3653863.3653864
M3 - Conference contribution
AN - SCOPUS:85196216468
T3 - ACM International Conference Proceeding Series
SP - 1
EP - 7
BT - 2023 6th International Conference on Sensors, Signal and Image Processing, SSIP 2023
PB - Association for Computing Machinery
T2 - 6th International Conference on Sensors, Signal and Image Processing, SSIP 2023
Y2 - 27 October 2023 through 29 October 2023
ER -