TY - JOUR
T1 - Improvement of visibility under foggy conditions
AU - Andrade, Juan
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/10
Y1 - 2017/10
N2 - Light scattering produced for bad weather conditions produces outdoor images with poor contrast and faded colors, these effects can be critical in applications such as video surveillance, driving assistance or autonomous navigation. This article introduces a novel algorithm to restore the contrast of images under adverse weather conditions e.g.; fog, mist or haze. The proposed method combines several techniques in order to provide a fast algorithm able to work with color as well as gray images. Although other deweathering methods require multiple images of the scene or information about the weather conditions or the scene structure the proposed method only requires a single image of the foggy scene and assumes heterogeneous atmospheric conditions which is a common feature in images affected for weather conditions. Experiment results on real-world datasets validate the effectiveness of the proposed method.
AB - Light scattering produced for bad weather conditions produces outdoor images with poor contrast and faded colors, these effects can be critical in applications such as video surveillance, driving assistance or autonomous navigation. This article introduces a novel algorithm to restore the contrast of images under adverse weather conditions e.g.; fog, mist or haze. The proposed method combines several techniques in order to provide a fast algorithm able to work with color as well as gray images. Although other deweathering methods require multiple images of the scene or information about the weather conditions or the scene structure the proposed method only requires a single image of the foggy scene and assumes heterogeneous atmospheric conditions which is a common feature in images affected for weather conditions. Experiment results on real-world datasets validate the effectiveness of the proposed method.
KW - Dehaze
KW - black channel
KW - contrast enhancement
KW - depth estimation
KW - foggy images
UR - https://www.scopus.com/pages/publications/85032620049
U2 - 10.1109/TLA.2017.8071244
DO - 10.1109/TLA.2017.8071244
M3 - Artículo
AN - SCOPUS:85032620049
SN - 1548-0992
VL - 15
SP - 1983
EP - 1987
JO - IEEE Latin America Transactions
JF - IEEE Latin America Transactions
IS - 10
M1 - 8071244
ER -