TY - GEN
T1 - Local Color Mapping Combined with Color Transfer for Underwater Image Enhancement
AU - Protasiuk, Rafal
AU - Bibi, Adel
AU - Ghanem, Bernard
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was supported by the King Abdullah University of Science and Technology Office of Sponsored Research.
PY - 2019/3/8
Y1 - 2019/3/8
N2 - Color correction and color transfer methods have gained a lot of attention in the past few years to circumvent color degradation that may occur due to various sources. In this paper, we propose a novel simple yet powerful strategy to profoundly enhance color distorted underwater images. The proposed approach combines both local and global information through a simple yet powerful affine transform model. Local and global information are carried through local color mapping and color covariance mapping between an input and some reference source, respectively. Several experiments on degraded underwater images demonstrate that the proposed method performs favourably to all other methods including ones that are tailored to correcting underwater images by explicit noise modelling.
AB - Color correction and color transfer methods have gained a lot of attention in the past few years to circumvent color degradation that may occur due to various sources. In this paper, we propose a novel simple yet powerful strategy to profoundly enhance color distorted underwater images. The proposed approach combines both local and global information through a simple yet powerful affine transform model. Local and global information are carried through local color mapping and color covariance mapping between an input and some reference source, respectively. Several experiments on degraded underwater images demonstrate that the proposed method performs favourably to all other methods including ones that are tailored to correcting underwater images by explicit noise modelling.
UR - http://hdl.handle.net/10754/631828
UR - https://ieeexplore.ieee.org/document/8659313
UR - http://www.scopus.com/inward/record.url?scp=85063596283&partnerID=8YFLogxK
U2 - 10.1109/WACV.2019.00157
DO - 10.1109/WACV.2019.00157
M3 - Conference contribution
SN - 9781728119755
SP - 1433
EP - 1439
BT - 2019 IEEE Winter Conference on Applications of Computer Vision (WACV)
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -