@article{Xu2023, 
author = {Xing-Gui Xu and Xiang-Suo Fan and Yong-Li Liu},
title = {Real-Time Underwater Image Enhancement Using Adaptive Full-Scale Retinex},
year = {2023},
journal = {Journal of Computer Science and Technology},
volume = {38},
number = {4},
pages = {885-898},
keywords = {underwater, image enhancement, Retinex, imaging through turbulent media},
url = {https://www.sciopen.com/article/10.1007/s11390-022-1115-z},
doi = {10.1007/s11390-022-1115-z},
abstract = {Current Retinex-based image enhancement methods with fixed scale filters cannot adapt to situations involving various depths of field and illuminations. In this paper, a simple but effective method based on adaptive full-scale Retinex (AFSR) is proposed to clarify underwater images or videos. First, we design an adaptive full-scale filter that is guided by the optical transmission rate to estimate illumination components. Then, to reduce the computational complexity, we develop a quantitative mapping method instead of non-linear log functions for directly calculating the reflection component. The proposed method is capable of real-time processing of underwater videos using temporal coherence and Fourier transformations. Compared with eight state-of-the-art clarification methods, our method yields comparable or better results for image contrast enhancement, color-cast correction and clarity.}
}