  In recent years, with the continuous development of the marine industry,
underwater image enhancement has attracted plenty of attention. Unfortunately,
the propagation of light in water will be absorbed by water bodies and
scattered by suspended particles, resulting in color deviation and low
contrast. To solve these two problems, we propose an Adaptive Transmission and
Dynamic Color guided network (named ATDCnet) for underwater image enhancement.
In particular, to exploit the knowledge of physics, we design an Adaptive
Transmission-directed Module (ATM) to better guide the network. To deal with
the color deviation problem, we design a Dynamic Color-guided Module (DCM) to
post-process the enhanced image color. Further, we design an
Encoder-Decoder-based Compensation (EDC) structure with attention and a
multi-stage feature fusion mechanism to perform color restoration and contrast
enhancement simultaneously. Extensive experiments demonstrate the
state-of-the-art performance of the ATDCnet on multiple benchmark datasets.

Computer Vision and Pattern Recognition;Image and Video Processing