Underwater Image Restoration using Deep Networks to Estimate Background Light and Scene Depth
- Resource Type
- Conference
- Authors
- Cao, Keming; Peng, Yan-Tsung; Cosman, Pamela C.
- Source
- 2018 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) Image Analysis and Interpretation (SSIAI), 2018 IEEE Southwest Symposium on. :1-4 Apr, 2018
- Subject
- Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Image restoration
Estimation
Training
Network architecture
Image color analysis
Cameras
Attenuation
Underwater images
image restoration
depth estimation
convolutional neural networks
- Language
- ISSN
- 2473-3598
Images taken underwater often suffer color distortion and low contrast because of light scattering and absorption. An underwater image can be modeled as a blend of a clear image and a background light, with the relative amounts of each determined by the depth from the camera. In this paper, we propose two neural network structures to estimate background light and scene depth, to restore underwater images. Experimental results on synthetic and real underwater images demonstrate the effectiveness of the proposed method.