AOD-Net: All-in-One Dehazing Network
Wuhan National Laboratory for Optoelectronics · Huazhong University of Science and Technology · +2 more institutions
Abstract
This paper proposes an image dehazing model built with a convolutional neural network (CNN), called All-in-One Dehazing Network (AOD-Net). It is designed based on a re-formulated atmospheric scattering model. Instead of estimating the transmission matrix and the atmospheric light separately as most previous models did, AOD-Net directly generates the clean image through a light-weight CNN. Such a novel end-to-end design makes it easy to embed AOD-Net into other deep models, e.g., Faster R-CNN, for improving high-level tasks on hazy images. Experimental results on both synthesized and natural hazy image datasets demonstrate our superior performance than the state-of-the-art in terms of PSNR, SSIM and the…
Citation impact
- FWCI
- 38.91
- Percentile
- 100%
- References
- 42
Authors
5- BLBoyi LiCorresponding
Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology
- XPXiulian Peng
Microsoft Research Asia (China)
- ZWZhangyang Wang
Texas A&M University
- JXJizheng Xu
Microsoft Research Asia (China)
- DFDan Feng
Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology
Topics & keywords
- Computer science
- Convolutional neural network
- Artificial intelligence
- Image (mathematics)
- Net (polyhedron)
- Transmission (telecommunications)
- Image quality
- Computer vision