We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Learning-Based Dark and Blurred Underwater Image Restoration.
- Authors
Xu, Yifeng; Wang, Huigang; Cooper, Garth Douglas; Rong, Shaowei; Sun, Weitao
- Abstract
Underwater image processing is a difficult subtopic in the field of computer vision due to the complex underwater environment. Since the light is absorbed and scattered, underwater images have many distortions such as underexposure, blurriness, and color cast. The poor quality hinders subsequent processing such as image classification, object detection, or segmentation. In this paper, we propose a method to collect underwater image pairs by placing two tanks in front of the camera. Due to the high-quality training data, the proposed restoration algorithm based on deep learning achieves inspiring results for underwater images taken in a low-light environment. The proposed method solves two of the most challenging problems for underwater image: darkness and fuzziness. The experimental results show that the proposed method surpasses most other methods.
- Subjects
IMAGE reconstruction; IMAGE processing; VISUAL fields; DEEP learning; ALGORITHMS; COMPUTER vision
- Publication
Complexity, 2020, p1
- ISSN
1076-2787
- Publication type
Article
- DOI
10.1155/2020/6549410