Abstract
Given a sequence of images taken in foggy weather, we seek to estimate the atmospheric light and the scattering coefficient. These are key parameters to characterise the nature of the fog, to reconstruct a clear image (defogging), and to infer scene depth. Existing methods adopt a sequential estimation strategy which is prone to error propagation. In sharp contrast, we take a more systematic approach and jointly estimate these parameters by solving a unified non-linear optimisation problem. Experimental results show that the proposed method is superior to existing ones in terms of both estimation accuracy and precision. Our method further demonstrates how image defogging and depth estimation can be linked to a visual localisation system, contributing to more comprehensive and robust perception in fog.
Original language | English |
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Title of host publication | 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) |
Publisher | IEEE |
Pages | 1567-1575 |
Number of pages | 9 |
ISBN (Electronic) | 9798350318920 |
DOIs | |
Publication status | Published - 9 Apr 2024 |
Event | 2024 IEEE/CVF Winter Conference on Applications of Computer Vision - Waikoloa, United States Duration: 3 Jan 2024 → 8 Jan 2024 |
Conference
Conference | 2024 IEEE/CVF Winter Conference on Applications of Computer Vision |
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Abbreviated title | WACV 2024 |
Country/Territory | United States |
City | Waikoloa |
Period | 3/01/24 → 8/01/24 |
Keywords
- 3D computer vision
- Algorithms
- Applications
- Autonomous Driving
- Low-level and physics-based vision
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Computer Science Applications