Image Processing and Visual Recognition for Adverse Weather Sensing and Monitoring
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 5
Special Issue Editors
Interests: image enhancement; object detection; semantic segmentation; sensor fusion
Special Issue Information
Dear Colleagues,
Vision-based perception systems are now widely applied in intelligent sensing scenarios such as autonomous driving, robotics, and surveillance. However, adverse weather conditions, including rain, fog, snow, and low light, can significantly degrade the quality of images captured by vision sensors. This degradation often leads to a substantial decline in the performance of downstream visual recognition tasks, such as object detection, semantic segmentation, and scene understanding.
This Special Issue aims to showcase recent advances in robust image processing and visual recognition techniques designed to address the challenges posed by adverse weather conditions. We invite research and review articles that focus on improving the robustness and performance of vision-based sensing systems through image restoration and enhancement, sensor fusion, and deep learning-based approaches.
Articles may cover, but are not limited to, the following topics:
- Object detection;
- RGB-D object detection;
- RGB-T object detection;
- Multimodal object detection and fusion;
- 3D object detection;
- Image fusion;
- Semantic and instance segmentation;
- Image restoration and enhancement;
- Image dehazing and deraining;
- Low-light image enhancement.
Dr. Jin Xie
Dr. Hanqing Sun
Guest Editors
Manuscript Submission Information
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Keywords
- visual recognition
- object detection
- semantic segmentation
- image enhancement
- image restoration
- image denoising
- image dehazing
- image fusion
- adverse weather
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