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Updated: Mar 31, 2026

High Throughput Analysis of Liquid Droplet Impacts
Published on: March 6, 2020
Adherent Raindrop Modeling, Detectionand Removal in Video
This study introduces a novel method for detecting and removing raindrops from videos using physics-based models and spatio-temporal derivatives. The technique effectively restores visibility in computer vision applications like intelligent vehicles and surveillance systems.
Area of Science:
- Computer Vision
- Image Processing
- Physics-based Modeling
Background:
- Raindrops on surfaces like windscreens degrade visibility.
- Accurate raindrop detection and removal are crucial for intelligent vehicles and surveillance systems.
Purpose of the Study:
- To develop an automated method for detecting and removing adherent raindrops from video footage.
- To enhance visibility in computer vision applications affected by raindrops.
Main Methods:
- Modeling adherent raindrops using physical laws.
- Detecting raindrops via spatio-temporal derivatives and motion/intensity analysis.
- Removing and restoring images by analyzing occlusion (partial/complete) and employing blending functions or video completion techniques.
Main Results:
- Demonstrated effectiveness in detecting and removing raindrops from various real-world videos.
- Successful restoration of scene visibility obscured by raindrops.
Conclusions:
- The proposed method offers an effective solution for raindrop removal in video.
- Significant improvements in visibility for computer vision applications are achievable.
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