Detecting Blurred Ground-based Sky/Cloud Images

Ground-based whole sky imagers (WSIs) are being used by researchers in various fields to study the atmospheric events. These ground-based sky cameras capture visible-light images of the sky at regular intervals of time. Owing to the atmospheric interference and camera sensor noise, the captured imag...

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Bibliographic Details
Published in:arXiv.org 2021-10
Main Authors: Jain, Mayank, Jain, Navya, Yee Hui Lee, Winkler, Stefan, Soumyabrata Dev
Format: Article
Language:English
Subjects:
Cameras
Clouds
Image processing
Sky
Online Access:Get full text
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Summary:Ground-based whole sky imagers (WSIs) are being used by researchers in various fields to study the atmospheric events. These ground-based sky cameras capture visible-light images of the sky at regular intervals of time. Owing to the atmospheric interference and camera sensor noise, the captured images often exhibit noise and blur. This may pose a problem in subsequent image processing stages. Therefore, it is important to accurately identify the blurred images. This is a difficult task, as clouds have varying shapes, textures, and soft edges whereas the sky acts as a homogeneous and uniform background. In this paper, we propose an efficient framework that can identify the blurred sky/cloud images. Using a static external marker, our proposed methodology has a detection accuracy of 94\%. To the best of our knowledge, our approach is the first of its kind in the automatic identification of blurred images for ground-based sky/cloud images.
ISSN:2331-8422