Real-time content adaptive contrast enhancement for see-through fog and rain

In this paper we present a novel algorithm for improving the visibility of surveillance videos degraded by fog and/or rain. The proposed algorithm adaptively enhances the global and local contrast of a surveillance video. The algorithm is inspired on the human visual system, and accounts for the per...

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Bibliographic Details
Published in2010 IEEE International Conference on Acoustics, Speech and Signal Processing pp. 1378 - 1381
Main Authors Zhen Jia, Hongcheng Wang, Caballero, Rodrigo, Ziyou Xiong, Jianwei Zhao, Finn, Alan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2010
Subjects
Adaptive equalizers
Contrast Enhancement
Degradation
Histograms
Human Visual System
Humans
Image coding
Rain
Real time systems
Surveillance
Video Quality Enhancement
Videos
Visual Surveillance
Visual system
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Summary:In this paper we present a novel algorithm for improving the visibility of surveillance videos degraded by fog and/or rain. The proposed algorithm adaptively enhances the global and local contrast of a surveillance video. The algorithm is inspired on the human visual system, and accounts for the perceptual sensitivity to noise, compression artifacts, and the texture of image content. The model is combined with the classic Contrast Limited Adaptive Histogram Equalization (CLAHE) method to adaptively enhance surveillance videos. We have implemented a real-time video enhancement system and performed extensive experimental testing over a video database containing common surveillance videos recorded under fog and rain conditions. The proposed approach significantly improves the visual quality of surveillance videos by removing fog/rain effects, as well as reducing noise and artifacts.
ISBN:9781424442959
1424442958
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2010.5495454