A Rain Pixel Recovery Algorithm for Videos With Highly Dynamic Scenes

Rain removal is a very useful and important technique in applications such as security surveillance and movie editing. Several rain removal algorithms have been proposed these years, where photometric, chromatic, and probabilistic properties of the rain have been exploited to detect and remove the r...

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Bibliographic Details
Published in:IEEE transactions on image processing 2014-03, Vol.23 (3), p.1097-1104
Main Authors: Chen, Jie, Chau, Lap-Pui
Format: Article
Language:English
Subjects:
adaptive filters
Algorithms
Applied sciences
Detection, estimation, filtering, equalization, prediction
dynamic scene
Dynamics
Exact sciences and technology
Heuristic algorithms
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
Information, signal and communications theory
motion buffering
motion occlusion
Motion segmentation
Optical imaging
Pattern Recognition, Automated - methods
Photography - methods
Rain
rain removal
Reproducibility of Results
Sensitivity and Specificity
Signal and communications theory
Signal processing
Signal representation. Spectral analysis
Signal, noise
Subtraction Technique
Surveillance
Telecommunications and information theory
Video Recording - methods
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Summary:Rain removal is a very useful and important technique in applications such as security surveillance and movie editing. Several rain removal algorithms have been proposed these years, where photometric, chromatic, and probabilistic properties of the rain have been exploited to detect and remove the rainy effect. Current methods generally work well with light rain and relatively static scenes, when dealing with heavier rainfall in dynamic scenes, these methods give very poor visual results. The proposed algorithm is based on motion segmentation of dynamic scene. After applying photometric and chromatic constraints for rain detection, rain removal filters are applied on pixels such that their dynamic property as well as motion occlusion clue are considered; both spatial and temporal informations are then adaptively exploited during rain pixel recovery. Results show that the proposed algorithm has a much better performance for rainy scenes with large motion than existing algorithms.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2013.2290595