Authors:
Fahimeh Farhadifard
1
;
Martin Radolko
1
and
Uwe Freiherr von Lukas
2
Affiliations:
1
University of Rostock, Germany
;
2
University of Rostock and Fraunhofer IGD Institute, Germany
Keyword(s):
Digital Image Processing, Underwater Imaging, Marine Snow Removal, Image Enhancement.
Related
Ontology
Subjects/Areas/Topics:
Color and Texture Analyses
;
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
;
Image Enhancement and Restoration
;
Image Formation and Preprocessing
Abstract:
Underwater image processing has attracted a lot of attention due to the special difficulties at capturing clean
and high quality images in this medium. Blur, haze, low contrast and color cast are the main degradations.
In an underwater image noise is mostly considered as an additive noise (e.g. sensor noise), although the
visibility of underwater scenes is distorted by another source, termed marine snow. This signal disturbs image
processing methods such as enhancement and segmentation. Therefore removing marine snow can improve
image visibility while helping advanced image processing approaches such as background subtraction to yield
better results. In this article, we propose a simple but effective filter to eliminate these particles from single
underwater images. It consists of different steps which adapt the filter to fit the characteristics of marine snow
the best. Our experimental results show the success of our algorithm at outperforming the existing approaches
by effectively
removing this phenomenon and preserving the edges as much as possible.
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