DocumentCode
2711675
Title
Enhancing underwater images and videos by fusion
Author
Ancuti, Cosmin ; Ancuti, Codruta Orniana ; Haber, Tom ; Bekaert, Philippe
Author_Institution
IBBT, Hasselt Univ., Hasselt, Belgium
fYear
2012
fDate
16-21 June 2012
Firstpage
81
Lastpage
88
Abstract
This paper describes a novel strategy to enhance underwater videos and images. Built on the fusion principles, our strategy derives the inputs and the weight measures only from the degraded version of the image. In order to overcome the limitations of the underwater medium we define two inputs that represent color corrected and contrast enhanced versions of the original underwater image/frame, but also four weight maps that aim to increase the visibility of the distant objects degraded due to the medium scattering and absorption. Our strategy is a single image approach that does not require specialized hardware or knowledge about the underwater conditions or scene structure. Our fusion framework also supports temporal coherence between adjacent frames by performing an effective edge preserving noise reduction strategy. The enhanced images and videos are characterized by reduced noise level, better exposed-ness of the dark regions, improved global contrast while the finest details and edges are enhanced significantly. In addition, the utility of our enhancing technique is proved for several challenging applications.
Keywords
image colour analysis; image denoising; image enhancement; image fusion; light absorption; light scattering; video signal processing; adjacent frames; color corrected version; contrast enhanced version; distant objects degradation; edge preserving noise reduction strategy; enhancing technique; fusion framework; fusion principles; global contrast; image fusion; medium absorption; medium scattering; reduced noise level; single image approach; temporal coherence; underwater conditions; underwater image enhancement; underwater scene structure; underwater videos enhancement; weight maps; Image color analysis; Image edge detection; Image restoration; Laplace equations; Lighting; Noise; Videos;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on
Conference_Location
Providence, RI
ISSN
1063-6919
Print_ISBN
978-1-4673-1226-4
Electronic_ISBN
1063-6919
Type
conf
DOI
10.1109/CVPR.2012.6247661
Filename
6247661
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