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    Felizberta Lo Padilla Tong School of Social SciencesIp Ying To Lee Yu Yee School of Humanities and LanguagesRita Tong Liu School of Business and Hospitality ManagementS.K. Yee School of Health SciencesYam Pak Charitable Foundation School of Computing and Information Sciences
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Single underwater image restoration using adaptive attenuation-curve prior

Author(s)
Liu, Hui  
Author(s)
Wang, Y.
Chau, L.-P.
Date Issued
2018
Publisher
IEEE
Journal
IEEE Transactions on Circuits and Systems I: Regular Papers
Volume
65
Issue
3
Start page
992
End page
1002
Abstract
Underwater imaging is an important topic in maritime research. Due to the existence of dust-like particles in water medium, underwater images are vulnerable to the effect of low contrast and color cast. In this paper, we propose a novel underwater image restoration method based on a non-local prior, namely, adaptive attenuation-curve prior. This prior relies on the statistical distribution of pixel values. That is, all pixel values of a clear image can be partitioned into several hundred distinct clusters in RGB space, and the pixel values in each cluster will be distributed on a curve with a power function form after attenuated by water in varying degrees. Specifically, we can estimate the transmission for each pixel according to its distribution on the curves. Then, we estimate the attenuation factor to compensate for the transmission. To prevent over saturation and reduce the noise of the recovered images, we propose the saturation constraints to adjust the transmission of the three color channels. Qualitative and quantitative results demonstrate that our proposed method can achieve better performance, compared with the state-of-the-art approaches. Moreover, our proposed method can be further extended to restore other kinds of degraded images, such as hazy images.
URI
https://repository.sfu.edu.hk/handle/sfu/4119
DOI
10.1109/TCSI.2017.2751671
SFU Affiliated Publication
No
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