TY - JOUR
T1 - Single Underwater Image Restoration Using Adaptive Attenuation-Curve Prior
AU - Wang, Yi
AU - Liu, Hui
AU - Chau, Lap Pui
N1 - Funding Information:
ACKNOWLEDGMENT The authors would like to thank the Singapore Maritime Institute (SMI) for kindly funding this research project and Fugro Subsea Technologies Pte Ltd. providing technical platform for testing and evaluation under the SMI Deepwater Technology R&D Programme.
Publisher Copyright:
© 2004-2012 IEEE.
PY - 2018/3
Y1 - 2018/3
N2 - 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.
AB - 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.
KW - attenuation-curve prior
KW - image restoration
KW - light attenuation
KW - transmission estimation
KW - Underwater image
KW - waterlight
UR - http://www.scopus.com/inward/record.url?scp=85030726273&partnerID=8YFLogxK
U2 - 10.1109/TCSI.2017.2751671
DO - 10.1109/TCSI.2017.2751671
M3 - Journal article
AN - SCOPUS:85030726273
SN - 1549-8328
VL - 65
SP - 992
EP - 1002
JO - IEEE Transactions on Circuits and Systems I: Regular Papers
JF - IEEE Transactions on Circuits and Systems I: Regular Papers
IS - 3
ER -