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Recent Advances in Electrical & Electronic Engineering

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ISSN (Print): 2352-0965
ISSN (Online): 2352-0973

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Research Article

Underwater Image Enhancement Method Combining color and Luminance

Author(s): Zhao Baiting, Wang Feng, Jia Xiaofen, Guo Yongcun* and Wang Chengjun

Volume 14, Issue 2, 2021

Published on: 26 October, 2020

Page: [241 - 249] Pages: 9

DOI: 10.2174/2352096513999201026225829

Price: $65

Abstract

Background: Aiming at the problems of color distortion, low clarity, and poor visibility of underwater images caused by a complex underwater environment, a wavelet fusion method, UIPWF, for underwater image enhancement is proposed.

Methods: First of all, an improved NCB color balance method is designed to identify and cut the abnormal pixels and balance the color of R, G, and B channels by an affine transformation. Then, the color correction map is converted to CIELab color space, and the L component is equalized with contrast limited adaptive histogram to obtain the brightness enhancement map. Finally, different fusion rules are designed for low-frequency and high-frequency components, the pixel level wavelet fusion of color balance image and brightness enhancement image is realized to improve the edge detail contrast on the basis of protecting the underwater image contour.

Results: The experiments demonstrate that compared with the existing underwater image processing methods, UIPWF is highly effective in the underwater image enhancement task, improves the objective indicators greatly, and produces visually pleasing enhancement images with clear edges and reasonable color information.

Conclusion: The UIPWF method can effectively mitigate the color distortion, improve the clarity and contrast, which is applicable for underwater image enhancement in different environments.

Keywords: Image enhancement, underwater image, color correction, luminance enhancement, wavelet fusion, Dark Channel Prior (DCP).

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[1]
RaihanRaihan A J, "Abas P E, C. De Silva L. Review of underwater image restoration algorithms", IET Image Process., vol. 13, no. 10, pp. 1587-1596, 2019.
[http://dx.doi.org/10.1049/iet-ipr.2019.0117]
[2]
K. He, J. Sun, and X. Tang, "Single image haze removal using dark channel prior", IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 12, pp. 2341-2353, 2011.
[http://dx.doi.org/10.1109/TPAMI.2010.168] [PMID: 20820075]
[3]
J.Y. Chiang, and Y.C. Chen, "Underwater image enhancement by wavelength compensation and dehazing", IEEE Trans. Image Process., vol. 21, no. 4, pp. 1756-1769, 2012.
[http://dx.doi.org/10.1109/TIP.2011.2179666] [PMID: 22180510]
[4]
A. Galdran, D. Pardo, and A. Picón, "Automatic red-channel underwater image restoration", J. Vis. Commun. Image Represent., vol. 26, pp. 132-145, 2015.
[http://dx.doi.org/10.1016/j.jvcir.2014.11.006]
[5]
Y. Wang, H. Liu, and L.P. Chau, "Single underwater image restoration using adaptive attenuation-curve prior", IEEE Trans. Circuits Syst. I Regul. Pap., vol. 65, no. 3, pp. 992-1002, 2018.
[http://dx.doi.org/10.1109/TCSI.2017.2751671]
[6]
H.H. Chang, C.Y. Cheng, and C.C. Sung, "Single underwater image restoration based on depth estimation and transmission compensation", IEEE J. Oceanic Eng., vol. 44, no. 4, pp. 1130-1149, 2019.
[http://dx.doi.org/10.1109/JOE.2018.2865045]
[7]
P.W. Pan, F. Yuan, and E. Cheng, "Underwater image de-scattering and enhancing using dehazenet and HWD", J. Mar. Sci. Technol., vol. 26, no. 04, pp. 531-540, 2018.
[http://dx.doi.org/10.6119/JMST.201808_26(4).0006]
[8]
N. Limare, J.L. Lisani, and J.M. Morel, "Simplest color balance", Image Processing on Line, vol. 1, pp. 297-315, 2011.
[http://dx.doi.org/10.5201/ipol.2011.llmps-scb]
[9]
M. Yang, and Z.C. Ji, "Underwater color image enhancement based on quaternion and fuzzy morphological sieves", Yiqi Yibiao Xuebao, vol. 33, no. 7, pp. 1601-1605, 2012.
[10]
C. Ancuti, C.O. Ancuti, and T. Haber, "Enhancing underwater images and videos by fusion In", Proceeding of IEEE Conference on Computer Vision and Pattern Recognition, 2012pp. 81-88
[http://dx.doi.org/10.1109/CVPR.2012.6247661]
[11]
C-Y. Li, J-C. Guo, R-M. Cong, Y-W. Pang, and B. Wang, "Underwater image enhancement by dehazing with minimum information loss and histogram distribution prior", IEEE Trans. Image Process., vol. 25, no. 12, pp. 5664-5677, 2016.
[http://dx.doi.org/10.1109/TIP.2016.2612882] [PMID: 28113974]
[12]
S. Zhang, T. Wang, and J.Y. Dong, "Underwater image enhancement via extended multi-scale Retinex", Neurocomputing, vol. 245, pp. 1-9, 2017.
[http://dx.doi.org/10.1016/j.neucom.2017.03.029]
[13]
C.O. Ancuti, C. Ancuti, C. De Vleeschouwer, and P. Bekaert, "Color balance and fusion for underwater image enhancement", IEEE Trans. Image Process., vol. 27, no. 1, pp. 379-393, 2018.
[http://dx.doi.org/10.1109/TIP.2017.2759252] [PMID: 28981416]
[14]
C.L. Li, Y.W. Sun, and J.W. Yan, "Underwater color image enhancement algorithm based on multi-channel equalization", J. Huazhong Uni. Sci. Technol. [Natural Science Edition, vol. 47, no. 6, pp. 1-5, 2019.
[15]
T.S. Krishnapriya, Underwater image processing using hybrid techniques., Nissan Kunju, 2019.
[16]
S.T. Li, X.D. Kang, and L.Y. Fang, "Pixel-level image fusion: A survey of the state of the art", Inf. Fusion, vol. 33, pp. 100-112, 2017.
[http://dx.doi.org/10.1016/j.inffus.2016.05.004]
[17]
J. Jiao, L.D. Wu, and S.B. Yu, "Image fusion method using multi-scale analysis and improved PCNN", J. Comput. Aided Des. Comput. Graph., vol. 31, no. 6, pp. 987-996, 2019.
[http://dx.doi.org/10.3724/SP.J.1089.2019.17405]
[18]
C.G. Dai, M.X. Lin, and Z. Wang, "Color compensation based on bright channel and fusion for underwater image enhancement", Acta Optica. Sinica., vol. 38, no. 11, 2018.
[19]
Y. Yang, S.Y. Huang, and J.F. Gao, "Multi-focus image fusion using an effective discrete wavelet transform based algorithm", Meas. Sci. Rev., vol. 14, no. 2, pp. 102-108, 2014.
[http://dx.doi.org/10.2478/msr-2014-0014]
[20]
X. Qiao, J.H. Bao, and H. Zhang, "Underwater image quality enhancement of sea cucumbers based on improved histogram equalization and wavelet transform", Inf. Process. Agric., vol. 4, no. 3, pp. 206-213, 2017.
[http://dx.doi.org/10.1016/j.inpa.2017.06.001]
[21]
X.L. Zhang, X.F. Li, and Y.C. Feng, "Image fusion based on simultaneous empirical wavelet transform", Multimedia Tools Appl., vol. 76, no. 6, pp. 8175-8193, 2017.
[http://dx.doi.org/10.1007/s11042-016-3453-8]
[22]
K. Panetta, C. Gao, and S. Agaian, "Human-visual-system-inspired underwater image quality measures", IEEE J. Oceanic Eng., vol. 41, no. 3, pp. 541-551, 2016.
[http://dx.doi.org/10.1109/JOE.2015.2469915]
[23]
K. Gu, G.T. Zhai, and X.K. Yang, "Using free energy principle for blind image quality assessment", IEEE Trans. Multimed., vol. 17, no. 1, pp. 50-63, 2015.
[http://dx.doi.org/10.1109/TMM.2014.2373812]
[24]
M. Yang, and A. Sowmya, "An underwater color image quality evaluation metric", IEEE Trans. Image Process., vol. 24, no. 12, pp. 6062-6071, 2015.
[http://dx.doi.org/10.1109/TIP.2015.2491020] [PMID: 26513783]

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