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Underwater Image Enhancement by Adaptive Gray World and Differential Gray-Levels Histogram EqualizationWONG, S.-L. , PARAMESRAN, R. , TAGUCHI, A.
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digital images, image processing, image enhancement, image color analysis, image fusion
image(23), water(16), enhancement(11), processing(10), quality(6), information(5), signal(4), restoration(4), method(4), images(4)
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About this article
Date of Publication: 2018-05-31
Volume 18, Issue 2, Year 2018, On page(s): 109 - 116
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.02014
Web of Science Accession Number: 000434245000014
SCOPUS ID: 85047857925
Most underwater images tend to be dominated by a single color cast. This paper presents a solution to remove the color cast and improve the contrast in underwater images. However, after the removal of the color cast using Gray World (GW) method, the resultant image is not visually pleasing. Hence, we propose an integrated approach using Adaptive GW (AGW) and Differential Gray-Levels Histogram Equalization (DHE) that operate in parallel. The AGW is applied to remove the color cast while DHE is used to improve the contrast of the underwater image. The outputs of both chromaticity components of AGW and intensity components of DHE are combined to form the enhanced image. The results of the proposed method are compared with three existing methods using qualitative and quantitative measures. The proposed method increased the visibility of underwater images and in most cases produces better quantitative scores when compared to the three existing methods.
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| J. Y. Chiang and Ying-Ching Chen, "Underwater Image Enhancement by Wavelength Compensation and Dehazing," IEEE Transactions on Image Processing, vol. 21, no. 4, pp. 1756-1769, Apr. 2012. |
[CrossRef] [Web of Science Times Cited 145] [SCOPUS Times Cited 206]
 E. Trucco and A. T. Olmos-Antillon, "Self-tuning underwater image restoration," IEEE Journal of Oceanic Engineering, vol. 31, no. 2, pp. 511-519, Apr. 2006.
[CrossRef] [Web of Science Times Cited 52] [SCOPUS Times Cited 65]
 A. Galdran, D. Pardo, A. Picon, and A. Alvarez-Gila, "Automatic Red-Channel underwater image restoration," Journal of Visual Communication and Image Representation, vol. 26, pp. 132-145, Jan. 2015.
[CrossRef] [Web of Science Times Cited 55] [SCOPUS Times Cited 67]
 M. S. Hitam, W. N. J. H. W. Yussof, E. A. Awalludin, and Z. Bachok, "Mixture contrast limited adaptive histogram equalization for underwater image enhancement," in 2013 International Conference on Computer Applications Technology (ICCAT), 2013, pp. 1-5.
[CrossRef] [SCOPUS Times Cited 62]
 K. Iqbal, M. Odetayo, and A. James, "Enhancing the low quality images using Unsupervised Colour Correction Method," in 2010 IEEE International Conference on Systems, Man and Cybernetics, 2010, pp. 1703-1709.
[CrossRef] [SCOPUS Times Cited 68]
 R. Schettini and S. Corchs, "Underwater image processing: state of the art of restoration and image enhancement methods," EURASIP Journal on Advances in Signal Processing, vol. 2010, pp. 1-15, 2010.
[CrossRef] [Web of Science Times Cited 93] [SCOPUS Times Cited 216]
 A. S. A. Ghani and N. A. M. Isa, "Underwater image quality enhancement through Rayleigh-stretching and averaging image planes," International Journal of Naval Architecture and Ocean Engineering, vol. 6, no. 4, pp. 840-866, 2014.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 11]
 A. S. A. Ghani and N. A. M. Isa, "Underwater image quality enhancement through integrated color model with Rayleigh distribution," Applied Soft Computing, vol. 27, pp. 219-230, Feb. 2015.
[CrossRef] [Web of Science Times Cited 22] [SCOPUS Times Cited 31]
 A. S. A. Ghani and N. A. M. Isa, "Enhancement of low quality underwater image through integrated global and local contrast correction," Applied Soft Computing, vol. 37, pp. 332-344, Dec. 2015.
[CrossRef] [Web of Science Times Cited 13] [SCOPUS Times Cited 19]
 C. Li, J. Guo, S. Chen, Y. Tang, Y. Pang, and J. Wang, "Underwater image restoration based on minimum information loss principle and optical properties of underwater imaging," in 2016 IEEE International Conference on Image Processing (ICIP), 2016, no. 20120032110034, pp. 1993-1997.
[CrossRef] [SCOPUS Times Cited 6]
 C. Li, J. Guo, R. Cong, Y. Pang, and B. Wang, "Underwater Image Enhancement by Dehazing with Minimum Information Loss and Histogram Distribution Prior," IEEE Transactions on Image Processing, vol. 25, no. 12, pp. 5664-5677, Dec. 2016.
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 33]
 N. Carlevaris-Bianco, A. Mohan, and R. M. Eustice, "Initial results in underwater single image dehazing," in Oceans 2010 Mts/Ieee Seattle, 2010, pp. 1-8.
[CrossRef] [SCOPUS Times Cited 95]
 C. Ancuti, C. O. Ancuti, T. Haber, and P. Bekaert, "Enhancing underwater images and videos by fusion," in 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012, pp. 81-88.
[CrossRef] [SCOPUS Times Cited 143]
 C. O. Ancuti, C. Ancuti, C. De Vleeschouwer, and P. Bekaert, "Color Balance and Fusion for Underwater Image Enhancement," IEEE Transactions on Image Processing, vol. 27, no. 1, pp. 379-393, Jan. 2018.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 8]
 G. Buchsbaum, "A spatial processor model for object colour perception," Journal of the Franklin Institute, vol. 310, no. 1, pp. 1-26, 1980.
[CrossRef] [Web of Science Times Cited 658] [SCOPUS Times Cited 827]
 V. Chikane and C. S. Fuh, "Automatic white balance for digital still cameras," Journal of Information Science and Engineering, vol. 22, no. 3, pp. 497-509, 2006.
[CrossRef] [Web of Science Times Cited 51] [SCOPUS Times Cited 73]
 W. J. Kyung, D. C. Kim, H. G. Ha, and Y. H. Ha, "Color enhancement for faded images based on multi-scale gray world algorithm," in 2012 IEEE 16th International Symposium on Consumer Electronics, no. 5, pp. 16-19, 2012.
[CrossRef] [SCOPUS Times Cited 3]
 S.-C. Tai, T.-W. Liao, Y.-Y. Chang, and C.-P. Yeh, "Automatic White Balance Algorithm through the Average Equalization and Threshold," in 8th International Conference on Information Science and Digital Content Technology (ICIDT), 2012, vol. 3, pp. 571-576.
 N. M. Kwok, D. Wang, X. Jia, S. Y. Chen, G. Fang, and Q. P. Ha, "Gray world based color correction and intensity preservation for image enhancement," 2011 4th International Congress on Image and Signal Processing, vol. 2, pp. 994-998, 2011.
[CrossRef] [SCOPUS Times Cited 15]
 G. Bianco, M. Muzzupappa, F. Bruno, R. Garcia, and L. Neumann, "A new color correction method for underwater imaging," in ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015, vol. XL-5/W5, no. April, pp. 25-32.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 22]
 E. Y. Lam, "Combining gray world and retinex theory for automatic white balance in digital photography," in Proceedings of the Ninth International Symposium on Consumer Electronics, 2005. (ISCE 2005)., 2005, pp. 134-139.
[CrossRef] [Web of Science Times Cited 63]
 K. Murahira and A. Taguchi, "A novel contrast enhancement method using differential gray-levels histogram," in 2011 International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS), 2011, pp. 1-5.
[CrossRef] [SCOPUS Times Cited 3]
 S. Wang, K. Ma, H. Yeganeh, Z. Wang, and W. Lin, "A Patch-Structure Representation Method for Quality Assessment of Contrast Changed Images," IEEE Signal Processing Letters, vol. 22, no. 12, pp. 2387-2390, Dec. 2015.
[CrossRef] [Web of Science Times Cited 42] [SCOPUS Times Cited 52]
 M. Yang and A. Sowmya, "An Underwater Color Image Quality Evaluation Metric," IEEE Transactions on Image Processing, vol. 24, no. 12, pp. 6062-6071, Dec. 2015.
[CrossRef] [Web of Science Times Cited 23] [SCOPUS Times Cited 30]
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Stefan cel Mare University of Suceava, Romania
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