Abstract
Underwater images are degraded by attenuation of light in water. This attenuation depends upon wavelength and depth in water. One of the effects of degradation of image in water is absorption of colour giving greenish-blue hue to the image. Because of this colour fading of underwater images, colour correction is the first preprocessing step in underwater image processing. Many researchers attempted colour correction methods but most of it operates globally. Global colour correction methods give reddish effect to image. The method proposed in this paper used Grey World approach for colour correction, but it is modified using attenuation map. Use of attenuation map avoids saturation of colours and colour corrects only those pixels which are significantly attenuated. Results of the proposed method are compared with state-of-the-art methods by quality metrics mean square error, structural similarity index and entropy of image. It is seen that the proposed method in this paper gives better results than state-of-the-art methods.
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References
Schettini, R., Corchs, S.: Underwater image processing: state of the art of restoration and image enhancement methods. EURASIP J. Adv. in Signal Process. 2010, Article ID 746052 (2010)
Funk, C., Bryant, S., Heckman, P.: Handbook of underwater imaging system design. Technical Report TP303, Naval Undersea Center, San Diego, Calif, USA (1972)
Torres-Mendez, L.A., Dudek, G.: Color correction of underwater images for aquatic robot inspection. In: Proceedings of the 5th International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR ’05) (2005)
Vasilescu, I., Detweiler, C., Rus, D.: Color-accurate underwater imaging using perceptual adaptive illumination. Auton Robot 31, 285–296 (2011)
Bazeille, S., Quidu, I., Jaulin, L., Malkasse, J.P.: Automatic underwater image pre-processing. In: Proceedings of the Caracterisation du Milieu Marin (CMM ’06) (2006)
Çelebi, A.T., Ertürk, S.: Visual enhancement of underwater images using empirical mode decomposition. Expert Syst. Appl. 39(1), 800–805 (2012)
Chiang, J.Y., Ying: Underwater image enhancement by wavelength compensation and image dehazing. IEEE Trans. Image Process. 21(4), 1756–1769 (2012)
Naim, M.J.N.M., Isa, N.A.M.: Pixel distribution shifting color correction for digital color images. J. Appl. Soft Comput. 12(9), 2948–2962 (2012)
Iqbal, K., Michael Odetayo, R., James, A., Salam, A., Talib, A.Z.: Enhancing the low quality images using unsupervised colour correction method. In: Proceedings of the IEEE conference on Systems Man and Cybernetics (SMC), pp. 1703–1709, Istanbul, Turkey, Oct 2010
Abdul Ghani, A.S., Isa, N.A.M.: Underwater image quality enhancement through composition of dual-intensity images and Rayleigh-stretching, vol. 3, article 757. SpringerPlus (2014)
Bianco, G., Muzzupappa, M., Brunoa, F., Garciab, R., Neumann, L.: A new color correction method for underwater imaging, the international archives of the photogrammetry. Remote Sens. Spat. Inf. Sci. XL-5/W5 (2015); Underwater 3D Recording and Modelling, Piano di Sorrento, Italy, pp. 16–17, Apr 2015
Abdul Ghani, A.S., Isa, N.A.M.: Homomorphic filtering with image fusion for enhancement of detail and homogeneous contrast of underwater image. Indian J. Geo-Mar. Sci. 44(2), 1904–1919 (2015)
Ancuti, C.O., Ancuti, C., De Vleeschouwer, C., Garcia, R.: A semi-global colour correction for underwater image restoration. In: Proceedings of SIGGRAPH 17, Posters, Los Angeles, CA, USA, July–Aug 2017
Fu, X., Zhuang, P., Huang, Y., Liao, Y., Zhang, X.P., Ding, X.: A retinex-based enhancing approach for single underwater image. In: IEEE International Conference on Image Processing, pp. 4572–4576 (2014)
Li, C.-Y., Guo, J.-C., Guo, C., Cong, R.-M., Gong, J.: A hybrid method for underwater image correction. Pattern Recognit. Lett. 94, 62–67 (2017)
Ancuti, C.O., Ancuti, C., De Vleeschouwer, C., Bekaert, P.: Color balance and fusion for underwater image enhancement. IEEE Trans. Image Process. 27(1), 379–393 (2018)
Buchsbaum, G.: A spatial processor model for object colour perception. J. Frankl. Inst. 310, 1–26 (1980)
He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1956–1963 (2009)
Carlevaris-Bianco, N., Mohan, A., Eustice, R.M.: Initial results in underwater single image dehazing. In: Proceedings of the IEEE conference on OCEANS 2010, Seattle, WA, USA, Sept 2010
Duarte, A., Codevilla, F., Gaya, J.D.O., Botelho, S.S.C.: A Dataset to Evaluate Underwater Image Restoration Methods, in Proceedings of the IEEE conference on OCEANS 2016, Shanghai, China, April (2016)
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 1–14 (2004)
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Sankpal, S., Deshpande, S. (2019). Underwater Image Colour Balance by Grey World Approach with Attenuation Map. In: Iyer, B., Nalbalwar, S., Pathak, N. (eds) Computing, Communication and Signal Processing . Advances in Intelligent Systems and Computing, vol 810. Springer, Singapore. https://doi.org/10.1007/978-981-13-1513-8_91
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DOI: https://doi.org/10.1007/978-981-13-1513-8_91
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