Abstract
Attenuation of light in water causes degradation of underwater images. This attenuation is caused by water molecules, suspended particles, and dissolved chemical compounds in water. The attenuation includes scattering and absorption of light in water. Backward scattering and fading of color are two major sources of degradation of underwater images. This paper proposed a method of enhancement of underwater images by providing a solution for degradation because of backward scattering. The proposed method corrects the effect of backward scattering by enhancing contrast of the image by Rayleigh stretching of each color channel using maximum likelihood estimation of scale parameter. After contrast enhancement, loss of energy in the signal is corrected, that recovers information loss caused by contrast enhancement. The results of the proposed method are compared quantitatively with state-of-the-art methods by applying it to underwater dataset. Comparison is done with mean square error (MSE), Structural SIMilarity index (SSIM), and Average Information Entropy (AIE) quality metrics. It is seen that the proposed method in this paper produces best results when compared with state-of-the-art methods.
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References
Jaffe, J.S.: Computer modelling and the design of optimal underwater imaging systems. IEEE J. Ocean. Eng. 15(2), 101–111 (1990)
Funk, C., Bryant, S., Heckman, P.: Handbook of underwater imaging system design. Technical report TP303, Naval Undersea Centre, San Diego, Calif, USA (1972)
Schettini, R., Corchs, S.: Underwater image processing: state of the art of restoration an image enhancement methods. EURASIP J. Adv. Signal Process. 2010 (2010)
Bazeille, S., Quidu, I., Jaulin, L., Malkasse, J.P.: Automatic underwater image pre-preprocessing. In: Proceedings of the Caracterisation du Milieu Marin (CMM ’06), Brest, France, Oct 2006
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. 1319–1321 (2009)
Carlevaris-Bianco, A., Eustice, M.R.: Initial results in underwater single image dehazing. OCEANS 2010, pp. 1–8 (2010)
Drews, P Jr., Nascimento, E.R., Boteiho, S., Campos, M.: Underwater depth estimation and image restoration based on single images. IEEE Comput. Graph. Appl. 36(2) (2016)
Chiang, J.Y., Chen, Y.: Underwater Image Enhancement by Wavelength Compensation and Dehazing (WCID). IEEE Trans. Image Proc. 21(4), 1756–1769 (2012)
Çelebi, A.T., Ertürk, S.: Visual enhancement of underwater images using empirical mode decomposition. Expert Syst. Appl. 39, 800–805 (2012)
Iqbal, K., Salam, R.A., Osman, A., Talib, A.Z.: Underwater image enhancement using integrated color model. IAENG Int. J. Comput. Sci. 34, 2 (2007)
Iqbal, K., Odetayo, M., James, A., Salam, R.A., Talib, A.Z.: Enhancing the low quality images using unsupervised color correction method. In: International Conference on System Man and Cybernetics (SMC), Istanbul, pp. 1703–1709, 10–13 Oct 2010
Abdul Ghani, A.S., Isa, N.A.M.: Underwater image quality enhancement through Rayleigh-stretching and averaging image planes. Int. J. Naval Arch. Ocean Eng. 6(4), 840–866 (2014)
Abdul Ghani, A.S., Isa, N.A.M.: Underwater Image Quality Enhancement Through Composition of Dual Intensity Images and Rayleigh-stretching, vol. 3, p. 757. Springer Plus (2014)
Sankpal, S.S., Deshpande, S.S.: Nonuniform illumination correction algorithm for underwater images using maximum likelihood estimation method. J. Eng. Dec 2015 (2016)
Ghani, A.S.A., Isa, N.A.M.: Homomorphic filtering with image fusion for enhancement of details and homogeneous contrast of underwater image. Indian J. Geo-Mar. Sci. 44(12), 1904–1919 (2015)
Fang, S., et al.: Effective single underwater image enhancement by fusion. J. Comput. 8(4), 904–911 (2013)
Ancuti, C., Ancuti, C.O., De Vleeschouwer, C., Garcia†, R., Bovik, A.C.: Multi-scale underwater descattering. In: 23rd International Conference on Pattern Recognition (ICPR) 2016, Cancun, Mexico (2016)
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)
Siddiqui, M.M.: Some problems connected with rayleigh distributions. J. Res. Nat. Bur. Stand.-D. Radio Propag. 66D(2), 167–174 (1962)
Papoulis, A., UnnikrishnaPillai, S.: The Concept of a Random Variable in Probability, Random Variables and Stochastic Processes, 4th edn. Tata McGraw-Hill Publishing Company Limited, New Delhi, Twelth Print (2007)
William, K.P.: Image enhancement. In: Digital Image Processing, 3rd edn. Wiley (2001)
Papoulis, A., UnnikrishnaPillai, S.: ‘Statistics’. In: Probability, Random Variables and Stochastic Processes. Tata McGraw-Hill Publishing Company Limited, New Delhi, 4th edn. Twelth Print (2007)
Duarte, A., Codevilla, F., De Gaya, J.O., Botelho, S.S.C.: A dataset to evaluate underwater image restoration methods. In: Proceedings of the IEEE Conference on OCEANS 2016, Shanghai, China, Apr 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 Enhancement by Rayleigh Stretching with Adaptive Scale Parameter and Energy Correction. 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_95
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DOI: https://doi.org/10.1007/978-981-13-1513-8_95
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