An optimization method for underwater images enhancement
DOI:
https://doi.org/10.31185/wjps.171Keywords:
Underwater image enhancement, Digital Image, Image Processing, Coronavirus Herd Immunity Optimizer Algorithm (CHIO), MetaheuristicsAbstract
Underwater images suffer from absorption and scattering of light, so underwater images are blurry, while contrast, clarity, and lighting are low. To improve the quality of underwater images, a method based on the new metaheuristic algorithm, the CHIO algorithm, was proposed. In our work, we first read the images and convert the color system from RGB to HSV. Subsequently, apply the CHIO algorithm to the image, and finally convert the color system from HSV to RGB. Experiments on the standard benchmark dataset for underwater image optimization proved the effectiveness of the method, while the performance of our algorithm is better than that of the standard optimization algorithms.
References
S. Lin, Z. Li, F. Zheng, Q. Zhao, and S. Li, “Underwater Image Enhancement Based on Adaptive Color Correction and Improved Retinex Algorithm,” IEEE Access, pp. 1–1, 2023, doi: 10.1109/access.2023.3258698.
W. Zhang, X. Pan, X. Xie, L. Li, Z. Wang, and C. Han, “Color correction and adaptive contrast enhancement for underwater image enhancement,” Comput. Electr. Eng., vol. 91, no. December 2020, p. 106981, 2021, doi: 10.1016/j.compeleceng.2021.106981.
F. Fausto, A. Reyna-Orta, E. Cuevas, Á. G. Andrade, and M. Perez-Cisneros, “From ants to whales: metaheuristics for all tastes,” Artif. Intell. Rev., vol. 53, no. 1, pp. 753–810, Jan. 2020, doi: 10.1007/s10462-018-09676-2.
Z. A. A. Alyasseri, “ADAPTION OF HARMONY SEARCH ALGORITHM FOR GRAY IMAGE ENHANCEMENT,” Universiti Sains Malaysia, 2013.
A. Abunaser, I. A. Doush, N. Mansour, and S. Alshattnawi, “Underwater Image Enhancement Using Particle Swarm Optimization,” J. Intell. Syst., vol. 24, no. 1, pp. 99–115, Mar. 2015, doi: 10.1515/JISYS-2014-0012/MACHINEREADABLECITATION/RIS.
Y. A. Zaid Abdi Alkareem, I. Venkat, M. A. Al-Betar, and A. T. Khader, “Edge preserving image enhancement via harmony search algorithm,” Conf. Data Min. Optim., no. September, pp. 47–52, 2012, doi: 10.1109/DMO.2012.6329797.
A. A. Yassin, R. M. Ghadban, S. F. Salah, and H. Z. Neima, “Using discrete wavelet transformation to enhance underwater image,” Int. J. Comput. Sci. Issues, vol. 10, no. 2, pp. 220–228, 2013.
O. Deperlioglu, U. Kose, and G. Emre Guraksin, “Underwater Image Enhancement with HSV and Histogram Equalization,” Int. Conf. Adv. Technol. (ICAT 2018), 2018.
M. A. Al-Betar, Z. A. A. Alyasseri, M. A. Awadallah, and I. Abu Doush, “Coronavirus herd immunity optimizer (CHIO),” Neural Comput. Appl., vol. 33, no. 10, pp. 5011–5042, May 2021, doi: 10.1007/s00521-020-05296-6.
M. A. Al-Betar, A. T. Khader, Z. Abdi, A. Alyasseri, A. La’aro Bolaji, and M. A. Awadallah, “Gray image enhancement using harmony search,” Taylor Fr., vol. 9, no. 5, pp. 932–944, Sep. 2016, doi: 10.1080/18756891.2016.1237191.
P. Zhuang, C. Li, and J. Wu, “Bayesian retinex underwater image enhancement,” Eng. Appl. Artif. Intell., vol. 101, no. March, p. 104171, 2021, doi: 10.1016/j.engappai.2021.104171.
Z. Wu, J. Han, and C. Cao, “Research on underwater image enhancement algorithm based on improved DCP,” J. Phys. Conf. Ser., vol. 2083, no. 4, p. 042008, Nov. 2021, doi: 10.1088/1742-6596/2083/4/042008.
S. Selva Nidhyanandhan, R. Sindhuja, and R. S. Selva Kumari, “Double Stage Gaussian Filter for Better Underwater Image Enhancement,” Wirel. Pers. Commun., vol. 114, no. 4, pp. 2909–2921, Oct. 2020, doi: 10.1007/s11277-020-07509-6.
K. Sun, F. Meng, and Y. Tian, “Progressive multi-branch embedding fusion network for underwater image enhancement,” J. Vis. Commun. Image Represent., vol. 87, no. October 2021, p. 103587, 2022, doi: 10.1016/j.jvcir.2022.103587.
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Zaid Alyasseri, Rana Ghalib
This work is licensed under a Creative Commons Attribution 4.0 International License.
