Thuật toán tối ưu hóa cá voi cải tiến lai cho việc nâng cao độ tương phản và chi tiết của hình ảnh màu

Braik, M., Sheta, A.: Exploration of genetic algorithms and particle swarm optimization in improving the quality of medical images. In: Computational intelligence techniques in handling image processing and pattern recognition, pp. 329–360. Lambert Academic Publishing, Germany (2011) Braik, M., Sheta, A.F., Ayesh, A.: Image enhancement using particle swarm optimization. World congress on engineering, pp. 978–988. Springer (2007) Xiao, Y.: Blurred trace infrared image segmentation based on template approach and immune factor. Infrared Phys Technol 67, 116–120 (2014) Zhang, W., Wang, X., You, W., Chen, J., Dai, P., Zhang, P.: Resls: region and edge synergetic level set framework for image segmentation. IEEE Trans Image Process 29, 57–71 (2019) Ablin, R., Helen Sulochana, C., Prabin, G.: An investigation in satellite images based on image enhancement techniques. Euro J Remote Sens 53(sup2), 86–94 (2020) Rundo, L., Tangherloni, A., Nobile, M.S., Militello, C., Besozzi, D., Mauri, G., Cazzaniga, P.: Medga: a novel evolutionary method for image enhancement in medical imaging systems. Expert Syst Appl 119(387–399), 2019 (2019) Sreeshan, K., Dinesh, R., Renji, K.: Nondestructive inspection of aerospace composite laminate using thermal image processing. SN Appl Sci 2(11), 1–14 (2020) Prasad, K.K., Aithal, P.S.: A conceptual study on image enhancement techniques for fingerprint images. Int J Appl Eng Manag Lett 1(1), 63–72 (2017) Aziz, M.N., Purboyo, T.W., Prasasti, A.L.: A survey on the implementation of image enhancement. Int. J. Appl. Eng. Res 12(21), 11451–11459 (2017) Du, N., Luo, Q., Du, Y., Zhou, Y.: Color image enhancement: a metaheuristic chimp optimization algorithm. Neural Process Lett 2022, 1–40 (2022) Xiao-Feng, W., Shi-gang, H., Zhao, J., Li, Z., Li, J., Tang, Z., Xi, Z.: Comparative analysis of different methods for image enhancement. J Cent South Univ 21(12), 4563–4570 (2014) Cao, L., Li, H., Zhang, Y.: Retinal image enhancement using low-pass filtering and \(\alpha\)-rooting. Signal Process 170, 107445 (2020) Yang, C.C.: Image enhancement by the modified high-pass filtering approach. Optik 120(17), 886–889 (2009) Pullagura, R., Valasani, U.S., Kesari, P.P.: Hybrid wavelet-based aerial image enhancement using georectification and homomorphic filtering. Arabn J Geosci 14(13), 1–13 (2021) Mayathevar, K., Veluchamy, M., Subramani, B.: Fuzzy color histogram equalization with weighted distribution for image enhancement. Optik 216, 164927 (2020) Sengupta, D., Biswas, A., Gupta, P.: Non-linear weight adjustment in adaptive gamma correction for image contrast enhancement. Multimed Tools Appl 80(3), 3835–3862 (2021) Wang, P., Wang, Z., Lv, D., Zhang, C., Wang, Y.: Low illumination color image enhancement based on gabor filtering and retinex theory. Multimed Tools Appl 80(12), 17705–17719 (2021) Kim, Y.T.: Contrast enhancement using brightness preserving bi-histogram equalization. IEEE Trans Consum Electron 43(1), 1–8 (1997) Pizer, S.M., Amburn, E.P., Austin, J.D., Cromartie, R., Geselowitz, A., Greer, T., Romeny, B.H., Zimmerman, J.B., Zuiderveld, K.: Adaptive histogram equalization and its variations. Comput Vision Gr Image Process 39(3), 355–368 (1987) Zuiderveld, K.: Contrast limited adaptive histogram equalization. Gr Gems 1994, 474–485 (1994) Ooi, C.H., Pik Kong, N.S., Ibrahim, H.: Bi-histogram equalization with a plateau limit for digital image enhancement. IEEE Trans Consum Electron 55(4), 2072–2080 (2009) Jobson, D.J., Rahman, Z., Woodell, G.A.: Properties and performance of a center/surround retinex. IEEE Trans Image Process 6(3), 451–462 (1997) Rahman, Z., Jobson, D.J., Woodell, G.A.: Proceedings of 3rd IEEE international conference on image processing. Multi-scale retinex for color image enhancement, IEEE, USA (1996) Xiao, Y., Zijie, Z.: Infrared image extraction algorithm based on adaptive growth immune field. Neural Process Lett 51(3), 2575–2587 (2020) Tubbs, J.D.: A note on parametric image enhancement. Pattern Recognit 20(6), 617–621 (1987) Hussain Khan, A., Ahmed, S., Kumar Bera, S., Mirjalili, S., Oliva, D., Sarkar, R.: Enhancing the contrast of the grey-scale image based on meta-heuristic optimization algorithm. Soft Comput 2022, 1–23 (2022) Soleimanian Gharehchopogh, F., Shayanfar, H., Gholizadeh, H.: A comprehensive survey on symbiotic organisms search algorithms. Artif Intell Rev 53(3), 2265–2312 (2020) Ghafori, S., Soleimanian Gharehchopogh, F.: Advances in spotted hyena optimizer: a comprehensive survey. Archiv Comput Methods Eng 2021, 1–22 (2021) Soleimanian Gharehchopogh, F.: An improved tunicate swarm algorithm with best-random mutation strategy for global optimization problems. J Bionic Eng 2022, 1–26 (2022) Soleimanian Gharehchopogh, F.: Advances in tree seed algorithm: a comprehensive survey. Archiv Comput Methods Eng 2022, 1–24 (2022) Sheta, A., Braik, M.S., Aljahdali, S.: Genetic algorithms: a tool for image segmentation. In: 2012 international conference on multimedia computing and systems. IEEE (2012) Braik, M., Sheta, A., Aljahdali, S.: Diagnosis of brain tumors in mr images using metaheuristic optimization algorithms. In: International conference Europe Middle East and North Africa information systems and technologies to support learning, pp. 603–614. Springer, USA (2019) Farshi, T.R., Ardabili, A.K.: A hybrid firefly and particle swarm optimization algorithm applied to multilevel image thresholding. Multimed Syst 27(1), 125–142 (2021) Acharya, U.K., Kumar, S.: Genetic algorithm based adaptive histogram equalization (gaahe) technique for medical image enhancement. Optik 230, 166273 (2021) Roy, M., Chakraborty, S., Mali, K., Chatterjee, S., Banerjee, S., Chakraborty, A., Biswas, R., Karmakar, J., Roy, K.: Biomedical image enhancement based on modified cuckoo search and morphology. In: 2017 8th annual industrial automation and electromechanical engineering conference (IEMECON), pp. 230–235. IEEE (2017) Asokan, A., Popescu, D.E., Anitha, J., Jude Hemanth, D.: Bat algorithm based non-linear contrast stretching for satellite image enhancement. Geosciences 10(2), 78 (2020) Emre, G.G., Köse, U., Deperlıoğlu, Ö.: Underwater image enhancement based on contrast adjustment via differential evolution algorithm. In: Din, R. (ed.) 2016 International symposium on innovations in intelligent systems and applications (INISTA), pp. 1–5. IEEE, USA (2016) Mirjalili, S., Lewis, A.: The whale optimization algorithm. Adv Eng Soft 95, 51–67 (2016) Agrawal, R.K., Kaur, B., Sharma, S.: Quantum based whale optimization algorithm for wrapper feature selection. Appl Soft Comput 89, 106092 (2020) Pham, Q.V., Mirjalili, S., Kumar, N., Alazab, M., Hwang, W.: Whale optimization algorithm with applications to resource allocation in wireless networks. IEEE Trans Veh Technol 69(4), 4285–4297 (2020) Rani, S., Kumar, M.: Contrast enhancement using improved adaptive gamma correction with weighting distribution technique. Int J Comput Appl 101(11), 1–10 (2014) Hu, Y., Li, T., Huang, L., Li, Y.: Brightness preserving image enhancement method based on bilateral gamma correction. Comput Appl Soft 36(5), 204–210 (2019) Aljarah, I., Faris, H., Mirjalili, S.: Optimizing connection weights in neural networks using the whale optimization algorithm. Soft Comput 22(1), 1–15 (2018) Nasiri, J., Khiyabani, F.M.: A whale optimization algorithm (woa) approach for clustering. Cogent Math Stat 5(1), 1483565 (2018) Kaveh, A., Ilchi Ghazaan, M.: Enhanced whale optimization algorithm for sizing optimization of skeletal structures. Mech Based Design Struct Mach 45(3), 345–362 (2017) Chakraborty, S., Kumar Saha, A., Sharma, S., Mirjalili, S., Chakraborty, R.: A novel enhanced whale optimization algorithm for global optimization. Comput Ind Eng 153, 107086 (2021) Oliva, D., Aziz, M.A., Ella Hassanien, A.: Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm. Appl Energy 200, 141–154 (2017) Mohammadzadeh, H., Soleimanian Gharehchopogh, F.: A novel hybrid whale optimization algorithm with flower pollination algorithm for feature selection: Case study email spam detection. Comput Intell 37(1), 176–209 (2021) Asghari, K., Masdari, M., Soleimanian Gharehchopogh, F., Saneifard, R.: Multi-swarm and chaotic whale-particle swarm optimization algorithm with a selection method based on roulette wheel. Exp Syst 38(8), e12779 (2021) Rahnema, N., Soleimanian Gharehchopogh, F.: An improved artificial bee colony algorithm based on whale optimization algorithm for data clustering. Multimed Tools Appl 79(43), 32169–32194 (2020) Asghari, K., Masdari, M., Soleimanian Gharehchopogh, F., Saneifard, R.: A chaotic and hybrid gray wolf-whale algorithm for solving continuous optimization problems. Progress in Artif Intell 10(3), 349–374 (2021) Soleimanian Gharehchopogh, F., Gholizadeh, H.: A comprehensive survey: whale optimization algorithm and its applications. Swarm and Evol Comput 48, 1–24 (2019) Shehadeh Braik, M.: Chameleon swarm algorithm: a bio-inspired optimizer for solving engineering design problems. Exp Syst Appl 174, 114685 (2021) Braik, M., Al-Zoubi, H., Ryalat, M., Sheta, A., Alzubi, O.: Memory based hybrid crow search algorithm for solving numerical and constrained global optimization problems. Artif Intell Rev 2022, 1–73 (2022) Ling, Z., Liang, Y., Wang, Y., Shen, H., Xiao, L.: Adaptive extended piecewise histogram equalisation for dark image enhancement. IET Image Process 9(11), 1012–1019 (2015) Kumar Bhandari, A., Kandhway, P., Maurya, S.: Salp swarm algorithm-based optimally weighted histogram framework for image enhancement. IEEE Trans Instrum Measure 69(9), 6807–6815 (2020) Zhou, Y., Ye, J., Du, Y., Rashid Sheykhahmad, F.: New improved optimized method for medical image enhancement based on modified shark smell optimization algorithm. Sens Imaging 21(1), 1–22 (2020) Katircioglu, F.: A novel gray image enhancement using the regional similarity transformation function and dragonfly algorithm. El-Cezeri J Sci Eng 7(3), 1201–1219 (2020) Xue, H.: Low light image enhancement based on modified retinex optimized by fractional order gradient descent with momentum rbf neural network. Multimed Tools Appl 80(12), 19057–19077 (2021) Wang, Z., Bovik, A.C., Lu, L.: Why is image quality assessment so difficult? In: 2002 IEEE International conference on acoustics, speech, and signal processing. IEEE (2002) Rich F: Kodak lossless true color image suite. source: http://r0k. us/graphics/kodak, (1999) Singh Parihar, A., Verma, O.P., Khanna, C.: Fuzzy-contextual contrast enhancement. IEEE Trans Image Process 26(4), 1810–1819 (2017) Braik, M., Hammouri, A., Atwan, J., Al-Betar, M.A., Awadallah, M.A.: White shark optimizer: a novel bio-inspired meta-heuristic algorithm for global optimization problems. Knowl Based Syst 243, 108457 (2022) Kennedy, J., Eberhart, R.: Particle swarm optimization (pso). In: Proc IEEE international conference on neural networks. IEEE (1995) Mirjalili, S., Gandomi, A.H., Zahra Mirjalili, S., Saremi, S., Faris, H., Mohammad Mirjalili, S.: Salp swarm algorithm: a bio-inspired optimizer for engineering design problems. Adv Eng Soft 114, 163–191 (2017) Karaboga, D., Gorkemli, B., Ozturk, C., Karaboga, N.: A comprehensive survey: artificial bee colony (abc) algorithm and applications. Artif Intell Rev 42(1), 21–57 (2014) Faramarzi, A., Heidarinejad, M., Mirjalili, S., Gandomi, A.H.: Marine predators algorithm: a nature-inspired metaheuristic. Exp Syst Appl 152, 113377 (2020) Braik, M., Hashem Ryalat, M., Al-Zoubi, H.: A novel meta-heuristic algorithm for solving numerical optimization problems: Ali baba and the forty thieves. Neural Comput Appl 34(1), 409–455 (2022)