Abstract
Satellites image segmentation is useful in a variety of fields. Professionals in related industries can gain a lot of important information by segmenting satellite images, but processing them is difficult due to the complex background and various locations of interest. The simplest basic picture segmentation approach is multilevel threshold segmentation, but the results can be unsatisfactory due to its computational complexity and high computation time. This paper presents an improved bald eagle search algorithm based on the standard bald eagle search algorithm. This method is used to find the best threshold values for the Renyi entropy multilevel threshold methods. To expand the diversity of the bald eagle population and the bald eagle's prey space, the strategy uses Chaotic Tent and Levy Fight method. The method is utilized to do multilevel segmentation of color satellite images, and the results suggest that it is capable of doing so. At the same time, this method has fewer iterations and can achieve better threshold values than typical methods such as standard bald eagle search optimization algorithm.
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The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
References
Resma, K.P.B., Nair, M.S.: Multilevel threshold for image segmentation using Krill Herd Optimization algorithm. J. King Saud Univ. Comput. Inf. Sci. (2021). https://doi.org/10.1016/j.jksuci.2018.04.007
Sowjanya, K., Injeti, S.K.: Investigation of butterfly optimization and gases Brownian motion optimization algorithms for optimal multilevel image threshold. Expert Syst. Appl. (2021). https://doi.org/10.1016/j.eswa.2021.115286
Liang, Z., Wang, Y.: Multilevel image threshold based on Renyi entropy using cuckoo search algorithm. Int. Symp. Intell. Comput. Appl. (2020). https://doi.org/10.1007/978-981-15-5577-0_31
Peng, L., Zhang, D.: An adaptive Lévy flight firefly algorithm for multilevel image threshold based on Rényi entropy. Deep Learn. IoT Emerg. Trends App. (2022). https://doi.org/10.1007/s11227-021-04150-3
Alsattar, H.A., Zaidan, A.A., Zaidan, B.B.: Novel meta-heuristic bald eagle search optimisation algorithm. Artif. Intell. Rev. (2019). https://doi.org/10.1007/s10462-019-09732-5
Acknowledgements
This work was supported by the National Engineering and Technology Research Center for Development and Utilization of Phosphate Resources Open Fund (No. NECP2022-11), and Yunnan Province Young Talents Project Fund (No. CCC21321247A), Funded by the Yunnan Provincial Department of Science and Technology (No. 202101AT070277).
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Chaoxi, L., Lifang, H., Songwei, H. et al. An improved bald eagle algorithm based on Tent map and Levy flight for color satellite image segmentation. SIViP 17, 2005–2013 (2023). https://doi.org/10.1007/s11760-022-02413-x
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DOI: https://doi.org/10.1007/s11760-022-02413-x