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Classification of Clouds by the Eagle Strategy

Aicha Tekkouk(1*), H. Fizazi(2)

(1) Department of Computer Sciences, University of science and technology of Oran Mohamed Boudif, Algeria
(2) Department of Computer Sciences, University of science and technology of Oran Mohamed Boudif, Algeria
(*) Corresponding author


DOI: https://doi.org/10.15866/irease.v12i3.14647

Abstract


In this article a method of image processing used to extract the different regions of clouds, from infrared images, visible images and water vapour images of satellite METEOSAT Second Generation MSG is presented. This research addresses one of the main problems of vision by computer, image segmentation, using a new strategy called eagle strategy. The results obtained have showed the effectiveness of this strategy.
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Keywords


Remote Sensing; Clouds; Meteorological Image; Segmentation; Eagle Strategy; Firefly Algorithm; Lévy Walk

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References


Holton, J. R., & Hakim, G. J. (2012). An introduction to dynamic meteorology (Vol. 88). Academic press.

Haeffelin, M., Barthès, L., Bock, O., Boitel, C., Bony, S., Bouniol, D., Drobinski, P. (2005, February). SIRTA, a ground-based atmospheric observatory for cloud and aerosol research. In Annales Geophysicae (Vol. 23, No. 2, pp. 253-275).
https://doi.org/10.5194/angeo-23-253-2005

Kozoderov, V., Kondranin, T., Dmitriev, E., Hyperspectral Remote Sensing Imagery Processing Focused on Forest Applications, (2017) International Review of Aerospace Engineering (IREASE), 10 (5), pp. 298-307.
https://doi.org/10.15866/irease.v10i5.12893

Senthilkumaran, N., & Rajesh, R. (2009, October). Image segmentation-a survey of soft computingapproaches. In 2009 International Conference on Advances in Recent Technologies in Communication and Computing (pp. 844-846). IEEE.
https://doi.org/10.1109/artcom.2009.219

Ceppi, P., & Hartmann, D. L. (2016). Clouds and the atmospheric circulation response to warming. Journal of Climate, 29(2), 783-799.
https://doi.org/10.1175/jcli-d-15-0394.1

Tokuno, M., & Tsuchiya, K. (1994). Classification of cloud types based on data of multiple satellite sensors. Advances in Space Research, 14(3), 199-206.
https://doi.org/10.1016/0273-1177(94)90216-x

Amato, U., Antoniadis, A., Cuomo, V., Cutillo, L., Franzese, M., Murino, L., Serio, C. (2008). Statistical cloud detection from SEVIRI multispectral images. Remote Sensing of Environment, 112(3), 750-766.
https://doi.org/10.1016/j.rse.2007.06.004

Li, J., Menzel, W. P., Yang, Z., Frey, R. A., Ackerman, S. A. (2003). High-spatial-resolution surface and cloud-type classification from MODIS multispectral band measurements. Journal of Applied Meteorology, 42(2), 204-226.
https://doi.org/10.1175/1520-0450(2003)042<0204:hsrsac>2.0.co;2

Derrien, M., Le Gleau, H. (1999, September). Cloud classification extracted from AVHRR and GOES imagery. In Proc. 1999 EUMETSAT Meteorological Satellite Data User’s Conf (pp. 545-553).

Xia, M., Lu, W., Yang, J., Ma, Y., Yao, W., Zheng, Z. (2015). A hybrid method based on extreme learning machine and k-nearest neighbor for cloud classification of ground-based visible cloud image. Neurocomputing, 160, 238-249.
https://doi.org/10.1016/j.neucom.2015.02.022

Fong, S., Deb, S., & Yang, X. S. (2015). A heuristic optimization method inspired by wolf preying behavior. Neural Computing and Applications, 26(7), 1725-1738.
https://doi.org/10.1007/s00521-015-1836-9

Yapıcı, H., Çetinkaya, N. (2017). An improved particle swarm optimization algorithm using eagle strategy for power loss minimization. Mathematical Problems in Engineering, 2017.
https://doi.org/10.1155/2017/1063045

Yang, X. S. (2010). Nature-inspired metaheuristic algorithms. Luniver press.

Yang, X. S., Deb, S. (2010). Eagle strategy using Lévy walk and firefly algorithms for stochastic optimization. In Nature Inspired Cooperative Strategies for Optimization (NICSO 2010) (pp. 101-111). Springer, Berlin, Heidelberg.
https://doi.org/10.1007/978-3-642-12538-6_9

Talatahari, S., Gandomi, A. H., Yang, X. S., Deb, S. (2015). Optimum design of frame structures using the eagle strategy with differential evolution. Engineering Structures, 91, 16-25.
https://doi.org/10.1016/j.engstruct.2015.02.026

Viswanathan, G. M., Afanasyev, V., Buldyrev, S. V., Murphy, E. J., Prince, P. A., Stanley, H. E. (1996). Lévy flight search patterns of wandering albatrosses. Nature, 381(6581), 413.
https://doi.org/10.1038/381413a0

Reynolds, A. (2015). Liberating Lévy walk research from the shackles of optimal foraging. Physics of life reviews, 14, 59-83.
https://doi.org/10.1016/j.plrev.2015.03.002

Łukasik, S., Żak, S. (2009, October). Firefly algorithm for continuous constrained optimization tasks. In International conference on computational collective intelligence (pp. 97-106). Springer, Berlin, Heidelberg.
https://doi.org/10.1007/978-3-642-04441-0_8

Jensen, J. R., Lulla, K. (1987). Introductory digital image processing: a remote sensing perspective.

Lillesand, Thomas, Kiefer, Ralph W., Chipman, Jonathan. Remote sensing and image interpretation. John Wiley & Sons, 2014.

Bins, L. S. A., Fonseca, L. G., Erthal, G. J., Ii, F. M. (1996). Satellite imagery segmentation: a region growing approach. Simpósio Brasileiro de Sensoriamento Remoto, 8(1996), 677-680.

Fister, I., Fister Jr, I., Yang, X. S., Brest, J. (2013). A comprehensive review of firefly algorithms. Swarm and Evolutionary Computation, 13, 34-46.
https://doi.org/10.1016/j.swevo.2013.06.001

Barthelemy, P., Bertolotti, J., Wiersma, D. S. (2008). A Lévy flight for light. Nature, 453(7194), 495.
https://doi.org/10.1038/nature06948

Brown, C. T., Liebovitch, L. S., Glendon, R. (2007). Lévy flights in Dobe Ju/’hoansi foraging patterns. Human Ecology, 35(1), 129-138.
https://doi.org/10.1007/s10745-006-9083-4

Yang, X. S. (2010). Firefly algorithm, Levy flights and global optimization. In Research and development in intelligent systems XXVI (pp. 209-218). Springer, London.
https://doi.org/10.1007/978-1-84882-983-1_15

Voigt, A., Shaw, T. A. (2015). Circulation response to warming shaped by radiative changes of clouds and water vapour. Nature Geoscience, 8(2), 102.
https://doi.org/10.1038/ngeo2345

Menzel, P., Strabala, K. (1997). Cloud top properties and cloud phase algorithm theoretical basis document. University of Wisconsin--Madison.

Schumann, W., Stark, H., McMullan, K., Aminou, D., Luhmann, H. J. (2002). The MSG system. ESA bulletin, 11-14.

Bony, S., Stevens, B., Frierson, D. M., Jakob, C., Kageyama, M., Pincus, R., Watanabe, M. (2015). Clouds, circulation and climate sensitivity. Nature Geoscience, 8(4), 261.
https://doi.org/10.1038/ngeo2398

El Saleous, N. Z., Vermote, E. F., Justice, C. O., Townshend, J. R. G., Tucker, C. J., Goward, S. N. (2000). Improvements in the global biospheric record from the Advanced Very High Resolution Radiometer (AVHRR). International Journal of Remote Sensing, 21(6-7), 1251-1277.
https://doi.org/10.1080/014311600210164

Gherdaoui, S., Fizazi, H., Hybrid Approach for the Detection of Regions of a Satellite Image, (2017) International Review of Aerospace Engineering (IREASE), 10 (3), pp. 114-121.
https://doi.org/10.15866/irease.v10i3.11980

Kozoderov, V., Kondranin, T., Dmitriev, E., Hyperspectral Remote Sensing Imagery Processing Focused on Forest Applications, (2017) International Review of Aerospace Engineering (IREASE), 10 (5), pp. 298-307.
https://doi.org/10.15866/irease.v10i5.12893


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