Article information

2024 , Volume 29, ¹ 1, p.86-92

Kalayda V.T., Shaposhnikov A.I.

The modification of algorithms for the estimation of the fractal dimension for clouds images

The research addresses the development of methodology for estimating the fractal dimension of cloud formations. Images of the Earth’s cloud cover contain superimposed and partially overlapped different types of cloud cover. Taking into account that each type of cloudiness has different values of coefficients for radiation attenuation, the problem of separating cloud types is the most important when assessing the radiation balance. The most important feature used in the classification of cloudiness is the fractal dimension. At the same time, the estimates obtained by using “modern” methods and algorithms for estimating the fractal dimension significantly depend on the “positioning” of the object. The paper proposes an effective (in terms of accuracy) method for estimating the fractal dimension, which is invariant with respect to the “positioning” of an object.

[link to elibrary.ru]

Keywords: box counting, cloud, fractal dimension, estimate, error

doi: 10.25743/ICT.2024.29.1.008

Author(s):
Kalayda Vladimir Timofeevich
Dr. , Professor
Position: Professor
Office: National Research Tomsk State University
Address: 634050, Russia, Tomsk, 36 Lenin Aven.
Phone Office: (3822)492242
E-mail: kalaida49@mail.ru
SPIN-code: 8384-7021

Shaposhnikov Albert Igorevich
PhD. , Associate Professor
Position: Associate Professor
Office: National Research Tomsk State University
Address: 634050, Russia, Tomsk, 36 Lenin Aven.
Phone Office: (3822)492242
E-mail: albertelena@mail.ru
SPIN-code: 6501-4685

References:
1. Brevik I., Shapovalov A.V. Effects of low concentration in aqueous solutions within the fractal approach. Russian Physics Journal. 2022; 65(2):197–207.

2. Magomedova D.I., Sheluhin O.I. Fractal models and algorithms for creating a protective marking for integrity and authenticity bitmap images. Systems of Signal Synchronization, Generating and Processing. 2020; 11(1):57–67. (In Russ.)

3. Sheluhin O.I., Magomedova D.I. Analysis of methods for calculating the fractal dimension of color and grayscale images. High-Tech in Earth Space Research. 2017; 9(6):6–16. (In Russ.)

4. Moisy F. Boxcount. 2008. Available at: https://www.mathworks.com/matlabcentral/fileexchange/13063-boxcount (accessed 04.07.2022).

5. Costa A. Hausdorff (Box-Counting) Fractal Dimension. 2022. Available at: https://www.mathworks.com/matlabcentral/fileexchange/30329-hausdorff-box-counting-fractal-dimension (accessed 04.07.2022).

6. PVSM Vychislenie fraktal’noy razmernosti Minkovskogo dlya ploskogo izobrazheniya [Calculation of Minkowski fractal dimension for a flat image]. 2014. Available at: https://www.pvsm.ru/matematika/52344. (In Russ.)

7. Mandelbrot D. The fractal geometry of nature. Moscow: Institute of Computer Research; 2002: 605. (In Russ.)

8. Minkowski Bouligand dimension. Wikipedia. Free Encyclopedia. Available at: https://en.wikipedia.org/wiki/Minkowski_Bouligand_dimension (accessed 04.07.2022).

9. Otsu N. A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics. 1979; 9(1):62–66. DOI:10.1109/TSMC.1979.4310076.

10. Monitoring atmosfery i podstilayushchey poverkhnosti. Panoramno-opticheskaya stantsiya TomSky 2022 [Monitoring of the atmosphere and underlying surface. Panoramic optical station TomSky 2022]. Available at: https://sky.iao.ru/gallery/2015.07.01__00_15_41.225.jpg. (In Russ.)

11. Kalaida V.T. Planirovanie eksperimeta. Metody obrabotki rezul’tatov eksperimenta i osnovy matematicheskoy teorii planirovaniya eksperimenta [Planning the experiment. Methods for processing experimental results and the fundamentals of the mathematical theory of experiment planning].
Tomsk: Izdatel’stvo Tomskogo Universiteta; 1997: 93. (In Russ.)

12. Shaposhnikov A.I. Tsifrovoe opisanie mnozhestva pri komp’yuternoy obrabotke [Digital description of a set during computer processing]. Sbornik Trudov IX Mezhdunarodnoy Nauchno-Prakticheskoy Konferentsii. Tomsk; 2021: 276–277. (In Russ.)

13. Selivanov M.S., Fridman A.E., Kudryashova Zh.F. Quality of measurements: metrological reference book. Leningrad: Lenizdat; 1987: 403. (In Russ.)

Bibliography link:
Kalayda V.T., Shaposhnikov A.I. The modification of algorithms for the estimation of the fractal dimension for clouds images // Computational technologies. 2024. V. 29. ¹ 1. P. 86-92
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