350 rub
Journal Information-measuring and Control Systems №9 for 2009 г.
Article in number:
Comparative analysis of fractal dimension estimation methods of 2-D signals
Authors:
A. B. Russkin
Abstract:
In the paper the questions of fractal dimension measurement with different methods and comparative analysis of methods with respect to estimation accuracy and time complexity, depending on observation window size, given fractal dimension and simulating algorithms of fractal surface, are considered. Twelve most common estimation methods to measure fractal dimension are used: Box counting, Triangular prism, Variogram, Isorithm, Power spectrum, Walking divider, Probability, Blanket, Pentland-s, Directional dimension, Information dimension and Correlation dimension. Comparative analysis of methods is based on a stochastic fractal reflected surface model - the two-dimensional fractional Brownian motion. Realizations of the model are obtained using the following simulation algorithms: sequential random addi-tion algorithm, midpoint displacement algorithm and fractal Fourier-filtering algorithm. Statistical estimates of mean, variance, standard deviation, and total fractal dimension measurement error of methods de-pending upon observation window size, given fractal dimension and simulating algorithms of fractal surface are calculated. Comparative analysis of discussed methods based on suggested rating estimation system is carried out. The best of considered methods is found - directional fractal dimension method.
Pages: 10-19
References
  1. Mandelbrot, B. B. The Fractal Geometry of Nature. N. Y.: Freeman, 1982.
  2. Потапов А. А. Фракталы в радиофизике и радиолокации: Топология выборки. М.: Университетскаякнига. 2005.
  3. Pentland, A. P., Fractal-Based Description of Natural Scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1984. V. 6. No. 6. P. 661-674.
  4. Lo, T., Leung, H., Litva, J., and Haykin S., Fractal Characterization of Sea-scattered Signals and Detection of Sea-surface Targets. IEE Proceedings, Part F: Radar and Signal Processing. 1993. V. 140. No. 4. P. 243-250.
  5. Tzeng, Y. C., Chu, D. M., Wu, M. F., Kun-Shan Chen Automatic detection of targets using fractal dimension. IEEE Geosciences and Remote Sensing Symposium. 2005. V. 3.
  6. Salmasi, M., Modarres-hashemi, M., Nayebi, M. M., Performance Analysis of Fractal Detector for General Model of HRR Signals. RADAR 2004. International Conference on Radar Systems.
  7. Kinsner, W., A unified approach to fractal dimensions. Fourth IEEE Conference on Cognitive Informatics. 2005.
  8. Sun, W., Xu, G., Gong, P., Liang, S., Fractal analysis of remotely sensed images: A review of methods and applications. International Journal of Remote Sensing. 2006. V. 27. No 22.
  9. Jansson, S., Evaluation of Methods for Estimating Fractal Properties of Intensity Images. Master-s Thesis in Computing Science, Umea University. Sweden. October 30. 2006.
  10. Liu, Tao, Gong, Yaohuan, Wei, Min, Li, Jun, Fractal Features and Detection of Meteor Interference in OTHR. Radar 2006. CIE-06, International Conference on. 16-19 October 2006. P. 1-5.
  11. Pesquet-Popescu, B., Vehel, J. L., Stochastic fractal models for image processing. IEEE Signal Processing Magazine. 2002. V. 19. No. 5.
  12. Кроновер Р. М. Фракталы и хаос в динамических системах. Основы теории. М.: Постмаркет, 2000.
  13. Шелухин О. И., Тенякшев А. М., Осин А. В. Фрактальные процессы в телекоммуникациях. М.: Радиотехника. 2003.
  14. Сосулин Ю. Г. Теоретические основы радиолокации и радионавигации. М.: Радио и связь. 1992.
  15. Русскин А. Б. Сравнительный анализ методов измерения фрактальной размерности. 11-я Международная научно-техническая конференция и выставка «Цифровая Обработка Сигналов и ее Применение». 25-27 марта 2009 г. С. 346-348.
  16. Русскин А. Б. Исследование методов оценки фрактальной размерности. ? 2-я Всероссийская конференция ученых, молодых специалистов и студентов «Информационные технологии в авиационной и космической технике-2009». 20-24 апреля 2009 г., Москва. Тез. докл. М.: МАИ-ПРИНТ. 2009. C 51-52.