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Performance Improvement of Fractal Dimension Estimator Based on a New Sampling Method
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 Title & Authors
Performance Improvement of Fractal Dimension Estimator Based on a New Sampling Method
Jin, Gang-Gyoo; Choi, Dong-Sik;
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Fractal theory has been widely used to quantify the complexity of remotely sensed digital elevation models and images. Despite successful applications of fractals to a variety of fields including computer graphics, engineering and geosciences, the performance of fractal estimators depends highly on data sampling. In this paper, we propose an algorithm for computing the fractal dimension based on the triangular prism method and a new sampling method. The proposed sampling method combines existing two methods, that is, the geometric step method and the divisor step method to increase pixel utilization. In addition, while the existing estimation methods are based on window, the proposed method expands to window. The proposed method is applied to generated fractal DEM, Brodatz's image DB and real images taken in the campus to demonstrate its feasibility.
digital elevation model(DEM);fractal dimension;data sampling;triangular prism method;
 Cited by
Anand, V. B.(1993), Computer Graphics and Geometric Modeling for Engineers, John Wiley & Sons.

Arakawa, K. and Krotkov, E.(1996), "Fractal Modeling of Natural Terrain: Analysis and Surface Reconstruction with Range Data", Graphical Models and Image Processing, Vol. 58, No. 5, pp. 413-436. crossref(new window)

"Brodatz Images(2013), University of Southern California, Signal and Image Processing Institute,".

Clarke, C.(1986), "Computation of the Fractal Dimension of Topographic Surfaces Using The Triangular Prism Surface Area Method," Computers & Geosciences, Vol. 12, No. 5, pp. 713-722. crossref(new window)

Emerson, C. W., Lam, N. S.-N. and Quattrochi, D. A.(2005), "A comparison of local variance, fractal dimension, and Moran's I as aids to multispectral image classification", Int. J. of Remote Sensing, Vol. 26, No. 8, pp. 1575-1588. crossref(new window)

Jin, G. and Kim, H.(2011), "Elevation Restoration of Natural Terrains Using the Fractal Technique", Journal of Navigation and Port Research, Vol. 35, No. 1, pp. 51-56. crossref(new window)

Ju, W. and Lam, N. S.-N.(2009), "An improved algorithm for computing local fractal dimension using the triangular prism method", Computers & Geosciences, Vol. 35, No. 6, pp. 1224-1233. crossref(new window)

Mandelbrot, B. B.(1967), "How Long Is the Coast of Britain? Statistical Self-Similarity and Fractional Dimension", Science, Vol. 156, No. 3775, pp. 636-638. crossref(new window)

Pokorny, C.(1994), Computer Graphics an Objected-Oriented Approach to the Art and Science, Franklin, Beedle & Associates Inc., Wilsonville, Oregon.

Saupe, D.(1988), Algorithms for Random Fractals, The Science of Fractal Images, In H. -O. Peitgen and D. Saupe, Editors, Springer-Verlag.

Wang, Gang and Ma, Ji(2010), "Fractal Analysis to the Robot during the Application of Defect Detection", Proc. of 2010 3rd IEEE Int. Conf. on Computer Science and Information Technology(ICCSIT), Chengdu, China, pp. 656-658.

Yang, S. et al.(2002), "A Study on the 3-D Digital Modelling of the Sea Bottom Topography", J. of the Korea Institute of Military Science and Technology, Vol. 5, No. 2, pp. 50-61.