
Proceedings Paper
Measuring Fractal Dimension: Morphological Estimates And Iterative OptimizationFormat | Member Price | Non-Member Price |
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Paper Abstract
An important characteristic of fractal signals is their fractal dimension. For arbitrary fractals, an efficient approach to evaluate their fractal dimension is the covering method. In this paper we unify many of the current implementations of covering methods by using morphological operations with varying structuring elements. Further, in the case of parametric fractals depending on a parameter that is in one-to-one correspondence with their fractal dimension, we develop an optimization method, which starts from an initial estimate and by iteratively minimizing a distance between the original function and the class of all such functions, spanning the quantized parameter space, converges to the true fractal dimension.
Paper Details
Date Published: 1 November 1989
PDF: 15 pages
Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); doi: 10.1117/12.970052
Published in SPIE Proceedings Vol. 1199:
Visual Communications and Image Processing IV
William A. Pearlman, Editor(s)
PDF: 15 pages
Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); doi: 10.1117/12.970052
Show Author Affiliations
Petros Maragos, Harvard University (United States)
Fang-Kuo Sun, The Analytic Sciences Corp. (United States)
Published in SPIE Proceedings Vol. 1199:
Visual Communications and Image Processing IV
William A. Pearlman, Editor(s)
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