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Proceedings Paper

Nonparametric Estimation Of Fractal Dimension
Author(s): Michael C. Stein; Keith D. Hartt
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Paper Abstract

Nonparametric techniques for estimating fractal dimension are discussed. These techniques are shown to be more robust and efficient when compared with the standard least-squares estimation techniques currently in use. In particular, two alternative nonparametric schemes are presented and their use in image modeling applications is discussed. Theoretical and practical reasons are given to indicate why nonparametric methods lead to improved dimension estimation algorithms. Test results are provided that demonstrate the potential of these methods for use in dimension estimation problems, such as image modeling, where small sample sizes are necessary.

Paper Details

Date Published: 25 October 1988
PDF: 6 pages
Proc. SPIE 1001, Visual Communications and Image Processing '88: Third in a Series, (25 October 1988); doi: 10.1117/12.968946
Show Author Affiliations
Michael C. Stein, The Analytic Sciences Corporation (United States)
Keith D. Hartt, The Analytic Sciences Corporation (United States)


Published in SPIE Proceedings Vol. 1001:
Visual Communications and Image Processing '88: Third in a Series
T. Russell Hsing, Editor(s)

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