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Proceedings Paper

Determining the fractal dimension of scenes and digital signals using ROSETA and other novel approaches
Author(s): Holger M. Jaenisch; Philip E. Barton; R. T. Carruth
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Paper Abstract

The use of fractal statistics for characterizing and synthesizing scenes and signals has in recent time been demonstrated as feasible. Traditionally global fractal dimensions based on morphological coverings were used to quantify the texture of sampled data sets. This texture could be used to describe the second order statistics in 2D scenes or in the jaggedness and fine structure of time series. With the realization of the benefits of fractal analysis has come a need for faster and more efficient computational algorithms. ROSETA is an algorithm which yields substantial computational performance improvements by calculating entropy based statistics instead of morphological geometric statistics. ROSETA may be used as a robust general purpose analytical tool and several examples of its implementation are described.

Paper Details

Date Published: 3 September 1993
PDF: 18 pages
Proc. SPIE 1955, Signal Processing, Sensor Fusion, and Target Recognition II, (3 September 1993); doi: 10.1117/12.155001
Show Author Affiliations
Holger M. Jaenisch, Nichols Research Corp. (United States)
Philip E. Barton, Nichols Research Corp. (United States)
R. T. Carruth, U. S. Army Space and Strategic Defense Command (United States)


Published in SPIE Proceedings Vol. 1955:
Signal Processing, Sensor Fusion, and Target Recognition II
Ivan Kadar; Vibeke Libby, Editor(s)

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