3 September 1993 Determining the fractal dimension of scenes and digital signals using ROSETA and other novel approaches
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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.
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Holger M. Jaenisch, Holger M. Jaenisch, Philip E. Barton, Philip E. Barton, R. T. Carruth, R. T. Carruth, } "Determining the fractal dimension of scenes and digital signals using ROSETA and other novel approaches", Proc. SPIE 1955, Signal Processing, Sensor Fusion, and Target Recognition II, (3 September 1993); doi: 10.1117/12.155001; https://doi.org/10.1117/12.155001
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