Paper
9 March 1999 Calculation of fractal dimension in the presence of nonfractal clutter
Kenneth A. Herren, Don A. Gregory
Author Affiliations +
Abstract
The area of information processing has grown dramatically over the last 50 years. In the areas of image processing and information storage the technology requirements have far outpaced the ability of the community to meet demands. The need for faster recognition algorithms and more efficient storage of large quantities of data has forced the user to accept less than lossless retrieval of that data for analysis. In addition to clutter which is not the object of interest in the data set, often the throughput requirements forces the user to accept 'noisy' data and to tolerate the clutter inherent in that data. It has been shown that some of this clutter, both the unavoidable clutter (clouds, trees, etc.) as well as the noise introduced on the data by processing requirements can be modeled as fractal or fractal-like. Traditional methods, using Fourier deconvolution on these sources of noise in frequency space, lead to loss of signal and can, in many cases, completely eliminate the target of interest. One parameter used to characterize fractal-like noise, the fractal dimension, has been investigated and fractal dimension images are presented.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kenneth A. Herren and Don A. Gregory "Calculation of fractal dimension in the presence of nonfractal clutter", Proc. SPIE 3715, Optical Pattern Recognition X, (9 March 1999); https://doi.org/10.1117/12.341303
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KEYWORDS
Fractal analysis

Wavelets

Wavelet transforms

Data modeling

Data storage

Image processing

Transform theory

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