1 January 1998 Wavelet-based fractal signature analysis for automatic target recognition
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Optical Engineering, 37(1), (1998). doi:10.1117/1.601844
Abstract
Texture measures offer a means of detecting targets in background clutter that has similar spectral characteristics. Our previous studies demonstrated that the ‘‘fractal signature’’ (a feature set based on the fractal surface area function) is very accurate and robust for grayscale texture classification. This paper introduces a new multichannel texture model that characterizes patterns as 2-D functions in a Besov space. The wavelet-based fractal signature generates an n-dimensional surface, which is used for classification. Results of some experimental studies are presented demonstrating the usefulness of this texture measure.
Fausto Espinal, Terrance L. Huntsberger, Bjorn D. Jawerth, Toshiro Kubota, "Wavelet-based fractal signature analysis for automatic target recognition," Optical Engineering 37(1), (1 January 1998). http://dx.doi.org/10.1117/1.601844
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KEYWORDS
Fractal analysis

Image segmentation

Wavelet transforms

Wavelets

Target detection

Feature extraction

Image classification

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