Wavelet-Based Fractal Signature Analysis forAutomatic Target

Texture measures o er 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 gray scale texture classi cation. This paper introduces a new multichannel texture model that characterizes patterns as 2-dimensional functions in a Besov space. The wavelet-based fractal signature generates an n-dimensional surface, which is used for classication. Results of some experimental studies are presented demonstrating the usefulness of this texture measure.

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