Nonlinear image operators, higher-order statistics,and the AND-like combinations of frequency components

Zetzsche C, Krieger G (2001)


Publication Type: Conference contribution

Publication year: 2001

Pages Range: 119-124

Conference Proceedings Title: 2nd Intl. Symp. Image and Signal Processing and Analysis

URI: https://elib.dlr.de/6003/

Abstract

The frequency domain plays a key role in the description of signals and systems. In the classical approaches, the individual frequency components are treated as independent: In linear systems, the superposition principle restricts the filtering to an OR-like processing of independent complex exponentials. Likewise, the classical second-order statistic (the powerspectrum) measures only the occurrence of each individual frequency component, independent of whether it occurs in a systematic combination with other components or not. This basic limitation can be overcome by the extension of the classical approaches to nonlinear systems and higher-order statistics, which makes it possible to selectively address AND-like combinations of frequency components. We measure which AND combinations are statistically most relevant in natural images, and investigate how this statistical structure can be exploited by nonlinear Volterra filters.

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APA:

Zetzsche, C., & Krieger, G. (2001). Nonlinear image operators, higher-order statistics,and the AND-like combinations of frequency components. In Loncaric S., Babic H. (Eds.), 2nd Intl. Symp. Image and Signal Processing and Analysis (pp. 119-124).

MLA:

Zetzsche, Christoph, and Gerhard Krieger. "Nonlinear image operators, higher-order statistics,and the AND-like combinations of frequency components." Proceedings of the 2nd Intl. Symp. Image and Signal Processing and Analysis Ed. Loncaric S., Babic H., 2001. 119-124.

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