Abstract

With regard to classical image transformations, the Karhunen–Loève transform is based on the statistical analysis of signal or image data. We propose using it to analyze and recognize the content of images generated in near-field microscopy. It is shown that such a transform is an efficient tool for separating actual information from noise without reducing the spatial-frequency band.

© 1996 Optical Society of America

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