Abstract

A method of adaptive, nonlinear filtering that enhances the features that separate two sets of images has been developed. The method uses the Hotelling trace criterion to find the optimal linear feature operator for the Fourier moduli of the images. This operator is then used as a filter in the Fourier domain such that the features that separate the two classes of objects are enhanced. We demonstrate the use of this filtering method to enhance texture features in simulated liver images from nuclear medicine, after using a training set of images to obtain the filter. We also demonstrate how this method of filtering can be used to reconstruct an object from a single photon-starved image of it, when the object contains a repetitive feature.

© 1987 Optical Society of America

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