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Improved feature extraction by use of a joint wavelet transform correlator

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Abstract

A new joint wavelet transform correlation-based technique is proposed for feature extraction such as the detection of edges in an unknown input scene. We exploited a modified version of the Roberts and the Sobel wavelet filters as reference images for extracting the edges of an unknown input scene. The performance of the proposed technique with the aforementioned wavelet filters is evaluated and compared by use of numerical simulations. For noise-free input scenes the Roberts wavelet filter was found to yield a superior output compared with that of the Sobel wavelet filter. However, for noisy input scenes the Sobel wavelet filter was found to yield a better output compared with the Roberts wavelet filter.

© 1998 Optical Society of America

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