Paper
Empirical multiresolution models applicable to gray-level image processing☆

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Abstract

This paper deals with empirical multiresolution linear models intended for image processing. Such models contain information about gray-level composition of regions in the image. First, a general method for building these models from samples of selected images is described. Then, a measure of their quality, based on the Jensen-Shannon divergence, is introduced. This divergence is also used as a distance measure for classifying images. Applications in non-linear image filtering are provided, giving better result than classical median filtering.

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This work was partially supported by grant TIC91-646 from the DGCYT of the Spanish Government.

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Copyright © 1997 Published by Elsevier B.V.