Title: Unsupervised feature reduction in image segmentation by local Karhunen-Loeve transform
Abstract: Proposes to reduce the dimensionality of feature vectors by using the principles of Karhunen-Loeve transform, (KL) applied to the feature images locally and globally. The reduction is achieved by choosing the resulting basis vectors which are closest to those of the classical KL transform. An efficient implementation technique using pyramids is proposed. Experimental results are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Publication Year: 2003
Publication Date: 2003-01-02
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 6
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