In this paper, we present an approach to the extraction and selection of robust features for classification of multispectral remote-sensing images. In particular, several robust features are proposed that, given a specific land-cover class, aim to exhibit an invariant behavior versus variations in the acquisition conditions of the images considered. In addition, a technique is presented, which is able to adaptively select the most robust features for a given problem.
Extraction and selection of robust features for classification of multispectral remote-sensing images
Bruzzone, Lorenzo;
1999-01-01
Abstract
In this paper, we present an approach to the extraction and selection of robust features for classification of multispectral remote-sensing images. In particular, several robust features are proposed that, given a specific land-cover class, aim to exhibit an invariant behavior versus variations in the acquisition conditions of the images considered. In addition, a technique is presented, which is able to adaptively select the most robust features for a given problem.File in questo prodotto:
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