Pedro García-Sevilla

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Hyperspectral imaging involves large amounts of information. This paper presents a technique for dimensionality reduction to deal with hyperspectral images. The proposed method is based on a hierarchical clustering structure to group bands to minimize the intracluster variance and maximize the intercluster variance. This aim is pursued using information(More)
This letter presents a spectral–spatial pixel characterization method for hyperspectral images. The characterization is based on textural features obtained using Gabor filters over a selected set of spectral bands. This scheme aims at improving land-use classification results, decreasing significantly the number of spectral bands needed in order to reduce(More)
Feature selection and dimensionality reduction are crucial research fields in pattern recognition. This work presents the application of a novel technique on dimensionality reduction to deal with multispectral images. A distance based on mutual information is used to construct a hierarchical clustering structure with the multispectral bands. Moreover, a(More)
This paper proposes a new unsupervised approach for colour image segmentation. A hierarchy of image partitions is created on the basis of a function that merges spatially connected regions according to primary perceptual criteria. Likewise, a global function that measures the goodness of each defined partition is used to choose the best low-level perceptual(More)
Satellite hyperspectral imaging deals with heterogenous images containing different texture areas. Filter banks are frequently used to characterize textures in the image performing pixel classification. This filters are designed using different scales and orientations in order to cover all areas in the frequential domain. This work is aimed at studying the(More)
Four different texture classification methods (wavelet-based, co-occurrence matrices-based, 1D-histograms-based, and 1D Boolean model-based) are systematically compared and evaluated with respect to their performance in identifying textures from small and irregular samples. Two sets of 135 complex shape masks (symmetric and nonsymmetric) are created using(More)