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Textural Features for Hyperspectral Pixel Classification
(Springer Berlin Heidelberg, 2009)
Hyperspectral remote sensing provides data in large amounts from a wide range of wavelengths in the spectrum and the possibility of distinguish subtle differences in the image. For this reason, the process of band selection ...
Scale Analysis of Several Filter Banks for Color Texture Classification
(Springer Berlin Heidelberg, 2009)
We present a study of the contribution of the different scales used by several feature extraction methods based on filter banks for color texture classification. Filter banks used for textural characterization purposes are ...
Multi-spectral Texture Characterisation for Remote Sensing Image Segmentation
(Springer Berlin Heidelberg, 2009)
A multi-spectral texture characterisation model is proposed, the Multi-spectral Local Differences Texem – MLDT, as an affordable approach to be used in multi-spectral images that may contain large number of bands. The MLDT ...