Listar por autoría "d9560cca-ec54-460f-8798-5af0217c70a5"
Mostrando ítems 1-7 de 7
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Filter banks for hyperspectral pixel classification of satellite images
Springer Verlag (Germany) (2009)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 ... -
Improving Hyperspectral Pixel Classification With Unsupervised Training Data Selection
Institute of Electrical and Electronics Engineers (IEEE) (2014)An unsupervised method for selecting training data is suggested here. The method is tested by applying it to hyperspectral land-use classification. The data set is reduced using an unsupervised band selection method and ...
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Influence of color spaces over texture characterization
Instituto Politécnico Nacional (Mèxic). Centro de Investigación en Computación (2008)Images are generally represented in the RGB color space. This is the model commonly used for most cameras and for displaying on computer screens. Nevertheless, the representation of color images using this color space has ...
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On the influence of spatial information for hyper-spectral satellite imaging characterization
Springer (2011)Land-use classification for hyper-spectral satellite images requires a previous step of pixel characterization. In the easiest case, each pixel is characterized by its spectral curve. The improvementof the spectral and ...
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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 ... -
Spectral–Spatial Pixel Characterization Using Gabor Filters for Hyperspectral Image Classification
Institute of Electrical and Electronics Engineers (IEEE) (2013)This paper 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 ...
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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 ...
