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Journal Articles ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Year : 2015

Morpho-Spectral Recognition of Dense Urban Objects by Hyperspectral Imagery

Abstract

This paper presents a methodology for recognizing, identifying and classifying built objects in dense urban areas, using a morphospectral approach applied to VNIR/SWIR hyperspectral image (HySpex). This methodology contains several image processing steps: Principal Components Analysis and Laplacian enhancement, Feature Extraction of segmented build-up objects, and supervised classification from a morpho-spectral database (i.e. spectral and morphometric attributes). The Feature Extraction toolbox automatically generates a vector map of segmented buildings and an urban object-oriented morphometric database which is merged with an independent spectral database of urban objects. Each build-up object is spectrally identified and morphologically characterized thanks to the built-in morpho-spectral database.
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Dates and versions

hal-01349835 , version 1 (04-08-2016)

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  • HAL Id : hal-01349835 , version 1

Cite

Sébastien Gadal, Walid Ouerghemmi. Morpho-Spectral Recognition of Dense Urban Objects by Hyperspectral Imagery. ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015, XL-3/W3, pp.433-438. ⟨hal-01349835⟩
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