Dimensionality reduction of hyperspectral data based on centroid feature

Abstract

Hyperspectral data consists of large number of images in narrow contiguous wavelength bands. In To reduce dimension of data, centroid amplitude coordinate of area under the spectral response curve (SRC) has been proposed, in this study, as feature. The methodology is based on dividing the area under SRC into subsets and calculating the centroid amplitude… (More)
DOI: 10.1109/WHISPERS.2010.5594924

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@article{Ghosh2010DimensionalityRO, title={Dimensionality reduction of hyperspectral data based on centroid feature}, author={Jayanta Kumar Ghosh and Kriti Mukherjee}, journal={2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing}, year={2010}, pages={1-4} }