Print Email Facebook Twitter Information extraction and dimensionality reduction of hyperspectral datasets through spectral region analyses Title Information extraction and dimensionality reduction of hyperspectral datasets through spectral region analyses Author Hosseini Aria, S.E. (TU Delft Optical and Laser Remote Sensing) Contributor Menenti, M. (promotor) Gorte, B.G.H. (copromotor) Degree granting institution Delft University of Technology Date 2018-05-14 Abstract Hyperspectral images present detailed spectral information of every pixel inthe images where the spectral signal is sampled in hundreds of narrow andcontiguous spectral channels, usually covering the 400-2500 nm spectral regionwhere sunlight reflected by the Earth can be measured. Earth observation systemsacquire spectral information by imaging spectrometers mounted in a platformflying over the Earth. Recent advances in technology make it possible to haveminiaturised hyperspectral satellites in orbit. Much of the work presented in thisthesis was inspired by the study of a CubeSat equipped with an imagingspectrometer and capable of onboard data processing. To reference this document use: https://doi.org/10.4233/uuid:72b4a11a-d394-433a-b1d1-1f40eb8bd8c6 ISBN 978-94-6295-935-4 Part of collection Institutional Repository Document type doctoral thesis Rights © 2018 S.E. Hosseini Aria Files PDF PhD_thesis_ReadyForPrint_ ... niAria.pdf 5.79 MB Close viewer /islandora/object/uuid:72b4a11a-d394-433a-b1d1-1f40eb8bd8c6/datastream/OBJ/view