Information extraction and dimensionality reduction of hyperspectral datasets through spectral region analyses

Enayat Hosseini Aria

Research output: ThesisDissertation (TU Delft)

243 Downloads (Pure)

Abstract

Hyperspectral images present detailed spectral information of every pixel in
the images where the spectral signal is sampled in hundreds of narrow and
contiguous spectral channels, usually covering the 400-2500 nm spectral region
where sunlight reflected by the Earth can be measured. Earth observation systems
acquire spectral information by imaging spectrometers mounted in a platform
flying over the Earth. Recent advances in technology make it possible to have
miniaturised hyperspectral satellites in orbit. Much of the work presented in this
thesis was inspired by the study of a CubeSat equipped with an imaging
spectrometer and capable of onboard data processing.
Original languageEnglish
Awarding Institution
  • Delft University of Technology
Supervisors/Advisors
  • Menenti, M., Supervisor
  • Gorte, Ben, Advisor
Award date14 May 2018
Electronic ISBNs978-94-6295-935-4
DOIs
Publication statusPublished - 2018

Fingerprint

Dive into the research topics of 'Information extraction and dimensionality reduction of hyperspectral datasets through spectral region analyses'. Together they form a unique fingerprint.

Cite this