elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

A data-driven approach to quality assessment for hyperspectral systems

Kerr, Gregoire and Fischer, Christian and Reulke, Ralf (2015) A data-driven approach to quality assessment for hyperspectral systems. Computers & Geosciences, 83, pp. 100-109. Elsevier. DOI: 10.1016/j.cageo.2015.07.004 ISSN 0098-3004

Full text not available from this repository.

Official URL: http://www.sciencedirect.com/science/article/pii/S0098300415300121

Abstract

The increasing use of products based on airborne hyperspectral data for decision-making calls for a thorough quality assessment. Due to the complexity of the corresponding processing chain, as well as the variety of physical processes involved, such a task is usually only performed in specific cases and on specific parts of the processing chain. In particular, the quality assessment of data-products is still an open issue. A generic quality assessment method – based on an cross-comparison of errors – is proposed in this paper. Airborne hyperspectral – also called imaging spectroscopy – data is commonly acquired by means of whisk- or push-broom sensors, and requires several strips – or flight-lines – to cover the full area of interest. A comparison of the discrepancies between overlapping parts of these flight-lines is used to retrieve an assessment of the measurement reproducibility. This mapping can be performed on pre-processed data which avoids the need to separately investigate all input parameters and their associated models, hence bypassing the ‘curse of dimensionality’. The first step involves retrieving the pairs of pixels corresponding to the same areas imaged from overlapping flight-lines. Even when an ortho-rectification of the data has been carried out, various phenomena, such as errors in the underlying digital elevation model, lead to flight-line mis-registrations. For heterogeneous land-covers, a pixel to pixel registration step has therefore to be performed in order to allow a cross-comparison of pixels: a suitable methodology is proposed along with its validation. The second step corresponds to the relative errors analysis itself. A set of quantitative quality indicators – corresponding to different types of land-products – is presented. These methods are illustrated with an example along with a discussion. This approach can be used on any reasonably well contrasted scene to retrieve a quality assessment for any raster product independently of its data type as well as for the reflectance data itself.

Item URL in elib:https://elib.dlr.de/97420/
Document Type:Article
Title:A data-driven approach to quality assessment for hyperspectral systems
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Kerr, GregoireGregoire.Kerr (at) dlr.deUNSPECIFIED
Fischer, ChristianC.Fischer (at) dlr.deUNSPECIFIED
Reulke, Ralfralf.reulke (at) dlr.deUNSPECIFIED
Date:2015
Journal or Publication Title:Computers & Geosciences
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:83
DOI :10.1016/j.cageo.2015.07.004
Page Range:pp. 100-109
Publisher:Elsevier
ISSN:0098-3004
Status:Published
Keywords:Airborne remote sensing; Hyperspectral; Imaging spectroscopy; Quality assessment; HySpex
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Spektrometrische Verfahren und Konzepte der Fernerkundung (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface
Institute of Optical Sensor Systems > Optics, Calibration and Validation
Deposited By: Kerr, Dr Grégoire Henry Gérard
Deposited On:22 Jul 2015 11:09
Last Modified:08 Mar 2018 18:18

Repository Staff Only: item control page

Browse
Search
Help & Contact
Information
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.