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Introducing DLR Hysu-A Benchmark Dataset for Spectral Unmixing

Cerra, Daniele and Pato, Miguel and Alonso, Kevin and Köhler, Claas Henning and Schneider, Mathias and de los Reyes, Raquel and Carmona, Emiliano and Richter, Rudolf and Kurz, Franz and Müller, Rupert and Reinartz, Peter (2023) Introducing DLR Hysu-A Benchmark Dataset for Spectral Unmixing. In: 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023, pp. 1008-1011. IGARSS 2023, 2023-07-16 - 2023-07-21, Pasadena, US. doi: 10.1109/igarss52108.2023.10281975. ISBN 979-835032010-7. ISSN 2153-6996.

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Official URL: https://ieeexplore.ieee.org/document/10281975

Abstract

The DLR HyperSpectral Unmixing (DLR HySU) open benchmark dataset includes airborne hyperspectral and RGB imagery of targets of different materials and sizes on a homogeneous background, complemented by simultaneous ground-based reflectance measurements. The dataset allows assessing dimensionality estimation, endmember extraction with and without pure pixel assumption, and abundance estimation in the frame of spectral unmixing applications, enabling estimations at sub-pixel level. This paper presents the first works in the literature using the dataset, which demonstrate that DLR HySU is filling a gap regarding validation using real imaging spectrometer data with accurately measured targets.

Item URL in elib:https://elib.dlr.de/199205/
Document Type:Conference or Workshop Item (Speech)
Title:Introducing DLR Hysu-A Benchmark Dataset for Spectral Unmixing
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Cerra, DanieleUNSPECIFIEDhttps://orcid.org/0000-0003-2984-8315UNSPECIFIED
Pato, MiguelUNSPECIFIEDhttps://orcid.org/0000-0003-0111-0861UNSPECIFIED
Alonso, KevinUNSPECIFIEDhttps://orcid.org/0000-0003-2469-8290UNSPECIFIED
Köhler, Claas HenningUNSPECIFIEDhttps://orcid.org/0000-0003-0127-935XUNSPECIFIED
Schneider, MathiasUNSPECIFIEDhttps://orcid.org/0000-0001-6698-3781147014250
de los Reyes, RaquelUNSPECIFIEDhttps://orcid.org/0000-0003-0485-9552UNSPECIFIED
Carmona, EmilianoUNSPECIFIEDhttps://orcid.org/0009-0008-8998-7310UNSPECIFIED
Richter, RudolfUNSPECIFIEDhttps://orcid.org/0000-0002-8499-4780UNSPECIFIED
Kurz, FranzUNSPECIFIEDhttps://orcid.org/0000-0003-1718-0004UNSPECIFIED
Müller, RupertUNSPECIFIEDhttps://orcid.org/0000-0002-3288-5814UNSPECIFIED
Reinartz, PeterUNSPECIFIEDhttps://orcid.org/0000-0002-8122-1475UNSPECIFIED
Date:July 2023
Journal or Publication Title:2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
DOI:10.1109/igarss52108.2023.10281975
Page Range:pp. 1008-1011
ISSN:2153-6996
ISBN:979-835032010-7
Status:Published
Keywords:Spectral unmixing, benchmark dataset, dimensionality reduction, endmember extraction, abundance estimation, HySpex
Event Title:IGARSS 2023
Event Location:Pasadena, US
Event Type:international Conference
Event Start Date:16 July 2023
Event End Date:21 July 2023
Organizer:IEEE
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Optical remote sensing
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Remote Sensing Technology Institute > Experimental Methods
Deposited By: Cerra, Daniele
Deposited On:20 Nov 2023 13:06
Last Modified:01 Sep 2024 03:00

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