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Feature fusion of hyperspectral and lidar data using extinction profiles and total variation

Ghamisi, Pedram and Rasti, Behnood and Zhu, Xiaoxiang (2017) Feature fusion of hyperspectral and lidar data using extinction profiles and total variation. In: IEEE 2017 Geoscience and Remote Sensing Symposium (IGARSS), pp. 2621-2624. IEEE Xplore. IGARSS 2017, 23.-28. Juli 2017, Fort Worth, Texas, USA. doi: 10.1109/IGARSS.2017.8127532. ISSN 2153-7003.

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Official URL: http://ieeexplore.ieee.org/document/8127532/


To improve the classification of hyperspectral images, this paper proposes an approach for multi-sensor data fusion of LiDAR and hyperspectral data using extinction profiles and Orthogonal Total Variation Component Analysis (OTVCA). Results on the benchmark Houston data indicate the superior performance of the proposed approach compared to other approaches used in the experiments based on classification accuracies.

Item URL in elib:https://elib.dlr.de/118209/
Document Type:Conference or Workshop Item (Speech)
Title:Feature fusion of hyperspectral and lidar data using extinction profiles and total variation
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Ghamisi, PedramPedram.Ghamisi (at) dlr.deUNSPECIFIED
Rasti, BehnoodKeilir Institute of TechnologyUNSPECIFIED
Zhu, Xiaoxiangxiao.zhu (at) dlr.deUNSPECIFIED
Date:July 2017
Journal or Publication Title:IEEE 2017 Geoscience and Remote Sensing Symposium (IGARSS)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
DOI :10.1109/IGARSS.2017.8127532
Page Range:pp. 2621-2624
Publisher:IEEE Xplore
Keywords:multi-sensor data fusion, hyperspectral data, lidar data, extinction profiles, orthogonal total variation
Event Title:IGARSS 2017
Event Location:Fort Worth, Texas, USA
Event Type:international Conference
Event Dates:23.-28. Juli 2017
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, R - Vorhaben hochauflösende Fernerkundungsverfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Zielske, Mandy
Deposited On:12 Jan 2018 14:47
Last Modified:31 Jul 2019 20:15

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