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Satellite Image Augmentation via Seamless Instance Blending for Building Damage Segmentation

Gapp, Sebastian and Merkle, Nina and Henry, Corentin (2023) Satellite Image Augmentation via Seamless Instance Blending for Building Damage Segmentation. In: International Geoscience and Remote Sensing Symposium (IGARSS), pp. 5182-5185. IGARSS 2023, 16.-21. Jul. 2023, USA, Pasadena. doi: 10.1109/IGARSS52108.2023.10282254.

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Official URL: https://2023.ieeeigarss.org/view_paper.php?PaperNum=2510


When a natural disaster strikes, humanitarian organizations require a rapid and precise localization of damaged buildings to coordinate rescue missions and allocate relief goods. Current approaches rely on a manual comparison of pre- and post-disaster satellite imagery to generate a reliable damage map for selected areas. The main obstacle to using machine learning methods to automate this time-consuming analysis is the small amount of labeled training data. To generate more diverse datasets, we propose an augmentation procedure to seamlessly insert buildings into optical satellite imagery. We analyzed how different compositions of inserted buildings affect the segmentation of building damage and showed how the proposed augmentation technique can be used to significantly improve the performance of building damage segmentation networks.

Item URL in elib:https://elib.dlr.de/197268/
Document Type:Conference or Workshop Item (Poster)
Title:Satellite Image Augmentation via Seamless Instance Blending for Building Damage Segmentation
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Merkle, NinaUNSPECIFIEDhttps://orcid.org/0000-0003-4177-1066UNSPECIFIED
Date:16 July 2023
Journal or Publication Title:International Geoscience and Remote Sensing Symposium (IGARSS)
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 5182-5185
Keywords:Deep Learning, Data Augmentation, Building Damage Assessment, Satellite Images
Event Title:IGARSS 2023
Event Location:USA, Pasadena
Event Type:international Conference
Event Dates:16.-21. Jul. 2023
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
Deposited By: Gapp, Sebastian
Deposited On:21 Sep 2023 10:03
Last Modified:26 Oct 2023 15:54

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