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Automatic Coastline Detection in Non-locally Filtered TanDEM-X Data

Schmitt, Michael and Wei, Lingyun and Zhu, Xiao Xiang (2015) Automatic Coastline Detection in Non-locally Filtered TanDEM-X Data. In: Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2015, pp. 1036-1039. IEEE Xplore. IGARSS 2015, 26.-31. Jul. 2015, Mailand, Italien.

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Official URL: http://www.igarss2015.org/Papers/AcceptedPapers.asp

Abstract

The detection of coastlines in SAR imagery has been studied for more than two decades now. Whereas the first works were based on the exploitation of amplitude imagery and the corresponding need to deal with speckle noise [1, 2, 3], with the ERS-1/2 tandem configuration also coherence maps started to be used as input [4, 5]. Based on the insights gained on these experiments, later the authors began to exploit both amplitude and coherence imagery simultaneously [6, 7], finally giving way to the first approach using the original complex SAR data for statistically motivated coastline extraction [8]. In any case, one of the core problems for coastline detection from SAR datasets is the comparably high level of noise, which degrades the grayscale input imagery, be it amplitude or coherence. In order to solve this deficiency, an abundance of filtering techniques have been proposed over the years, among which the most sophisticated are based on the recently introduced non-local paradigm. Since Deledalle et al. proposed the NL-InSAR algorithm designed for interferometric multilooking in 2011 [9], novel denoising qualities can be achieved. In [10] and [11], it was already shown that the final DEM to be created during the German TanDEM-X mission [12] can be improved significantly by a specifically optimized implementation of NL-InSAR. This paper proposes a fully automatic framework for coastline extraction from non-locally filtered TanDEM-X data based on unsupervised active contours. It is therefore structured into two main parts: First, the non-local filtering framework will be described. Second, the active contours algorithm for coastline detection will be described. Finally, some preliminary experimental results processed from an interferometric TerraSAR-X dataset showing the skerry coast in the area of Stockholm, Sweden, will be demonstrated.

Item URL in elib:https://elib.dlr.de/97459/
Document Type:Conference or Workshop Item (Speech)
Title:Automatic Coastline Detection in Non-locally Filtered TanDEM-X Data
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Schmitt, MichaelTUM-LMFUNSPECIFIED
Wei, LingyunTUM-LMFUNSPECIFIED
Zhu, Xiao XiangDLR-IMF/TUM-LMFUNSPECIFIED
Date:2015
Journal or Publication Title:Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2015
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 1036-1039
Editors:
EditorsEmailEditor's ORCID iD
UNSPECIFIEDIEEE Org.UNSPECIFIED
Publisher:IEEE Xplore
Status:Published
Keywords:Coastline detection, Non-local filtering, TanDEM-X, SAR
Event Title:IGARSS 2015
Event Location:Mailand, Italien
Event Type:international Conference
Event Dates:26.-31. Jul. 2015
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 - Vorhaben hochauflösende Fernerkundungsverfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Ge, Nan
Deposited On:22 Jul 2015 15:38
Last Modified:31 Jul 2019 19:54

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