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The cross-scattering component of polarimetric SAR in urban areasand its application to model-based scattering decomposition
KTH, School of Architecture and the Built Environment (ABE). National University of Defense Technology, China. (Division of Geoinformatics)
(English)In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901Article in journal (Refereed) Accepted
Abstract [en]

After the work of Freeman, Durden, Pottier, and Yamaguchi, manydecomposition techniques have been proposed for urban areas, mainly to resolvethe overestimation problem of volume scattering. Since it has been validated thatthe cross-polarised (HV) scattering is caused not only by forests but also byrotated dihedrals, in this paper, we propose a cross scattering coherency matrix tomodel the HV component from orientated and complex buildings and thendemonstrate its performance on model-based scattering decomposition. Thebuilding orientation angle is considered in this coherency matrix, making itflexible and adaptive in the decomposition. Therefore, the HV components fromforests and orientated urban areas can be modelled respectively. Twodecomposition procedures are applied in this paper. The first one is to validatethe effectiveness of this scattering model. We regard the HV component fromurban areas as cross scattering, which is an independent scattering componentadded to the Yamaguchi four-component decomposition. Another one is theurban area decomposition application using this scattering model. Decompositionis implemented for urban and natural areas respectively and the HV componentfrom urban areas is regarded as their volume scattering. This procedure is similarto many other state-of-the-art methods for urban areas and needs to discriminatethe urban and natural areas before decomposition. Spaceborne Radarsat-2 C band,the Airborne Synthetic Aperture Radar (AIRSAR) L band and UninhabitedAerial Vehicle Synthetic Aperture Radar (UAVSAR) L band full polarimetricSAR data are used to validate the performance of this cross scattering coherencymatrix. The HV component of orientated buildings is generated, leading to abetter decomposition result for urban areas.

Place, publisher, year, edition, pages
Taylor & Francis Group.
Keyword [en]
cross scattering coherency matrix; orientated urban areas; modelbased decomposition; polarimetric SAR (PolSAR)
National Category
Remote Sensing
Identifiers
URN: urn:nbn:se:kth:diva-187939OAI: oai:DiVA.org:kth-187939DiVA: diva2:932588
Note

QC 20160607

Available from: 2016-06-01 Created: 2016-06-01 Last updated: 2016-06-07Bibliographically approved
In thesis
1. Urban Area Information Extraction From Polarimetric SAR Data
Open this publication in new window or tab >>Urban Area Information Extraction From Polarimetric SAR Data
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Polarimetric Synthetic Aperture Radar (PolSAR) has been used for various remote sensing applications since more information could be obtained in multiple polarizations. The overall objective of this thesis is to investigate urban area information extraction from PolSAR data with the following specific objectives: (1) to exploit polarimetric scattering model-based decomposition methods for urban areas, (2) to investigate effective methods for man-made target detection, (3) to develop edge detection and superpixel generation methods, and (4) to investigate urban area classification and segmentation.

Paper 1 proposes a new scattering coherency matrix to model the cross-polarized scattering component from urban areas, which adaptively considers the polarization orientation angles of buildings. Thus, the HV scattering components from forests and oriented urban areas can be modelled respectively. Paper 2 presents two urban area decompositions using this scattering model. After the decomposition, urban scattering components can be effectively extracted.

Paper 3 presents an improved man-made target detection method for PolSAR data based on nonstationarity and asymmetry. Reflection asymmetry was incorporate into the azimuth nonstationarity extraction method to improve the man-made target detection accuracy, i.e., removing the natural areas and detecting the small targets.

In Paper 4, the edge detection of PolSAR data was investigated using SIRV model and Gauss-shaped filter. This detector can locate the edge pixels accurately with fewer omissions. This could be useful for speckle noise reduction, superpixel generation and others.

Paper 5 investigates an unsupervised classification method for PolSAR data in urban areas. The ortho and oriented buildings can be discriminated very well. Paper 6 proposes an adaptive superpixel generation method for PolSAR images. The algorithm produces compact superpixels that can well adhere to image boundaries in both natural and urban areas.

Abstract [sv]

Polarimetriska Synthetic Aperture Radar (PolSAR) har använts för olika fjärranalystillämpningar för, eftersom mer information kan erhållas från multipolarisad data. Det övergripande syftet med denna avhandling är att undersöka informationshämtning över urbana områden från PolSAR data med följande särskilda mål: (1) att utnyttja polarimetrisk spridningsmodellbaserade nedbrytningsmetoder för stadsområden, (2) att undersöka effektiva metoder för upptäckt av konstgjorda objekt, (3) att utveckla metoder som kantavkänning och superpixel generation, och (4) för att undersöka klassificering och segmentering av stadsområden.

Artikel 1 föreslår en ny spridnings-koherens matris för att modellera korspolariserade spridningskomponent från tätorter, som adaptivt utvärderar polariseringsorienteringsvinkel av byggnader. Artikel 2 presenterar nedbrytningstekniken över två urbana områden med hjälp av denna spridningsmodell. Efter nedbrytningen kunde urbana spridningskomponenter effektivt extraheras.

Artikel 3 presenterar en förbättrad detekteringsmetod för konstgjorda mål med PolSAR data baserade på icke-stationaritet och asymmetri. integrerades reflektionsasymmetri i icke-stationaritetsmetoden för att förbättra noggrannheten i upptäckten av konstgjorda föremål, dvs. att ta bort naturområden och upptäcka de små föremålen.

I artikel 4 undersöktes kantdetektering av PolSAR data med hjälp av SIRV modell och ett Gauss-formad filter. Denna detektor kan hitta kantpixlarna noggrant med mindre utelämnande. Detta skulle den vara användbar för reduktion av brus, superpixel generation och andra.

Artikel 5 utforskar en oövervakad klassificeringsmetod av PolSAR data över stadsområden. Orto- och orienterade byggnader kan särskiljas mycket väl. Baserat på artikel 4 föreslår artikel 6 en adaptiv superpixel generationensmetod för PolSAR data. Algoritmen producerar kompakta superpixels som kan kommer att följa bildgränser i både naturliga och stadsområden.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2016. 121 p.
Series
TRITA-SOM, ISSN 1653-6126
Keyword
Polarimetric SAR, Scattering Decomposition, Man-Made Target Detection, Edge Detection, Superpixel, Urban Classification, Polarimetrisk SAR, Spridningsnedbrytning, Upptäckt av artificiella objekt, Kantupptäckt, Superpixel, Urban klassificering
National Category
Remote Sensing
Research subject
Geodesy and Geoinformatics
Identifiers
urn:nbn:se:kth:diva-187951 (URN)978-91-7729-047-6 (ISBN)
Public defence
2016-08-25, Kollegiesalen, Brinellvägen 8, KTH-Campus, Stockholm, 13:30 (English)
Opponent
Supervisors
Note

QC 20160607

Available from: 2016-06-07 Created: 2016-06-01 Last updated: 2016-06-07Bibliographically approved

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