Information Extraction and Modeling from Remote Sensing Images : Application to the Enhancement of Digital Elevation Models

The analysis of remote sensing images aggregates numerous disciplines which were, before the advent of Earth observation (EO) techniques, distinct fields. The synergies between Cartography, Photogrammetry, Image processing and analysis, Computer vision, etc. allow to observe, monitor and study our e...
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Autor*in:	Maire, Cyrille [verfasserIn]
Hochschulschrift:	Karlsruhe, Univ., Diss., 2009

Format:	E-Book
Sprache:	Englisch

Erschienen:	2009

Formangabe:	Hochschulschrift

Umfang:	Online-Ressource

Links:	Link aufrufen Volltext Volltext Volltext

DOI / URN:	urn:nbn:de:swb:90-175177 10.5445/IR/1000017517

Katalog-ID:	625784928

Internformat


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Indexfelder

author_variant	c m cm
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oclc_num	837605372 699719269
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publishDate	2009
allfields	10,O06 dnb 1002231981 DE-101 urn:nbn:de:swb:90-175177 urn 10.5445/IR/1000017517 doi (DE-627)625784928 (DE-576)32245560X (DE-599)BSZ32245560X (OCoLC)837605372 (OCoLC)699719269 DE-627 ger DE-627 rakwb eng XA-DE 550 OCLC 550 DNB 14 ssgn Maire, Cyrille verfasserin aut Information Extraction and Modeling from Remote Sensing Images Application to the Enhancement of Digital Elevation Models von Cyrille Maire 2009 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Karlsruhe, Univ., Diss., 2009 The analysis of remote sensing images aggregates numerous disciplines which were, before the advent of Earth observation (EO) techniques, distinct fields. The synergies between Cartography, Photogrammetry, Image processing and analysis, Computer vision, etc. allow to observe, monitor and study our environment. In this dissertation, several methods to analyse, interpret and enhance satellite images are considered. Those different axes are motivated by a crucial need of efficient and novel methods for the extraction and the modeling of relevant information from standard remote sensing images in order to fully exploit those data presenting metric resolution over large areas. During this research work, an innovative, fast and robust image processing system has been fully developed, tested and validated. It consists in, (1) a robust region-based segmentation approach, using the Mumford and Shah formalism to generate meaningful partitions from large remote sensing images, (2) a novel dynamic algorithm to extract and express the regions with the complex cellular model. A tree structure is introduced to store the regions while reflecting their topological (adjacency, inclusion) and geometrical properties. (3) information learning methods to analyse and interpret the extracted and modeled primitives. The interest of such a processing line is emphasized on various EO data ranking from decametric to metric resolution (e.g. multispectral SPOT 5, Ikonos or QuickBird, panchromatic Cartosat) presenting various coverage types (e.g. agricultural fields, communication networks, man-made structures, urban areas) ... 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spelling	10,O06 dnb 1002231981 DE-101 urn:nbn:de:swb:90-175177 urn 10.5445/IR/1000017517 doi (DE-627)625784928 (DE-576)32245560X (DE-599)BSZ32245560X (OCoLC)837605372 (OCoLC)699719269 DE-627 ger DE-627 rakwb eng XA-DE 550 OCLC 550 DNB 14 ssgn Maire, Cyrille verfasserin aut Information Extraction and Modeling from Remote Sensing Images Application to the Enhancement of Digital Elevation Models von Cyrille Maire 2009 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Karlsruhe, Univ., Diss., 2009 The analysis of remote sensing images aggregates numerous disciplines which were, before the advent of Earth observation (EO) techniques, distinct fields. The synergies between Cartography, Photogrammetry, Image processing and analysis, Computer vision, etc. allow to observe, monitor and study our environment. In this dissertation, several methods to analyse, interpret and enhance satellite images are considered. 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The interest of such a processing line is emphasized on various EO data ranking from decametric to metric resolution (e.g. multispectral SPOT 5, Ikonos or QuickBird, panchromatic Cartosat) presenting various coverage types (e.g. agricultural fields, communication networks, man-made structures, urban areas) ... Archivierung/Langzeitarchivierung gewährleistet DISS XA-DE-BW pdager DE-90 Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Karlsruhe (DE-588)4029713-5 (DE-627)106273159 (DE-576)208983864 uvp https://digbib.bibliothek.kit.edu/volltexte/1000017517 Archivierung kostenfrei Volltext http://d-nb.info/1002231981/34 Langzeitarchivierung Nationalbibliothek Volltext http://nbn-resolving.de/urn:nbn:de:swb:90-175177 Resolving-System Volltext GBV-ODiss GBV_ILN_20 ISIL_DE-84 SYSFLAG_1 GBV_KXP SSG-OPC-GGO GBV_ILN_21 ISIL_DE-46 GBV_ILN_22 ISIL_DE-18 GBV_ILN_23 ISIL_DE-830 GBV_ILN_30 ISIL_DE-104 GBV_ILN_40 ISIL_DE-7 GBV_ILN_60 ISIL_DE-705 GBV_ILN_63 ISIL_DE-Wim2 GBV_ILN_70 ISIL_DE-89 GBV_ILN_105 ISIL_DE-841 GBV_ILN_110 ISIL_DE-Luen4 GBV_ILN_132 ISIL_DE-959 GBV_ILN_151 ISIL_DE-546 GBV_ILN_161 ISIL_DE-960 GBV_ILN_293 ISIL_DE-960-3 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2014 ISIL_DE-90 GBV_ILN_2403 ISIL_DE-LFER BO 045F 550 20 01 0084 1180794877 x 11-09-10 21 01 0046 1180894812 z 11-09-10 22 01 0018 1180988191 SUBolrd xu 11-09-10 23 01 0830 1181071089 olr-d x 11-09-10 30 01 0104 1181132177 z 11-09-10 40 01 0007 1181200806 ksn 11-04-12 60 01 0705 1181294142 OLRD z 11-09-10 63 01 3401 1595674233 ORD x 21-01-16 70 01 0089 1228079056 zdo 20-02-11 105 01 0841 1596487437 z 21-01-16 110 01 3110 1181378281 x 11-09-10 132 01 0959 1497552826 OLR-DISS x 11-08-14 151 01 0546 3594096327 OLR-ODISS z 13-02-20 161 01 0960 1597435481 ORD x 28-01-16 293 01 3293 1597864072 ORD xf 28-01-16 370 01 4370 1181415810 x 11-09-10 2014 01 DE-90 3332329251 00 --%%-- --%%-- --%%-- --%%-- l01 29-04-10 2403 01 DE-LFER 3332329286 00 --%%-- --%%-- n --%%-- l01 14-05-10 20 01 0084 http://nbn-resolving.de/urn:nbn:de:swb:90-175177 21 01 0046 http://nbn-resolving.de/urn:nbn:de:swb:90-175177 22 01 0018 http://nbn-resolving.de/urn:nbn:de:swb:90-175177 23 01 0830 http://nbn-resolving.de/urn:nbn:de:swb:90-175177 30 01 0104 http://nbn-resolving.de/urn:nbn:de:swb:90-175177 60 01 0705 http://nbn-resolving.de/urn:nbn:de:swb:90-175177 63 01 3401 E-Book http://nbn-resolving.de/urn:nbn:de:swb:90-175177 LF 70 01 0089 http://nbn-resolving.de/urn:nbn:de:swb:90-175177 105 01 0841 http://nbn-resolving.de/urn:nbn:de:swb:90-175177 110 01 3110 http://nbn-resolving.de/urn:nbn:de:swb:90-175177 132 01 0959 http://nbn-resolving.de/urn:nbn:de:swb:90-175177 151 01 0546 Volltext http://nbn-resolving.de/urn:nbn:de:swb:90-175177 161 01 0960 http://nbn-resolving.de/urn:nbn:de:swb:90-175177 293 01 3293 http://nbn-resolving.de/urn:nbn:de:swb:90-175177 370 01 4370 http://nbn-resolving.de/urn:nbn:de:swb:90-175177 2014 01 DE-90 Volltext frei verfügbar https://digbib.bibliothek.kit.edu/volltexte/1000017517 2403 01 DE-LFER https://digbib.bibliothek.kit.edu/volltexte/1000017517 2014 01 DE-90 00 s Image analysis 2014 01 DE-90 00 s image segmentation and topology 2014 01 DE-90 00 s information extraction and modeling 2014 01 DE-90 00 s DEM regularization and filtering 40 00 DE-7 00 QA 60 01 0705 10 ho 20 01 0084 OLRD 110 01 3110 OLRD 370 01 4370 OLRD 22 01 0018 SUBolrd 23 01 0830 olr-d 60 01 0705 OLRD 63 01 3401 ORD 132 01 0959 OLR-DISS 151 01 0546 OLR-ODISS 161 01 0960 ORD 293 01 3293 ORD 23 01 0830 2010-09-11:05:41:15 40 01 0007 2011-12 9 g
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allfieldsGer	10,O06 dnb 1002231981 DE-101 urn:nbn:de:swb:90-175177 urn 10.5445/IR/1000017517 doi (DE-627)625784928 (DE-576)32245560X (DE-599)BSZ32245560X (OCoLC)837605372 (OCoLC)699719269 DE-627 ger DE-627 rakwb eng XA-DE 550 OCLC 550 DNB 14 ssgn Maire, Cyrille verfasserin aut Information Extraction and Modeling from Remote Sensing Images Application to the Enhancement of Digital Elevation Models von Cyrille Maire 2009 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Karlsruhe, Univ., Diss., 2009 The analysis of remote sensing images aggregates numerous disciplines which were, before the advent of Earth observation (EO) techniques, distinct fields. The synergies between Cartography, Photogrammetry, Image processing and analysis, Computer vision, etc. allow to observe, monitor and study our environment. In this dissertation, several methods to analyse, interpret and enhance satellite images are considered. Those different axes are motivated by a crucial need of efficient and novel methods for the extraction and the modeling of relevant information from standard remote sensing images in order to fully exploit those data presenting metric resolution over large areas. During this research work, an innovative, fast and robust image processing system has been fully developed, tested and validated. It consists in, (1) a robust region-based segmentation approach, using the Mumford and Shah formalism to generate meaningful partitions from large remote sensing images, (2) a novel dynamic algorithm to extract and express the regions with the complex cellular model. A tree structure is introduced to store the regions while reflecting their topological (adjacency, inclusion) and geometrical properties. (3) information learning methods to analyse and interpret the extracted and modeled primitives. The interest of such a processing line is emphasized on various EO data ranking from decametric to metric resolution (e.g. multispectral SPOT 5, Ikonos or QuickBird, panchromatic Cartosat) presenting various coverage types (e.g. agricultural fields, communication networks, man-made structures, urban areas) ... 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allfieldsSound	10,O06 dnb 1002231981 DE-101 urn:nbn:de:swb:90-175177 urn 10.5445/IR/1000017517 doi (DE-627)625784928 (DE-576)32245560X (DE-599)BSZ32245560X (OCoLC)837605372 (OCoLC)699719269 DE-627 ger DE-627 rakwb eng XA-DE 550 OCLC 550 DNB 14 ssgn Maire, Cyrille verfasserin aut Information Extraction and Modeling from Remote Sensing Images Application to the Enhancement of Digital Elevation Models von Cyrille Maire 2009 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Karlsruhe, Univ., Diss., 2009 The analysis of remote sensing images aggregates numerous disciplines which were, before the advent of Earth observation (EO) techniques, distinct fields. The synergies between Cartography, Photogrammetry, Image processing and analysis, Computer vision, etc. allow to observe, monitor and study our environment. In this dissertation, several methods to analyse, interpret and enhance satellite images are considered. Those different axes are motivated by a crucial need of efficient and novel methods for the extraction and the modeling of relevant information from standard remote sensing images in order to fully exploit those data presenting metric resolution over large areas. During this research work, an innovative, fast and robust image processing system has been fully developed, tested and validated. It consists in, (1) a robust region-based segmentation approach, using the Mumford and Shah formalism to generate meaningful partitions from large remote sensing images, (2) a novel dynamic algorithm to extract and express the regions with the complex cellular model. A tree structure is introduced to store the regions while reflecting their topological (adjacency, inclusion) and geometrical properties. (3) information learning methods to analyse and interpret the extracted and modeled primitives. The interest of such a processing line is emphasized on various EO data ranking from decametric to metric resolution (e.g. multispectral SPOT 5, Ikonos or QuickBird, panchromatic Cartosat) presenting various coverage types (e.g. agricultural fields, communication networks, man-made structures, urban areas) ... 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author	Maire, Cyrille
spellingShingle	Maire, Cyrille ddc 550 ssgn 14 2014 Image analysis 2014 image segmentation and topology 2014 information extraction and modeling 2014 DEM regularization and filtering Information Extraction and Modeling from Remote Sensing Images Application to the Enhancement of Digital Elevation Models
authorStr	Maire, Cyrille
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topic_title	550 OCLC 550 DNB 14 ssgn 2014 01 DE-90 00 s Image analysis 2014 01 DE-90 00 s image segmentation and topology 2014 01 DE-90 00 s information extraction and modeling 2014 01 DE-90 00 s DEM regularization and filtering Information Extraction and Modeling from Remote Sensing Images Application to the Enhancement of Digital Elevation Models von Cyrille Maire
topic	ddc 550 ssgn 14 2014 Image analysis 2014 image segmentation and topology 2014 information extraction and modeling 2014 DEM regularization and filtering
topic_unstemmed	ddc 550 ssgn 14 2014 Image analysis 2014 image segmentation and topology 2014 information extraction and modeling 2014 DEM regularization and filtering
topic_browse	ddc 550 ssgn 14 2014 Image analysis 2014 image segmentation and topology 2014 information extraction and modeling 2014 DEM regularization and filtering
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title	Information Extraction and Modeling from Remote Sensing Images Application to the Enhancement of Digital Elevation Models
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title_full	Information Extraction and Modeling from Remote Sensing Images Application to the Enhancement of Digital Elevation Models von Cyrille Maire
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title_sub	Application to the Enhancement of Digital Elevation Models
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title_sort	information extraction and modeling from remote sensing imagesapplication to the enhancement of digital elevation models
title_auth	Information Extraction and Modeling from Remote Sensing Images Application to the Enhancement of Digital Elevation Models
abstract	The analysis of remote sensing images aggregates numerous disciplines which were, before the advent of Earth observation (EO) techniques, distinct fields. The synergies between Cartography, Photogrammetry, Image processing and analysis, Computer vision, etc. allow to observe, monitor and study our environment. In this dissertation, several methods to analyse, interpret and enhance satellite images are considered. Those different axes are motivated by a crucial need of efficient and novel methods for the extraction and the modeling of relevant information from standard remote sensing images in order to fully exploit those data presenting metric resolution over large areas. During this research work, an innovative, fast and robust image processing system has been fully developed, tested and validated. It consists in, (1) a robust region-based segmentation approach, using the Mumford and Shah formalism to generate meaningful partitions from large remote sensing images, (2) a novel dynamic algorithm to extract and express the regions with the complex cellular model. A tree structure is introduced to store the regions while reflecting their topological (adjacency, inclusion) and geometrical properties. (3) information learning methods to analyse and interpret the extracted and modeled primitives. The interest of such a processing line is emphasized on various EO data ranking from decametric to metric resolution (e.g. multispectral SPOT 5, Ikonos or QuickBird, panchromatic Cartosat) presenting various coverage types (e.g. agricultural fields, communication networks, man-made structures, urban areas) ...
abstractGer	The analysis of remote sensing images aggregates numerous disciplines which were, before the advent of Earth observation (EO) techniques, distinct fields. The synergies between Cartography, Photogrammetry, Image processing and analysis, Computer vision, etc. allow to observe, monitor and study our environment. In this dissertation, several methods to analyse, interpret and enhance satellite images are considered. Those different axes are motivated by a crucial need of efficient and novel methods for the extraction and the modeling of relevant information from standard remote sensing images in order to fully exploit those data presenting metric resolution over large areas. During this research work, an innovative, fast and robust image processing system has been fully developed, tested and validated. It consists in, (1) a robust region-based segmentation approach, using the Mumford and Shah formalism to generate meaningful partitions from large remote sensing images, (2) a novel dynamic algorithm to extract and express the regions with the complex cellular model. A tree structure is introduced to store the regions while reflecting their topological (adjacency, inclusion) and geometrical properties. (3) information learning methods to analyse and interpret the extracted and modeled primitives. The interest of such a processing line is emphasized on various EO data ranking from decametric to metric resolution (e.g. multispectral SPOT 5, Ikonos or QuickBird, panchromatic Cartosat) presenting various coverage types (e.g. agricultural fields, communication networks, man-made structures, urban areas) ...
abstract_unstemmed	The analysis of remote sensing images aggregates numerous disciplines which were, before the advent of Earth observation (EO) techniques, distinct fields. The synergies between Cartography, Photogrammetry, Image processing and analysis, Computer vision, etc. allow to observe, monitor and study our environment. In this dissertation, several methods to analyse, interpret and enhance satellite images are considered. Those different axes are motivated by a crucial need of efficient and novel methods for the extraction and the modeling of relevant information from standard remote sensing images in order to fully exploit those data presenting metric resolution over large areas. During this research work, an innovative, fast and robust image processing system has been fully developed, tested and validated. It consists in, (1) a robust region-based segmentation approach, using the Mumford and Shah formalism to generate meaningful partitions from large remote sensing images, (2) a novel dynamic algorithm to extract and express the regions with the complex cellular model. A tree structure is introduced to store the regions while reflecting their topological (adjacency, inclusion) and geometrical properties. (3) information learning methods to analyse and interpret the extracted and modeled primitives. The interest of such a processing line is emphasized on various EO data ranking from decametric to metric resolution (e.g. multispectral SPOT 5, Ikonos or QuickBird, panchromatic Cartosat) presenting various coverage types (e.g. agricultural fields, communication networks, man-made structures, urban areas) ...
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title_short	Information Extraction and Modeling from Remote Sensing Images
url	https://digbib.bibliothek.kit.edu/volltexte/1000017517 http://d-nb.info/1002231981/34 http://nbn-resolving.de/urn:nbn:de:swb:90-175177
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Information Extraction and Modeling from Remote Sensing Images : Application to the Enhancement of Digital Elevation Models

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