Detecting changes in polarimetric SAR data with content-based image retrieval

Matthieu Molinier; Jorma Laaksonen; Yrjö Rauste; Tuomas Häme

doi:10.1109/IGARSS.2007.4423323

Detecting changes in polarimetric SAR data with content-based image retrieval

Matthieu Molinier, Jorma Laaksonen, Yrjö Rauste, Tuomas Häme

Helsinki University of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

7 Citations (Scopus)

Abstract

In this study, we extended the potential of a Content-Based Image Retrieval (CBIR) system based on Self-Organizing Maps (SOMs), for the analysis of remote sensing data. A database was artificially created by splitting each image to be analyzed into small images (or imagelets). Content-based image retrieval was applied to fully Polarimetric airborne SAR data, using a selection of Polarimetric features. After training the system on this imagelet database, automatic queries could detect changes. Results were encouraging on airborne SAR data and may be more useful for spaceborne Polarimetric data.

Original language	English
Title of host publication	2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	2390-2393
Number of pages	4
ISBN (Electronic)	978-1-4244-1212-9
ISBN (Print)	978-1-4244-1211-2
DOIs	https://doi.org/10.1109/IGARSS.2007.4423323
Publication status	Published - 1 Dec 2007
MoE publication type	A4 Article in a conference publication
Event	2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007 - Barcelona, Spain Duration: 23 Jun 2007 → 28 Jun 2007

Conference

Conference	2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007
Abbreviated title	IGARSS 2007
Country/Territory	Spain
City	Barcelona
Period	23/06/07 → 28/06/07

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10.1109/IGARSS.2007.4423323

Cite this

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title = "Detecting changes in polarimetric SAR data with content-based image retrieval",

abstract = "In this study, we extended the potential of a Content-Based Image Retrieval (CBIR) system based on Self-Organizing Maps (SOMs), for the analysis of remote sensing data. A database was artificially created by splitting each image to be analyzed into small images (or imagelets). Content-based image retrieval was applied to fully Polarimetric airborne SAR data, using a selection of Polarimetric features. After training the system on this imagelet database, automatic queries could detect changes. Results were encouraging on airborne SAR data and may be more useful for spaceborne Polarimetric data.",

author = "Matthieu Molinier and Jorma Laaksonen and Yrj{\"o} Rauste and Tuomas H{\"a}me",

year = "2007",

month = dec,

day = "1",

doi = "10.1109/IGARSS.2007.4423323",

language = "English",

isbn = "978-1-4244-1211-2 ",

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booktitle = "2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

address = "United States",

note = "2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007, IGARSS 2007 ; Conference date: 23-06-2007 Through 28-06-2007",

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Molinier, M, Laaksonen, J, Rauste, Y & Häme, T 2007, Detecting changes in polarimetric SAR data with content-based image retrieval. in 2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007., 4423323, IEEE Institute of Electrical and Electronic Engineers, pp. 2390-2393, 2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007, Barcelona, Spain, 23/06/07. https://doi.org/10.1109/IGARSS.2007.4423323

Detecting changes in polarimetric SAR data with content-based image retrieval. / Molinier, Matthieu; Laaksonen, Jorma; Rauste, Yrjö et al.
2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007. IEEE Institute of Electrical and Electronic Engineers, 2007. p. 2390-2393 4423323.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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T1 - Detecting changes in polarimetric SAR data with content-based image retrieval

AU - Molinier, Matthieu

AU - Laaksonen, Jorma

AU - Rauste, Yrjö

AU - Häme, Tuomas

PY - 2007/12/1

Y1 - 2007/12/1

N2 - In this study, we extended the potential of a Content-Based Image Retrieval (CBIR) system based on Self-Organizing Maps (SOMs), for the analysis of remote sensing data. A database was artificially created by splitting each image to be analyzed into small images (or imagelets). Content-based image retrieval was applied to fully Polarimetric airborne SAR data, using a selection of Polarimetric features. After training the system on this imagelet database, automatic queries could detect changes. Results were encouraging on airborne SAR data and may be more useful for spaceborne Polarimetric data.

AB - In this study, we extended the potential of a Content-Based Image Retrieval (CBIR) system based on Self-Organizing Maps (SOMs), for the analysis of remote sensing data. A database was artificially created by splitting each image to be analyzed into small images (or imagelets). Content-based image retrieval was applied to fully Polarimetric airborne SAR data, using a selection of Polarimetric features. After training the system on this imagelet database, automatic queries could detect changes. Results were encouraging on airborne SAR data and may be more useful for spaceborne Polarimetric data.

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DO - 10.1109/IGARSS.2007.4423323

M3 - Conference article in proceedings

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SN - 978-1-4244-1211-2

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EP - 2393

BT - 2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - 2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007

Y2 - 23 June 2007 through 28 June 2007

ER -

Detecting changes in polarimetric SAR data with content-based image retrieval

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