Exploiting multi-aspect SAR data for object extraction

K. Hedman; S. Hinz; U. Stilla

doi:10.1109/IGARSS.2006.672

Exploiting multi-aspect SAR data for object extraction

K. Hedman, S. Hinz, U. Stilla

Associate Professorship of Photogrammetry and Remote Sensing

Technical University of Munich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

In this paper we describe a fusion approach for automatic object extraction from multi-aspect SAR images. Before fusion the uncertainty of each extracted object is assessed by means of Bayesian probability theory. The assessment is performed on attribute-level and is based on predefined probability density functions learned from training data.

Original language	English
Title of host publication	2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
Pages	2601-2604
Number of pages	4
DOIs	https://doi.org/10.1109/IGARSS.2006.672
State	Published - 2006
Event	2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS - Denver, CO, United States Duration: 31 Jul 2006 → 4 Aug 2006

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference	2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
Country/Territory	United States
City	Denver, CO
Period	31/07/06 → 4/08/06

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10.1109/IGARSS.2006.672

Cite this

@inproceedings{4e28f6d6dbfb46cb88b602510d3f6fd0,

title = "Exploiting multi-aspect SAR data for object extraction",

abstract = "In this paper we describe a fusion approach for automatic object extraction from multi-aspect SAR images. Before fusion the uncertainty of each extracted object is assessed by means of Bayesian probability theory. The assessment is performed on attribute-level and is based on predefined probability density functions learned from training data.",

author = "K. Hedman and S. Hinz and U. Stilla",

year = "2006",

doi = "10.1109/IGARSS.2006.672",

language = "English",

isbn = "0780395107",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

pages = "2601--2604",

booktitle = "2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS",

note = "2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS ; Conference date: 31-07-2006 Through 04-08-2006",

}

Hedman, K, Hinz, S & Stilla, U 2006, Exploiting multi-aspect SAR data for object extraction. in 2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS., 4241820, International Geoscience and Remote Sensing Symposium (IGARSS), pp. 2601-2604, 2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Denver, CO, United States, 31/07/06. https://doi.org/10.1109/IGARSS.2006.672

TY - GEN

T1 - Exploiting multi-aspect SAR data for object extraction

AU - Hedman, K.

AU - Hinz, S.

AU - Stilla, U.

PY - 2006

Y1 - 2006

N2 - In this paper we describe a fusion approach for automatic object extraction from multi-aspect SAR images. Before fusion the uncertainty of each extracted object is assessed by means of Bayesian probability theory. The assessment is performed on attribute-level and is based on predefined probability density functions learned from training data.

AB - In this paper we describe a fusion approach for automatic object extraction from multi-aspect SAR images. Before fusion the uncertainty of each extracted object is assessed by means of Bayesian probability theory. The assessment is performed on attribute-level and is based on predefined probability density functions learned from training data.

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U2 - 10.1109/IGARSS.2006.672

DO - 10.1109/IGARSS.2006.672

M3 - Conference contribution

AN - SCOPUS:34948888102

SN - 0780395107

SN - 9780780395107

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 2601

EP - 2604

BT - 2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS

T2 - 2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS

Y2 - 31 July 2006 through 4 August 2006

ER -

Exploiting multi-aspect SAR data for object extraction

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