Tensor based structure estimation in multi-channel images

Jesper Schou; Wolfgang Dierking; Henning Skriver

doi:10.1109/IGARSS.2000.861664

Tensor based structure estimation in multi-channel images

Jesper Schou
, Wolfgang Dierking
, Henning Skriver

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

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Abstract

In this work a two-step algorithm is proposed for detecting structures in multi-channel remote sensing images. The first part is a normal low level structure detection performed on the individual images, which provides information of the strength as well as the orientation of the structure. In the second part tensors are used for representing the structure information. This approach has the advantage, that tensors can be averaged either spatially or by applying several images, and the resulting tensor provides information of the average strength as well as orientation of the structure. The performance of the algorithm is examined using multi-frequency, polarimetric SAR images from the Danish airborne EMISAR.

Original language	English
Title of host publication	Proceedings on Geoscience and Remote Sensing Symposium
Volume	2
Place of Publication	Honolulu, HI
Publisher	IEEE
Publication date	2000
Pages	663-665
ISBN (Print)	0-7803-6359-0
DOIs	https://doi.org/10.1109/IGARSS.2000.861664
Publication status	Published - 2000
Event	IEEE 2000 International Geoscience and Remote Sensing Symposium - Honolulu, United States Duration: 24 Jul 2000 → 28 Jul 2000 http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6913

Conference

Conference	IEEE 2000 International Geoscience and Remote Sensing Symposium
Country/Territory	United States
City	Honolulu
Period	24/07/2000 → 28/07/2000
Internet address	http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6913

Bibliographical note

Copyright: 2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

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title = "Tensor based structure estimation in multi-channel images",

abstract = "In this work a two-step algorithm is proposed for detecting structures in multi-channel remote sensing images. The first part is a normal low level structure detection performed on the individual images, which provides information of the strength as well as the orientation of the structure. In the second part tensors are used for representing the structure information. This approach has the advantage, that tensors can be averaged either spatially or by applying several images, and the resulting tensor provides information of the average strength as well as orientation of the structure. The performance of the algorithm is examined using multi-frequency, polarimetric SAR images from the Danish airborne EMISAR.",

author = "Jesper Schou and Wolfgang Dierking and Henning Skriver",

note = "Copyright: 2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE; IEEE 2000 International Geoscience and Remote Sensing Symposium, IGARSS 2000 ; Conference date: 24-07-2000 Through 28-07-2000",

year = "2000",

doi = "10.1109/IGARSS.2000.861664",

language = "English",

isbn = "0-7803-6359-0",

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pages = "663--665",

booktitle = "Proceedings on Geoscience and Remote Sensing Symposium",

publisher = "IEEE",

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T1 - Tensor based structure estimation in multi-channel images

AU - Schou, Jesper

AU - Dierking, Wolfgang

AU - Skriver, Henning

N1 - Copyright: 2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

PY - 2000

Y1 - 2000

N2 - In this work a two-step algorithm is proposed for detecting structures in multi-channel remote sensing images. The first part is a normal low level structure detection performed on the individual images, which provides information of the strength as well as the orientation of the structure. In the second part tensors are used for representing the structure information. This approach has the advantage, that tensors can be averaged either spatially or by applying several images, and the resulting tensor provides information of the average strength as well as orientation of the structure. The performance of the algorithm is examined using multi-frequency, polarimetric SAR images from the Danish airborne EMISAR.

AB - In this work a two-step algorithm is proposed for detecting structures in multi-channel remote sensing images. The first part is a normal low level structure detection performed on the individual images, which provides information of the strength as well as the orientation of the structure. In the second part tensors are used for representing the structure information. This approach has the advantage, that tensors can be averaged either spatially or by applying several images, and the resulting tensor provides information of the average strength as well as orientation of the structure. The performance of the algorithm is examined using multi-frequency, polarimetric SAR images from the Danish airborne EMISAR.

U2 - 10.1109/IGARSS.2000.861664

DO - 10.1109/IGARSS.2000.861664

M3 - Article in proceedings

SN - 0-7803-6359-0

VL - 2

SP - 663

EP - 665

BT - Proceedings on Geoscience and Remote Sensing Symposium

PB - IEEE

CY - Honolulu, HI

T2 - IEEE 2000 International Geoscience and Remote Sensing Symposium

Y2 - 24 July 2000 through 28 July 2000

ER -

Tensor based structure estimation in multi-channel images

Abstract

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