An accuracy assessment of ML texture tracking algorithm over multitemporal SAR images

Esra Erten; Andreas Reigber; Olaf Hellwich; Pau Prats

doi:10.1109/IGARSS.2009.5417411

An accuracy assessment of ML texture tracking algorithm over multitemporal SAR images

Esra Erten^*, Andreas Reigber, Olaf Hellwich, Pau Prats

^*Corresponding author for this work

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

Abstract

In this paper, the accuracy assessment of the recently proposed Maximum Likelihood (ML) texture tracking algorithm is discussed. Its comparison with the well known texture tracking technique, i.e., Normalized Incoherent Cross Correlation (NICC), has also been investigated in the case of the presence of multiplicative noise structure.

Original language	English
Title of host publication	2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009 - Proceedings
Pages	IV454-IV457
DOIs	https://doi.org/10.1109/IGARSS.2009.5417411
Publication status	Published - 2009
Externally published	Yes
Event	2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009 - Cape Town, South Africa Duration: 12 Jul 2009 → 17 Jul 2009

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	4

Conference

Conference	2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009
Country/Territory	South Africa
City	Cape Town
Period	12/07/09 → 17/07/09

Keywords

Bivariate gamma distribution
Cramer-Rao Lower Bound (CRLB)
Incoherent normalized cross correlation
Texture tracking

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10.1109/IGARSS.2009.5417411

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Erten, E., Reigber, A., Hellwich, O., & Prats, P. (2009). An accuracy assessment of ML texture tracking algorithm over multitemporal SAR images. In 2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009 - Proceedings (pp. IV454-IV457). Article 5417411 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 4). https://doi.org/10.1109/IGARSS.2009.5417411

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title = "An accuracy assessment of ML texture tracking algorithm over multitemporal SAR images",

abstract = "In this paper, the accuracy assessment of the recently proposed Maximum Likelihood (ML) texture tracking algorithm is discussed. Its comparison with the well known texture tracking technique, i.e., Normalized Incoherent Cross Correlation (NICC), has also been investigated in the case of the presence of multiplicative noise structure.",

keywords = "Bivariate gamma distribution, Cramer-Rao Lower Bound (CRLB), Incoherent normalized cross correlation, Texture tracking",

author = "Esra Erten and Andreas Reigber and Olaf Hellwich and Pau Prats",

year = "2009",

doi = "10.1109/IGARSS.2009.5417411",

language = "English",

isbn = "9781424433957",

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

pages = "IV454--IV457",

booktitle = "2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009 - Proceedings",

note = "2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009 ; Conference date: 12-07-2009 Through 17-07-2009",

}

Erten, E, Reigber, A, Hellwich, O & Prats, P 2009, An accuracy assessment of ML texture tracking algorithm over multitemporal SAR images. in 2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009 - Proceedings., 5417411, International Geoscience and Remote Sensing Symposium (IGARSS), vol. 4, pp. IV454-IV457, 2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009, Cape Town, South Africa, 12/07/09. https://doi.org/10.1109/IGARSS.2009.5417411

An accuracy assessment of ML texture tracking algorithm over multitemporal SAR images. / Erten, Esra; Reigber, Andreas; Hellwich, Olaf et al.
2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009 - Proceedings. 2009. p. IV454-IV457 5417411 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 4).

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

TY - GEN

T1 - An accuracy assessment of ML texture tracking algorithm over multitemporal SAR images

AU - Erten, Esra

AU - Reigber, Andreas

AU - Hellwich, Olaf

AU - Prats, Pau

PY - 2009

Y1 - 2009

N2 - In this paper, the accuracy assessment of the recently proposed Maximum Likelihood (ML) texture tracking algorithm is discussed. Its comparison with the well known texture tracking technique, i.e., Normalized Incoherent Cross Correlation (NICC), has also been investigated in the case of the presence of multiplicative noise structure.

AB - In this paper, the accuracy assessment of the recently proposed Maximum Likelihood (ML) texture tracking algorithm is discussed. Its comparison with the well known texture tracking technique, i.e., Normalized Incoherent Cross Correlation (NICC), has also been investigated in the case of the presence of multiplicative noise structure.

KW - Bivariate gamma distribution

KW - Cramer-Rao Lower Bound (CRLB)

KW - Incoherent normalized cross correlation

KW - Texture tracking

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DO - 10.1109/IGARSS.2009.5417411

M3 - Conference contribution

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SN - 9781424433957

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - IV454-IV457

BT - 2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009 - Proceedings

T2 - 2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009

Y2 - 12 July 2009 through 17 July 2009

ER -

An accuracy assessment of ML texture tracking algorithm over multitemporal SAR images

Abstract

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Keywords

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