A one-class classification by spatial-contextual for remotely sensed image

Xiaofei Wang; Shuang Wu; Ye Zhang; Wang Aihua; Chuanlong Hou

doi:10.1109/IGARSS.2013.6721186

A one-class classification by spatial-contextual for remotely sensed image

Xiaofei Wang, Shuang Wu, Ye Zhang, Wang Aihua, Chuanlong Hou

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

Abstract

Hyperspectral remote sensing is a technique based on the spectroscopy, which contains abundant spectral information besides the spatial information of the images, and overcomes the limitations of the wide-band remote sensing detection. When classifying hyperspectral and multispectral images with the existing algorithms, we use only the spectral information more often. This paper presents an one-class classification techniques, which is based spatial-contextual term, this study modifies the decision function and constraints of support vector data description. Experimental results show that the proposed method achieves good classification performance on hyperspectral image.

Original language	English
Title of host publication	2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings
Pages	437-440
Number of pages	4
DOIs	https://doi.org/10.1109/IGARSS.2013.6721186
Publication status	Published - 2013
Externally published	Yes
Event	2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Melbourne, VIC, Australia Duration: 21 Jul 2013 → 26 Jul 2013

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference	2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013
Country/Territory	Australia
City	Melbourne, VIC
Period	21/07/13 → 26/07/13

Keywords

hyperspectral iamge
One-class classification
spatial-contextual information
support vector data description

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10.1109/IGARSS.2013.6721186

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Wang, X., Wu, S., Zhang, Y., Aihua, W., & Hou, C. (2013). A one-class classification by spatial-contextual for remotely sensed image. In 2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings (pp. 437-440). Article 6721186 (International Geoscience and Remote Sensing Symposium (IGARSS)). https://doi.org/10.1109/IGARSS.2013.6721186

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title = "A one-class classification by spatial-contextual for remotely sensed image",

abstract = "Hyperspectral remote sensing is a technique based on the spectroscopy, which contains abundant spectral information besides the spatial information of the images, and overcomes the limitations of the wide-band remote sensing detection. When classifying hyperspectral and multispectral images with the existing algorithms, we use only the spectral information more often. This paper presents an one-class classification techniques, which is based spatial-contextual term, this study modifies the decision function and constraints of support vector data description. Experimental results show that the proposed method achieves good classification performance on hyperspectral image.",

keywords = "hyperspectral iamge, One-class classification, spatial-contextual information, support vector data description",

author = "Xiaofei Wang and Shuang Wu and Ye Zhang and Wang Aihua and Chuanlong Hou",

year = "2013",

doi = "10.1109/IGARSS.2013.6721186",

language = "English",

isbn = "9781479911141",

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

pages = "437--440",

booktitle = "2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings",

note = "2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 ; Conference date: 21-07-2013 Through 26-07-2013",

}

Wang, X, Wu, S, Zhang, Y, Aihua, W & Hou, C 2013, A one-class classification by spatial-contextual for remotely sensed image. in 2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings., 6721186, International Geoscience and Remote Sensing Symposium (IGARSS), pp. 437-440, 2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013, Melbourne, VIC, Australia, 21/07/13. https://doi.org/10.1109/IGARSS.2013.6721186

A one-class classification by spatial-contextual for remotely sensed image. / Wang, Xiaofei; Wu, Shuang; Zhang, Ye et al.
2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings. 2013. p. 437-440 6721186 (International Geoscience and Remote Sensing Symposium (IGARSS)).

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

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T1 - A one-class classification by spatial-contextual for remotely sensed image

AU - Wang, Xiaofei

AU - Wu, Shuang

AU - Zhang, Ye

AU - Aihua, Wang

AU - Hou, Chuanlong

PY - 2013

Y1 - 2013

N2 - Hyperspectral remote sensing is a technique based on the spectroscopy, which contains abundant spectral information besides the spatial information of the images, and overcomes the limitations of the wide-band remote sensing detection. When classifying hyperspectral and multispectral images with the existing algorithms, we use only the spectral information more often. This paper presents an one-class classification techniques, which is based spatial-contextual term, this study modifies the decision function and constraints of support vector data description. Experimental results show that the proposed method achieves good classification performance on hyperspectral image.

AB - Hyperspectral remote sensing is a technique based on the spectroscopy, which contains abundant spectral information besides the spatial information of the images, and overcomes the limitations of the wide-band remote sensing detection. When classifying hyperspectral and multispectral images with the existing algorithms, we use only the spectral information more often. This paper presents an one-class classification techniques, which is based spatial-contextual term, this study modifies the decision function and constraints of support vector data description. Experimental results show that the proposed method achieves good classification performance on hyperspectral image.

KW - hyperspectral iamge

KW - One-class classification

KW - spatial-contextual information

KW - support vector data description

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U2 - 10.1109/IGARSS.2013.6721186

DO - 10.1109/IGARSS.2013.6721186

M3 - Conference contribution

AN - SCOPUS:84894271257

SN - 9781479911141

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

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EP - 440

BT - 2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings

T2 - 2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013

Y2 - 21 July 2013 through 26 July 2013

ER -

A one-class classification by spatial-contextual for remotely sensed image

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