An ikonos image fusion process using support value transform

Sheng Zheng; Wenzhong Shi; Jian Liu

doi:10.1109/ICMLC.2007.4370398

An ikonos image fusion process using support value transform

Sheng Zheng, Wenzhong Shi, Jian Liu

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Abstract

Panehromatic (Pan)-sharpening of muttispectral (MS) bands is an important technique in various applications of satellite remote sensing. In this paper, we apply the support value transform (SVT) to lkonos image fusion. The fused saliency features are represented by support values and extracted by SVT. The low-resolution MS bands are resampled to the fine scale of the Pan image and sharpened by injecting the detailed features extracted from the high-resolution Pan image. The fusing results on Ikonos MS + Pan data demonstrate that the proposed image fusion method is effective and efficient.

Original language	English
Title of host publication	Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007
Pages	1584-1589
Number of pages	6
Volume	3
DOIs	https://doi.org/10.1109/ICMLC.2007.4370398
Publication status	Published - 1 Dec 2007
Event	6th International Conference on Machine Learning and Cybernetics, ICMLC 2007 - Hong Kong, Hong Kong Duration: 19 Aug 2007 → 22 Aug 2007

Conference

Conference	6th International Conference on Machine Learning and Cybernetics, ICMLC 2007
Country/Territory	Hong Kong
City	Hong Kong
Period	19/08/07 → 22/08/07

Keywords

Ikonos image fusion
Mapped least squares support vector machine (mapped LS-SVM)
Support value transform (SVT)

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Software
Theoretical Computer Science

More information

10.1109/ICMLC.2007.4370398

Cite this

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title = "An ikonos image fusion process using support value transform",

abstract = "Panehromatic (Pan)-sharpening of muttispectral (MS) bands is an important technique in various applications of satellite remote sensing. In this paper, we apply the support value transform (SVT) to lkonos image fusion. The fused saliency features are represented by support values and extracted by SVT. The low-resolution MS bands are resampled to the fine scale of the Pan image and sharpened by injecting the detailed features extracted from the high-resolution Pan image. The fusing results on Ikonos MS + Pan data demonstrate that the proposed image fusion method is effective and efficient.",

keywords = "Ikonos image fusion, Mapped least squares support vector machine (mapped LS-SVM), Support value transform (SVT)",

author = "Sheng Zheng and Wenzhong Shi and Jian Liu",

year = "2007",

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doi = "10.1109/ICMLC.2007.4370398",

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Zheng, S, Shi, W & Liu, J 2007, An ikonos image fusion process using support value transform. in Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007. vol. 3, 4370398, pp. 1584-1589, 6th International Conference on Machine Learning and Cybernetics, ICMLC 2007, Hong Kong, Hong Kong, 19/08/07. https://doi.org/10.1109/ICMLC.2007.4370398

An ikonos image fusion process using support value transform. / Zheng, Sheng; Shi, Wenzhong; Liu, Jian.
Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007. Vol. 3 2007. p. 1584-1589 4370398.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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N2 - Panehromatic (Pan)-sharpening of muttispectral (MS) bands is an important technique in various applications of satellite remote sensing. In this paper, we apply the support value transform (SVT) to lkonos image fusion. The fused saliency features are represented by support values and extracted by SVT. The low-resolution MS bands are resampled to the fine scale of the Pan image and sharpened by injecting the detailed features extracted from the high-resolution Pan image. The fusing results on Ikonos MS + Pan data demonstrate that the proposed image fusion method is effective and efficient.

AB - Panehromatic (Pan)-sharpening of muttispectral (MS) bands is an important technique in various applications of satellite remote sensing. In this paper, we apply the support value transform (SVT) to lkonos image fusion. The fused saliency features are represented by support values and extracted by SVT. The low-resolution MS bands are resampled to the fine scale of the Pan image and sharpened by injecting the detailed features extracted from the high-resolution Pan image. The fusing results on Ikonos MS + Pan data demonstrate that the proposed image fusion method is effective and efficient.

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KW - Mapped least squares support vector machine (mapped LS-SVM)

KW - Support value transform (SVT)

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BT - Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007

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ER -

An ikonos image fusion process using support value transform

Abstract

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Keywords

ASJC Scopus subject areas

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