An agglomerative hierarchical clustering based high-resolution remote sensing image segmentation algorithm

Rongjie Liu; Jie Zhang; Pingjian Song; Fengjing Shao; Guanfeng Liu

doi:10.1109/CSSE.2008.1017

An agglomerative hierarchical clustering based high-resolution remote sensing image segmentation algorithm

Rongjie Liu^*, Jie Zhang, Pingjian Song, Fengjing Shao, Guanfeng Liu

^*Corresponding author for this work

School of Computing

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

9 Citations (Scopus)

Abstract

Remote sensing image segmentation is the basis of image pattern recognition. It is significant for the application and analysis of remote sensing images. Clustering analysis as a non-supervised learning method is widely used in the segmentation of remote sensing images. It has made good results in the segmentation of low-resolution and moderate-resolution remote sensing images. As the improvement of image resolution, however, they have problems in the segmentation of high-resolution remote sensing images. In this paper we propose an Agglomerative Hierarchical Clustering based High-Resolution Remote Sensing Image Segmentation Algorithm. The segmentation experiments show that the result of this algorithm is better than the K-Means' and is close to the results of artificial extraction.

Original language	English
Title of host publication	Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008
Pages	403-406
Number of pages	4
Volume	4
DOIs	https://doi.org/10.1109/CSSE.2008.1017
Publication status	Published - 2008
Event	International Conference on Computer Science and Software Engineering, CSSE 2008 - Wuhan, Hubei, China Duration: 12 Dec 2008 → 14 Dec 2008

Other

Other	International Conference on Computer Science and Software Engineering, CSSE 2008
Country/Territory	China
City	Wuhan, Hubei
Period	12/12/08 → 14/12/08

Keywords

Agglomerative hierarchical clustering method
High-resolution remote sensing image segmentation
Remote sensing

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10.1109/CSSE.2008.1017

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title = "An agglomerative hierarchical clustering based high-resolution remote sensing image segmentation algorithm",

abstract = "Remote sensing image segmentation is the basis of image pattern recognition. It is significant for the application and analysis of remote sensing images. Clustering analysis as a non-supervised learning method is widely used in the segmentation of remote sensing images. It has made good results in the segmentation of low-resolution and moderate-resolution remote sensing images. As the improvement of image resolution, however, they have problems in the segmentation of high-resolution remote sensing images. In this paper we propose an Agglomerative Hierarchical Clustering based High-Resolution Remote Sensing Image Segmentation Algorithm. The segmentation experiments show that the result of this algorithm is better than the K-Means' and is close to the results of artificial extraction.",

keywords = "Agglomerative hierarchical clustering method, High-resolution remote sensing image segmentation, Remote sensing",

author = "Rongjie Liu and Jie Zhang and Pingjian Song and Fengjing Shao and Guanfeng Liu",

year = "2008",

doi = "10.1109/CSSE.2008.1017",

language = "English",

isbn = "9780769533360",

volume = "4",

pages = "403--406",

booktitle = "Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008",

note = "International Conference on Computer Science and Software Engineering, CSSE 2008 ; Conference date: 12-12-2008 Through 14-12-2008",

}

Liu, R, Zhang, J, Song, P, Shao, F & Liu, G 2008, An agglomerative hierarchical clustering based high-resolution remote sensing image segmentation algorithm. in Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008. vol. 4, 4722644, pp. 403-406, International Conference on Computer Science and Software Engineering, CSSE 2008, Wuhan, Hubei, China, 12/12/08. https://doi.org/10.1109/CSSE.2008.1017

An agglomerative hierarchical clustering based high-resolution remote sensing image segmentation algorithm. / Liu, Rongjie; Zhang, Jie; Song, Pingjian et al.
Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008. Vol. 4 2008. p. 403-406 4722644.

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

TY - GEN

T1 - An agglomerative hierarchical clustering based high-resolution remote sensing image segmentation algorithm

AU - Liu, Rongjie

AU - Zhang, Jie

AU - Song, Pingjian

AU - Shao, Fengjing

AU - Liu, Guanfeng

PY - 2008

Y1 - 2008

N2 - Remote sensing image segmentation is the basis of image pattern recognition. It is significant for the application and analysis of remote sensing images. Clustering analysis as a non-supervised learning method is widely used in the segmentation of remote sensing images. It has made good results in the segmentation of low-resolution and moderate-resolution remote sensing images. As the improvement of image resolution, however, they have problems in the segmentation of high-resolution remote sensing images. In this paper we propose an Agglomerative Hierarchical Clustering based High-Resolution Remote Sensing Image Segmentation Algorithm. The segmentation experiments show that the result of this algorithm is better than the K-Means' and is close to the results of artificial extraction.

AB - Remote sensing image segmentation is the basis of image pattern recognition. It is significant for the application and analysis of remote sensing images. Clustering analysis as a non-supervised learning method is widely used in the segmentation of remote sensing images. It has made good results in the segmentation of low-resolution and moderate-resolution remote sensing images. As the improvement of image resolution, however, they have problems in the segmentation of high-resolution remote sensing images. In this paper we propose an Agglomerative Hierarchical Clustering based High-Resolution Remote Sensing Image Segmentation Algorithm. The segmentation experiments show that the result of this algorithm is better than the K-Means' and is close to the results of artificial extraction.

KW - Agglomerative hierarchical clustering method

KW - High-resolution remote sensing image segmentation

KW - Remote sensing

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U2 - 10.1109/CSSE.2008.1017

DO - 10.1109/CSSE.2008.1017

M3 - Conference proceeding contribution

AN - SCOPUS:79951479459

SN - 9780769533360

VL - 4

SP - 403

EP - 406

BT - Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008

T2 - International Conference on Computer Science and Software Engineering, CSSE 2008

Y2 - 12 December 2008 through 14 December 2008

ER -

An agglomerative hierarchical clustering based high-resolution remote sensing image segmentation algorithm

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