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Proceedings Paper

Semantic structure tree with application to remote sensing image segmentation
Author(s): Xiangrong Zhang; Xian Pan; Biao Hou; Licheng Jiao
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Paper Abstract

This paper presents a new method based on Semantic Structure Tree (SST) for remote sensing image segmentation, in which, the semantic image analysis is used to construct the SST of the image. The leaves of the SST represent the semantics of the image and serve as human semantic understanding of the image. The root of the tree is the whole image. The SST uses grammar rules to construct a hierarchy structure of the image and gives a complete high-level semantics contents description of the image. Experimental results show that the tree can give efficient description of the semantic content of the remote sensing image, and can be well used in remote sensing image segmentation.

Paper Details

Date Published: 22 October 2010
PDF: 6 pages
Proc. SPIE 7830, Image and Signal Processing for Remote Sensing XVI, 78301C (22 October 2010); doi: 10.1117/12.864814
Show Author Affiliations
Xiangrong Zhang, Xidian Univ. (China)
Xian Pan, Xidian Univ. (China)
Biao Hou, Xidian Univ. (China)
Licheng Jiao, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 7830:
Image and Signal Processing for Remote Sensing XVI
Lorenzo Bruzzone, Editor(s)

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