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22 October 2010 Semantic structure tree with application to remote sensing image segmentation
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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.
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Xiangrong Zhang, Xian Pan, Biao Hou, and Licheng Jiao "Semantic structure tree with application to remote sensing image segmentation", Proc. SPIE 7830, Image and Signal Processing for Remote Sensing XVI, 78301C (22 October 2010); https://doi.org/10.1117/12.864814
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