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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