Semantic structure tree with application to remote sensing image segmentation
Xiangrong Zhang, Xian Pan, Biao Hou, Licheng Jiao · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2010
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.