基于图像内容层次表征的遥感图像分割

method of high-spatial resolution remotely sensed imagery segmentation based on the hierarchical representation of image content is proposed in the paper. The hierarchical representation is built through a hierarchical merging process based on initial segmentation. First, we build the region Adjacency Graph (RAG) on which Markov Random Field (MRF) is defined. Then the hierarchical merging process, where the merging criterion includes the multi-spectral, edge and shape features, is applied and recorded on the RAG to obtain the hierarchical representation. It is quite efficient to produce a number of segmentation results with different precision using relationship of different objects in the hierarchical representation. Experimental results on QuickBird images show that the proposed method can improve segmentation efficiency greatly and produce results with high quality.