An Agglomerative Hierarchical Clustering Based High-Resolution Remote Sensing Image Segmentation Algorithm

Remote sensing image segmentation is the basis of image pattern recognition. It is significant for the application and analysis of remote sensing images. Clustering analysis as a non-supervised learning method is widely used in the segmentation of remote sensing images. It has made good results in the segmentation of low-resolution and moderate-resolution remote sensing images. As the improvement of image resolution, however, they have problems in the segmentation of high-resolution remote sensing images. In this paper we propose an agglomerative hierarchical clustering based high-resolution remote sensing image segmentation algorithm. The segmentation experiments show that the result of this algorithm is better than the K-Meanspsila and is close to the results of artificial extraction.