• Journal of Infrared and Millimeter Waves
  • Vol. 39, Issue 2, 263 (2020)
Liang HUANG1、2, Bing-Xiu YAO1、*, Peng-Di CHEN1, Ai-Ping REN1, and Yan XIA1
Author Affiliations
  • 1Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming650093, China
  • 2Surveying and Mapping Geo-Informatics Technology Research Center on Plateau Mountains of Yunnan Higher Education, Kunming650093, China
  • show less
    DOI: 10.11972/j.issn.1001-9014.2020.02.014 Cite this Article
    Liang HUANG, Bing-Xiu YAO, Peng-Di CHEN, Ai-Ping REN, Yan XIA. Superpixel segmentation method of high resolution remote sensing images based on hierarchical clustering[J]. Journal of Infrared and Millimeter Waves, 2020, 39(2): 263 Copy Citation Text show less

    Abstract

    To solve the problem of automatic selection the segmentation scale in remote sensing image, a superpixel segmentation method of high resolution remote sensing image based on hierarchical clustering is proposed. Firstly, the watershed segmentation algorithm based on adaptive morphological reconstruction is used to segment the image into multiple superpixels. Then, the gray feature vectors of each superpixel is extracted. Finally, the hierarchical clustering method is adopted to merge the superpixels, the accurate segmentation of high-resolution remote sensing images is realized. Four sets of remote sensing images are selected in the experiment, and the experimental results are evaluated by a combination of qualitative and quantitative methods. Experimental results shown that the proposed method effectively improves the segmentation accuracy of remote sensing images, and better segmentation visual effects are obtained.
    Liang HUANG, Bing-Xiu YAO, Peng-Di CHEN, Ai-Ping REN, Yan XIA. Superpixel segmentation method of high resolution remote sensing images based on hierarchical clustering[J]. Journal of Infrared and Millimeter Waves, 2020, 39(2): 263
    Download Citation