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  • 标题:Information Extraction of High-Resolution Remotely Sensed Image based on Multiresolution Segmentation
  • 本地全文:下载
  • 作者:P. Shao ; G.-D. Yang ; X.-F. Niu
  • 期刊名称:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
  • 印刷版ISSN:2194-9042
  • 电子版ISSN:2194-9050
  • 出版年度:2013
  • 卷号:XL-4/W3
  • 页码:117-121
  • DOI:10.5194/isprsarchives-XL-4-W3-117-2013
  • 出版社:Copernicus Publications
  • 摘要:The principle of multiresolution segmentation was represented in detail in this study, and the canny algorithm was applied for edge-detection of remotely sensed image based on this principle. The target image was divided into regions based on objectoriented multiresolution segmentation and edge-detection. Further, object hierarchy was created, and a series of features (water bodies, vegetation, roads, residential areas, bare land and other information) were extracted by the spectral and geometrical features. The results indicates that edge-detection make a positive effect on multiresolution segmentation, and overall accuracy of information extraction reaches to 94.6% through confusion matrix
  • 关键词:Edge-detection; Object-oriented. Multiresolution segmentation; Spectral features; Geometrical features; Confusion matrix
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