INFORMATION EXTRACTION OF HIGH-RESOLUTION REMOTELY SENSED IMAGE BASED ON MULTIRESOLUTION SEGMENTATION

被引：0
|
作者：
Shao Peng [1 ]
Yang Guodong [1 ]
Niu Xuefeng [1 ]
Zhang Xuqing [1 ]
Zhan Fulei [1 ]
Tang Tianqi [1 ]
机构：
[1] Jilin Univ, Coll Geoexplorat Sci & Technol, Changchun 130026, Jilin Province, Peoples R China
来源：
ISPRS/IGU/ICA JOINT WORKSHOP ON BORDERLANDS MODELLING AND UNDERSTANDING FOR GLOBAL SUSTAINABILITY 2013 | 2013年 / 40-4-W3卷
关键词：
Edge-detection; Object-oriented; Multiresolution segmentation; Spectral features; Geometrical features; Confusion matrix;
D O I：
10.5194/isprsarchives-XL-4-W3-117-2013
中图分类号：
P9 [自然地理学];
学科分类号：
0705 ; 070501 ;
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 object-oriented 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.
引用
收藏
页码：117 / 121
页数：5
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