Information Extraction of High-Resolution Remotely Sensed Image Based on Multiresolution Segmentation

Sustainability

Peng Shao²  Guodong Yang²  Xuefeng Niu¹  Xuqing Zhang²  Fulei Zhan² 

[1] College of Geo-exploration Science and Technology, Jilin University, Changchun 130026, China;

关键词: edge-detection;    object-oriented;    multiresolution segmentation;    spectral features;    geometrical features;    confusion matrix;   

DOI  :  10.3390/su6085300

来源: mdpi

【 摘 要 】

The principle of multiresolution segmentation was represented in detail in this study, and the canny algorithm was applied for edge-detection of a remotely sensed image based on this principle. The target image was divided into regions based on object-oriented multiresolution segmentation and edge-detection. Furthermore, 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 indicate that the edge-detection has a positive effect on multiresolution segmentation, and overall accuracy of information extraction reaches to 94.6% by the confusion matrix.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.