HIERARCHICAL SEGMENTATION FOR POLSAR IMAGE USING MINIMUM SPANNING TREE

被引：0
|
作者：
Deng, Jie [1 ]
Wang, Wei [1 ]
Zhan, Ronghui [1 ]
Zhang, Jun [1 ]
机构：
[1] Natl Univ Def Technol, Coll Elect Sci & Engn, Natl Key Lab Sci & Technol Automat Target Recogni, Changsha 410073, Peoples R China
来源：
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年
关键词：
Superpixel; PolSAR image; minimum spanning tree; hierarchical segmentation; SUPERPIXEL SEGMENTATION; CLASSIFICATION;
D O I：
10.1109/IGARSS46834.2022.9884305
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
Superpixel segmentation is essential to the rapid information extraction and image interpretation. In this paper, we develop a superpixel segmentation method for polarimetric synthetic aperture radar (PolSAR) images, utilizing minimum spanning tree algorithm (MST) to achieve a hierarchy of superpixels. Thereinto, the revised Wishart distance and region intensity distance is applied to accurately measure the dissimilarity between two neighboring pixels. The proposed method can generate superpixels of different scales in real time, so it has significant application value. The performance of the proposed method is validated on experimental PolSAR dataset from the ESAR system.
引用
收藏
页码：979 / 982
页数：4
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