Improved Classification of SAR Sea Ice Imagery Based on Segmentation

被引：2
|
作者：
Yang, Wen [1 ]
He, Chu [1 ]
Cao, Yongfeng [1 ]
Sun, Hong [1 ]
Xu, Xin [1 ]
机构：
[1] Wuhan Univ, Sch Elect Informat, Dept Commun Engn, Signal Proc Lab, Wuhan 430079, Peoples R China
来源：
2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8 | 2006年
关键词：
image classification; watershed segmentation; sea ice; Markov random field model; region adjacency graph; synthtic aperture radar;
D O I：
10.1109/IGARSS.2006.955
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
This paper presents a method for semi-supervised classification of polarimetric synthetic aperture radar (PoISAR) sea ice data. The method consists of two steps. In the first stage, a markov random field on region adjacency graph is constructed on the initial watershed oversegmented result. While in the second stage, the Wishart distribution model and maximum a posterior (MAP) are applied as the criterion for obtaining the optimal classification. Good experimental results and less time-consuming are obtained when this method is applied to PoISAR data sets of sea ice in the Beaufort Sea acquired by the airborne AIRSAR.
引用
收藏
页码：3727 / 3730
页数：4
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