Multiscale Markov Random Field Method for SAR Image Segmentation

被引：0
|
作者：
Zhang, Jian-Guang [1 ]
Wen, Xian-Bin
Jiao, Xu
Wang, Lei
机构：
[1] Tianjin Univ Technol, Key Lab Comp Vis & Syst, Minist Educ, Tianjin 300191, Peoples R China
来源：
PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9 | 2009年
基金：
中国国家自然科学基金;
关键词：
Multiscale Autoregressive Model; markove random field; Synthetic aperture radar; Image Segmentation; AUTOREGRESSIVE PROCESSES; TEXTURED IMAGES; ALGORITHM;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a multiscale markov random field method for segmentation of the synthetic aperture radar (SAR) images is proposed. A classifier which inherits the strongpoint of the markov random field (MRF) and the multiscale autoregressive (MAR) model is designed. The MAR models are utilized to extract the multiscale feature of SAR image, which is used to train the MRF with the proposed algorithm, and then the SAR images is segmented by the trained random field. The experimental result demonstrates the effectiveness and efficiency of the proposed method.
引用
收藏
页码：1846 / 1850
页数：5
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