红外与毫米波学报2018，Vol.37Issue(2)：177-183,7.DOI:10.11972/j.issn.1001-9014.2018.02.009
基于稀疏自编码器和边缘保持的Wishart马尔科夫随机场的极化SAR图像分类
PolSAR image classification based on sparse autoencoder and boundary-preserved WMRF
摘要
Abstract
In order to solve problem of the limited training samples and keep consistency in one region,a new two-level classification scheme is proposed, which combines sparse auto-encoder(SAE)and Boundary-preserved Wishart-markov random fields(BWMRF).In the first layer,an SAE classifier is applied to obtain an initial classi-fication and more accurate regional boundaries.In the second layer, Boundary-preserved Wishart-markov random fields have been used to correct the previous classification results.Meanwhile, the boundaries classified by sparse auto-encoder are preserved, and a new error correction strategy is applied to ensure the classification accuracy. Therefore,accurate region boundaries supplied by SAE are explored to divide different regions,and the coherent in each region will be realized during the BWMRF process.Compared with other classification methods,this method obtains higher classification accuracy and proves the validity of the new scheme.关键词
稀疏自编码器/极化SAR图像/Wishart距离/马尔科夫随机场Key words
sparse auto-encoder(SAE)/polarimetric synthetic aperture radar(PolSAR)images/Wishart dis-tance/Markov random fields(MRF)分类
信息技术与安全科学引用本文复制引用
张姝茵,侯彪,焦李成,吴倩..基于稀疏自编码器和边缘保持的Wishart马尔科夫随机场的极化SAR图像分类[J].红外与毫米波学报,2018,37(2):177-183,7.基金项目
Supported by National Natural Science Foundation of China(61671350,61573267,61473215,61572383,61502369),and the National Basic Research Program(973 Program)of China(2013CB329402) （61671350,61573267,61473215,61572383,61502369）
