Multi-feature adaptive classifiers for SAR image segmentation

被引：28

作者：

Ceccarelli, M ^{[1
]}

Petrosino, A ^{[1
]}

机构：

[1] CNR,IRSIP,I-80131 NAPLES,ITALY

来源：

NEUROCOMPUTING | 1997年 / 14卷 / 04期

关键词：

neural networks; image segmentation; ensemble classification;

D O I：

10.1016/S0925-2312(96)00038-0

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We propose a multifeature scheme for terrain classification in SAR image analysis, Different neural classifiers, trained on different features of the same sample space, are combined by using a non-linear ensemble method. The feature extraction modules are chosen in order to discover the textural and contextual characteristics within the neighbourhood of each pixel. Comparisons with classical data fusion techniques and consensus schema are reported.

引用

页码：345 / 363

页数：19

共 37 条

[1]

[Anonymous], 1986, STAT SCI

[2]

[Anonymous], 1982, Pattern recognition: A statistical approach

[3] TERRAIN CLASSIFICATION IN SAR IMAGES USING PRINCIPAL COMPONENTS-ANALYSIS AND NEURAL NETWORKS [J].