A statistical approach to the fusion of spectral and spatio-temporal contextual information for the classification of remote-sensing images

被引：52

作者：

Melgani, F ^{[1
]}

Serpico, SB ^{[1
]}

机构：

[1] Univ Genoa, Dept Biophys & Elect Engn, I-16145 Genoa, Italy

来源：

PATTERN RECOGNITION LETTERS | 2002年 / 23卷 / 09期

关键词：

remote-sensing image classification; spatio-temporal context; data fusion; neural networks;

D O I：

10.1016/S0167-8655(02)00052-1

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, an iterative statistical approach is proposed to fuse spectral information with spatial and temporal contextual information for the classification of multitemporal, multisensor remote-sensing images. Experimental results show, in terms of classification accuracy, the improvement that can be reached by exploiting the contextual information. (C) 2002 Elsevier Science B.V. All rights reserved.

引用

页码：1053 / 1061

页数：9

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