A relevance feedback method based on genetic programming for classification of remote sensing images

被引：41

作者：

dos Santos, J. A. ^{[1
]}

Ferreira, C. D. ^{[1
]}

Torres, R. da S. ^{[1
]}

Goncalves, M. A. ^{[2
]}

Lamparelli, R. A. C. ^{[3
]}

机构：

[1] Univ Estadual Campinas, Inst Comp, Campinas, SP, Brazil

[2] Univ Fed Minas Gerais, Dept Comp Sci, Belo Horizonte, MG, Brazil

[3] Univ Estadual Campinas, Agr Res Ctr, Campinas, SP, Brazil

来源：

INFORMATION SCIENCES | 2011年 / 181卷 / 13期

基金：

巴西圣保罗研究基金会;

关键词：

Content-based image retrieval; Region descriptors; Relevance feedback; Genetic programming; Remote sensing image classification; RETRIEVAL; DISCOVERY; FRAMEWORK; REGION;

D O I：

10.1016/j.ins.2010.02.003

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents an interactive technique for remote sensing image classification. In our proposal, users are able to interact with the classification system, indicating regions of interest (and those which are not). This feedback information is employed by a genetic programming approach to learning user preferences and combining image region descriptors that encode spectral and texture properties. Experiments demonstrate that the proposed method is effective for image classification tasks and outperforms the traditional MaxVer method. (C) 2010 Elsevier Inc. All rights reserved.

引用

页码：2671 / 2684

页数：14

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