An entropy-based approach to automatic image segmentation of satellite images

被引：46

作者：

Barbieri, Andre L. ^{[2
]}

de Arruda, G. F. ^{[2
]}

Rodrigues, Francisco A. ^{[1
]}

Bruno, Odemir M. ^{[2
]}

Costa, Luciano da Fontoura ^{[2
]}

机构：

[1] Univ Sao Paulo, Inst Ciencias Matemat & Computacao, Dept Matemat Aplicada & Estat, BR-13560970 Sao Carlos, SP, Brazil

[2] Univ Sao Paulo, Inst Fis Sao Carlos, BR-13560970 Sao Carlos, SP, Brazil

来源：

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | 2011年 / 390卷 / 03期

基金：

巴西圣保罗研究基金会;

关键词：

Entropy; Information theory; Pattern recognition; Image analysis;

D O I：

10.1016/j.physa.2010.10.015

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：512 / 518

页数：7

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