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


Autoria(s): BARBIERI, Andre L.; ARRUDA, G. F. de; RODRIGUES, Francisco A.; BRUNO, Odemir M.; COSTA, Luciano da Fontoura
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

20/10/2012

20/10/2012

2011

Resumo

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.

FAPESP[proc. 05/00587-5]

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

FAPESP[proc. 07/50633-9]

CNPq[proc. 301303/06-1]

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

CNPq[306628/2007-4]

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

CNPq[484474/2007-3]

Identificador

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, v.390, n.3, p.512-518, 2011

0378-4371

http://producao.usp.br/handle/BDPI/29829

10.1016/j.physa.2010.10.015

http://dx.doi.org/10.1016/j.physa.2010.10.015

Idioma(s)

eng

Publicador

ELSEVIER SCIENCE BV

Relação

Physica A-statistical Mechanics and Its Applications

Direitos

restrictedAccess

Copyright ELSEVIER SCIENCE BV

Palavras-Chave #Entropy #Information theory #Pattern recognition #Image analysis #Physics, Multidisciplinary
Tipo

article

original article

publishedVersion