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

Author(s)

Barbieri, Andre L. ^[1] ; de Arruda, G. F. ^[1] ; Rodrigues, Francisco A. ^[2] ; Bruno, Odemir M. ^[1] ; Costa, Luciano da Fontoura ^[1]

Affiliation

^[1] Univ Sao Paulo, Inst Fis Sao Carlos, BR-13560970 Sao Carlos, SP - Brazil

^[2] Univ Sao Paulo, Inst Ciencias Matemat & Computacao, Dept Matemat Aplicada & Estat, BR-13560970 Sao Carlos, SP - Brazil

• Document type: Journal article
• Source: PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS; v. 390, n. 3, p. 512-518, FEB 1 2011.
• Web of Science Citations: 27

Abstract

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. (AU)

• FAPESP's process: 05/00587-5 - Mesh (graph) modeling and techniques of pattern recognition: structure, dynamics and applications
• Grantee: Roberto Marcondes Cesar Junior
• Support Opportunities: Research Projects - Thematic Grants