Algorithms 2013, 6(4), 762-781; doi:10.3390/a6040762
Very High Resolution Satellite Image Classification Using Fuzzy Rule-Based Systems
Department of Geodesy and Geomatics Engineering, University of New Brunswick, 15 Dineen Drive, Fredericton, NB E3B 5A3, Canada
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Received: 23 August 2013 / Revised: 22 October 2013 / Accepted: 6 November 2013 / Published: 12 November 2013
(This article belongs to the Special Issue Fuzzy Algorithms for Decision Making and Data Analysis)
Abstract
The aim of this research is to present a detailed step-by-step method for classification of very high resolution urban satellite images (VHRSI) into specific classes such as road, building, vegetation, etc., using fuzzy logic. In this study, object-based image analysis is used for image classification. The main problems in high resolution image classification are the uncertainties in the position of object borders in satellite images and also multiplex resemblance of the segments to different classes. In order to solve this problem, fuzzy logic is used for image classification, since it provides the possibility of image analysis using multiple parameters without requiring inclusion of certain thresholds in the class assignment process. In this study, an inclusive semi-automatic method for image classification is offered, which presents the configuration of the related fuzzy functions as well as fuzzy rules. The produced results are compared to the results of a normal classification using the same parameters, but with crisp rules. The overall accuracies and kappa coefficients of the presented method stand higher than the check projects. View Full-TextKeywords:
fuzzy rule based systems; object-based image classification; very high resolution satellite imagery; urban land cover
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MDPI and ACS Style
Jabari, S.; Zhang, Y. Very High Resolution Satellite Image Classification Using Fuzzy Rule-Based Systems. Algorithms 2013, 6, 762-781.
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Algorithms
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