International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

An Efficient Satellite Image Classification Method Using Cellular Automata

Author : Minu Nair S ¹ Bindhu J S ²

Date of Publication :7th February 2016

Abstract: Remote Sensing is a multi-disciplinary technique for image acquisition and exploitation. A major goal of remote sensing is data analysis and interpretation. Remote sensing analysis paved way for satellite image classification which facilitates the image interpretation of large amount of data. Satellite Images covers large geographical span and results in the exploitation of huge information which includes classifying into different sectors. Different classification algorithms exist for classifying satellite images but for variety of applications a classification technique with improved performance in terms of accuracy is required. Classification based on cellular automata offers many advantages that improve the result of classical classification algorithms. The concept groups together classification and post-classification processes for producing a highly accurate classified image. The proposed paper performs spectral and contextual classification incorporating fuzzy rules and states for attaining improved accuracy and can configure a personalized land use classification. The system improves the satellite image classification accuracy by applying fuzzy rules which is used for eliminating the uncertain pixels obtained when applying the spectral and contextual classification. The resultant classified image will be an image with improved accuracy.

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