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    Satellite Image Classification using Clustering Algorithms with Edge Detection Operators

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    Image classification consists of image processing algorithms for grouping cells of similar characteristics together. Satellite image classification is essential to extract the information and identify the different components such as water dense region, roads, vegetation etc. from the classified image. In this paper, an attempt is made to locate and identify the different regions of interest using classification algorithms such as K means and Fuzzy-C Means. Comparison is done for both the algorithms in terms of computational time and memory requirements. Also, the algorithms are applied for the input image by considering different values of K and its discussion is presented in the paper. The algorithms are then applied for the given image with edge detection operators to obtain the better visual clarity of the edges
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