Classification Of Cluster Area Forsatellite Image
Thwe Zin Phyo, Aung Soe Khaing, Hla Myo Tun
Keywords: Image segmentation, K-means clustering Algorithm, Remote sensing, content classification.
Abstract: This paper describes area classification for Landsat7 satellite image. The main purpose of this system is to classify the area of each cluster contained in a satellite image. To classify this image, firstly need to clusterthe satellite image into different land cover types. Clustering is an unsupervised learning method that aimsto classify an image into homogeneous regions. This system is implemented based on color features with K-means clustering unsupervised algorithm. This method does not need to train image before clustering.The clusters of satellite image are grouped into a set of three clusters for Landsat7 satellite image. For this work, the combined band 432 from Landsat7 satellite is used as an input. Satellite image(Mandalay area in 2001) is chosen to test the segmentation method. After clustering, a specific range for three clustered images must be defined in order to obtain greenland, water and urban+balance.This system is implemented by using MATLAB programming language.
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