Supervised classification of satellite imagery using Enhanced seeded region growing technique

Abstract

The image classifications techniques have been practiced by remote sensing experts following certain methods like unsupervised and supervised. Supervised classification requires precise human intervention to extract features. Enhanced Seeded region growing technique is an image segmentation method; where the image pixel is seeded by latitude and longitude recorded during ground truth data collection using GPS. The Enhanced seeded region growing technique generates clusters based upon 8 nearest neighbor pixel connections. Pattern recognition standard software is trained for the spectral signatures of the corresponding pixels. Then the supervised classification algorithm can be used. The system can leverage the potential of Location based services (LBS) and Information Communication Technology (ICT) to dynamically pull the latitude and longitude from the server using web services and gateway protocols. This method requires less effort to extract features from the image. This scheme is applied on satellite imagery covering surendranagar district in Gujarat, India.