An Adaptive Approach for Hybrid OPF Algorithm for the Classification of Remote Sensing Image Processing

Abstract

Remote sensing is the process of gathering data about the earth’s surface without being in contact with it. In remote sensing, the image processing techniques can be categorise in to three main processing stages: Image pre- processing, Enhancement and Classification.  Image pre-processing is the initial processing which deals with correcting radiometric distortions, atmospheric distortion and geometric distortions present in the raw image data. Enhancement techniques are applied to preprocessed data in order to effectively display the image for visual interpretation. Using DBSCAN the image is classified into vegetation, water bodies, waste land and built-up region. In this, the classification is optimized using Cuckoo search algorithm (CSA).  It includes techniques to effectively distinguish surface features for visual interpretation.