ISODATA classification using Fuzzy Logic

Abstract

In current days remote sensing is mainly recent application in many sectors. Remote Sensing (RS) refers to the science of identification of earth surface facet and analysis of their geo-biophysical property via electromagnetic emission as a model for interaction. Spectral, spatial, temporal and polarization signatures are key features of the sensor/target, which make easy target bias. Earth surface data seen by the sensors in altered wavelengths (reflected, scattered and/or emitted) is radio metrically and geometrically right by extraction of spectral data. RS data is a synoptic read, pedestrian exposure with calibrate sensors to work out changes, observations at various resolutions, deals with a alternative for normal resources management as compare to standard methods. This remote sensing utilizes dissimilar images like multispectral, hyper spectral or ultra-spectral. The remote sensing image classification is being of the significant methods to sort image. In order to state we classify the ISODATA classification amid fuzzy logic. In this we experimenting fuzzy logic be affectionate of spatial, spectral texture methods in that dissimilar sub methods to be worn for image classification.