Neural Network and Fuzzy Logic Approach for Satellite Image Classification: A Review

Image classification is the important part of remote sensing, image analysis and pattern recognition. Digital Image Classification is the process of sorting all the pixels in an image into a finite number of individual classes. Landuse/Landcover classification of satellite images is an important activity for extracting geospatial information for military & civil purposes like inaccessible areas. It is difficult to classify satellites image manually. So computer aided techniques are used. The images can be classified by probabilistic techniques, maximum likelihood classifier, parallelepiped etc. but these are very slow and accuracy is very less. It is not easy to obtain perfect data in real world since most data contains errors and omissions. To overcome this soft computing techniques which are based on uncertainty like fuzzy set theory, rough set theory and artificial neural network are used. The aim of soft computing is to model human perceptions of the world with inexact expression.