A Comparative Study Of Supervised Image Classification Algorithms For Satellite Images
Image classification is a complex information extraction technique. The objective of image classification is to
identify the features occurring in an image and group similar features as clusters. The aim of this study is to compare some
supervised image classification techniques .The techniques considered in this paper are Minimum Distance, k-Nearest
Neighbour (KNN), Nearest Clustering Fuzzy C-Means (FCM) and Maximum Likelihood (ML) Classification algorithms.
All the techniques are compared and analysed for best results and maximum accuracy