A hybrid FPAB/BBO Algorithm for Satellite Image Classification

In the past years, remote sensing has been used for the classification of satellite image on a very large scale. This paper deals with image classification by using swarm computing technique. In this work, we use a new swarm data clustering method based upon flower pollination by artificial bees to cluster the satellite image pixels. The aim of clustering is to separate a set of data points into self-similar groups. Those clusters will be further classified using Biogeography Based Optimization. The results indicate that highly accurate classification of the satellite image is obtained by using the proposed algorithm.