Paper Title
Pixel Classification in Remote Sensing Imagery using Multiobjective Genetic Clustering

Classification in remote sensing images is the clustering of pixels in the spectral domain into several fuzzy partitions. In this paper, a multiobjective optimization algorithm is utilized to tackle the problem of fuzzy partitioning where a number of fuzzy cluster validity indexes are simultaneously optimized. Real-coded encoding of the cluster centers is used for this purpose Results demonstrating the effectiveness of the proposed technique are provided for numeric remote sensing data described in terms of feature vectors. Different land cover regions in remote sensing imagery have also been classified using the proposed technique to establish its efficiency. Keyword - Cluster Validity Measures, Genetic Algorithm (GA), Multiobjective Optimization (MOO), Pareto-Optimal, Remote Sensing Application