Best of breed solution for clustering of satellite images using bigdata platform spark

摘要

Clustering is the unsupervised process of assigning entities into groups based on similarities among those entities. Image clustering is the crucial step of mining satellite images. As the satellite imagery is getting generated at a higher rate than the previous decades, it becomes essential to have better solutions in terms of accuracy as well as performance. In this paper, we are proposing the solution over big data platform Apache Spark which performs the clustering of images using different methods viz. Scalable K-means++, Bisecting K-means and Gaussian Mixture. Since the number of clusters is not known in advance in any of the methods, we also propose a Best of Breed approach of validating the number of clusters using Simple Silhouette Index algorithm and thus to provide the best clustering possible.