A Fast Search System for Remote Sensing Imagery Based On Bag Of Visual Words and Latent Dirichlet Allocation

Abstract

In this paper, we present our image search system for remote sensing imagery leveraging the capabilities of Elasticsearch, a well-known full-text search engine. We use bag of visual words and bag of visual topics model to represent the earth observation images in a text- equivalent format. The image files are stored in Elasticsearch in their text-equivalent format, making it feasible to apply some sophisticated textbased search functionalities of Elasticsearch on the data. This gives great flexibility to the search clauses allowing the user to match chosen fragments of images. We also implement visual topic search which enables search by higher level semantics. The proposed methods are simple and fast as they do not require any complex image feature computation