Searching satellite imagery with integrated measures

Due to the advances in imaging and storage technologies, the number and size of images continue to grow at a rapid pace. This problem is particularly acute in the case of remotely sensed imagery. The continuous stream of sensory data from satellites poses major challenges in storage and retrieval of the satellite imagery. In the mean time, the ubiquity of Internet has resulted into an ever-growing population of users searching for various forms of information. In this paper, we describe the search engine SIMR—Satellite Image Matching and Retrieval system. SIMR provides an efficient means to match remotely sensed imagery. It computes spectral and spatial attributes of the images using a hierarchical representation. A unique aspect of our approach is the coupling of second-level spatial autocorrelation with quad tree structure. The efficiency of the web-based SIMR has been evaluated using a database of images with known characteristics: cities, towns, airports, lakes, and mountains. Results show that the integrated signature can be an effective basis for accurately searching databases of satellite based imagery.