Affiliations: [a] Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, MIS 126-347, Pasadena, CA 91109-8099, USA | [b] Department of Geology, Arizona State University, Tempe, AZ 85287-1404, USA
Abstract: In recent times, improvements in imaging technology have made available an incredible array of information in image format. While powerful and sophisticated image processing software tools are available to prepare and analyze the data, these tools are complex and cumbersome, requiring significant expertise to properly operate. Thus, in order to extract (e.g., mine or analyze) useful information from the data, a user (in our case a scientist) often must possess both significant science and image processing expertise. This article describes the use of artificial intelligence (AI) planning techniques to represent scientific, image processing and software tool knowledge to automate knowledge discovery and data mining (e.g., science data analysis) of large image databases. In particular, we describe two fielded systems. The Multimission VICAR Planner (MVP) which has been deployed for since 1995 and is currently supporting science product generation for the Galileo mission. MVP has reduced time to fill certain classes of requests from 4 h to 15 min. The Automated SAR Image Processing system (ASIP) was deployed at the Department of Geology at Arizona State University in 1997 to support aeolian science analysis of synthetic aperture radar images. ASIP reduces the number of manual inputs in science product generation by ten-fold.
Keywords: Planning, Reconfiguration of software modules, Science data analysis
