Automating Image Processing for Scientific Data Analysis of a Large Image Database

  • Authors:
  • Steve A. Chien;Helen B. Mortensen

  • Affiliations:
  • -;-

  • Venue:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Year:
  • 1996

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Abstract

This article describes the Multimission VICAR Planner (MVP): an AI planning system which uses knowledge about image processing steps and their requirements to construct executable image processing scripts to support high-level science requests made to the Jet Propulsion Laboratory (JPL) Multimission Image Processing Subsystem (MIPS). This article describes a general AI planning approach to automation and application of the approach to a specific area of image processing for planetary science applications involving radiometric correction, color triplet reconstruction, and mosaicing in which the MVP system significantly reduces the amount of effort required by image processing experts to fill a typical request.