Developing operational performance metrics using image comparison metrics and the concept of degradation space

Carl E. Halford, Keith A. Krapels, Ronald G. Driggers, Ellis E. Burroughs

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

A technique for determining relative degradations from image metrics is presented along with a technique for predicting sensor performance from metrics. These techniques are illustrated with degradations of blur and noise in thermal imagery. These uses of metrics are depicted as mappings among a degradation space, an image quality metric space, and an operational performance space. This technique has utility in sampled imagery applications where input and output image comparison is possible, e.g., validation of an infrared scene projector (IRSP), testing image compression algorithms, image simulation, etc. Such applications have a known input image and a degraded output image. With the input image, one can characterize the output image in terms of its degradations relative to the input. The concept of a degradation space leads to developing an Operational Performance Metric (OPM) in terms of more traditional Image Quality Metrics (IQMs). The technique is illustrated using empirical results for human observers performing recognition tasks with thermal imagery in a degradation space of blur and noise.

Original languageEnglish (US)
Pages (from-to)836-844
Number of pages9
JournalOptical Engineering
Volume38
Issue number5
DOIs
StatePublished - May 1999
Externally publishedYes

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering(all)

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