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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 38, Iss. 28 — Oct. 1, 1999
  • pp: 5936–5943

Sensor Performance Conversions for Infrared Target Acquisition and Intelligence-Surveillance- Reconnaissance Imaging Sensors

Ronald G. Driggers, Mel Kruer, Dean Scribner, Penny Warren, and Jon Leachtenauer  »View Author Affiliations


Applied Optics, Vol. 38, Issue 28, pp. 5936-5943 (1999)
http://dx.doi.org/10.1364/AO.38.005936


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Abstract

Target acquisition infrared imaging sensors are characterized by their minimum resolvable temperature parameter that is translated to the probability of identification (Pid) performance estimate for a given target. Intelligence–surveillance–reconnaissance (ISR) sensors are characterized by the general image quality equation to give a national imagery interpretability rating scale (NIIRS) performance estimate. Sensors, such as those on Predator and Global Hawk, will soon be used for both ISR and target acquisition purposes. We present a performance conversion that includes both sensor resolution and sensitivity. We also provide the first empirical results to our knowledge ever to be presented that relate NIIRS and Pid for a given set of targets.

© 1999 Optical Society of America

OCIS Codes
(040.3060) Detectors : Infrared
(100.2960) Image processing : Image analysis
(100.5010) Image processing : Pattern recognition

Citation
Ronald G. Driggers, Mel Kruer, Dean Scribner, Penny Warren, and Jon Leachtenauer, "Sensor Performance Conversions for Infrared Target Acquisition and Intelligence-Surveillance- Reconnaissance Imaging Sensors," Appl. Opt. 38, 5936-5943 (1999)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-38-28-5936


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References

  1. R. Driggers, P. Cox, J. Leachtenauer, R. Vollmerhausen, and D. Scribner, “Targeting and intelligence electro-optical recognition modeling: a juxtaposition of the probabilities of discrimination and the general image quality equation,” Opt. Eng. 37, 789–797 (1998).
  2. J. Johnson, “Analysis of image-forming systems,” in Proceedings of the Image Intensifier Symposium (Warfare Vision Branch, Electrical Engineering Department, U.S. Army Engineering Development Laboratories, Ft. Belvoir, Va., 1958), pp. 249–273.
  3. J. Lloyd, Thermal Imaging Systems (Plenum, New York, 1975), p. 183.
  4. R. Sendall and F. Rosell, “EO sensor performance analysis and synthesis (TV/IR comparison study), Final Report AFAL-TR-72–374 (U.S. Air Force Avionics Laboratory, Wright-Patterson Air Force Base, Dayton, Ohio, 1973).
  5. J. Ratches, “NVL static performance model for thermal viewing systems,” Report ECOM 7043, AD-A011212 (U.S. Army Electronics Command, Fort Monmouth, N.J., 1975).
  6. J. C. Leachtenauer, “National imagery interpretability rating scales: overview and product description,” in APRS/ASCM Annual Convention and Exhibition Technical Papers: Remote Sensing and Photogrammetry (American Society for Photogrammetry and Remote Sensing and American Congress on Surveying and Mapping, Baltimore, Md., 1996), Vol. 1, pp. 262–272.
  7. J. Leachtenauer, W. Malila, J. Irvine, L. Colburn, and N. Salvaggio, “General image quality equations: GIQE,” Appl. Opt. 36, 8322–8328 (1997).

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