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Radiometrically accurate scene-based nonuniformity correction for array sensors.

Bradley M Ratliff1, Majeed M Hayat, J Scott Tyo

  • 1Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, New Mexico 87131-1356, USA. bratliff@eece.unm.edu

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|October 23, 2003
PubMed
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This study introduces a new method for nonuniformity correction (NUC) in infrared cameras. It achieves radiometric accuracy by combining absolute calibration with an algebraic scene-based algorithm, improving image quality without camera disruption.

Area of Science:

  • Infrared imaging technology
  • Optical sensor calibration
  • Image processing algorithms

Background:

  • Nonuniformity correction (NUC) is crucial for accurate infrared imaging.
  • Existing NUC methods can be complex or disrupt camera operation.
  • Radiometric accuracy is essential for quantitative analysis of infrared data.

Purpose of the Study:

  • To develop a novel, radiometrically accurate scene-based nonuniformity correction (NUC) algorithm.
  • To combine absolute calibration with an algebraic scene-based NUC technique.
  • To achieve accurate NUC without interrupting camera functionality.

Main Methods:

  • Absolute calibration of perimeter detectors on the focal-plane array.
  • Application of an algebraic scene-based NUC algorithm using image frame pairs with motion.

Related Experiment Videos

  • Transferring calibration from exterior to interior detectors.
  • Main Results:

    • The proposed technique achieves radiometric accuracy during NUC.
    • Accurate bias nonuniformity estimation is possible with fewer than ten frame pairs.
    • The method functions without disrupting camera operation.

    Conclusions:

    • The combined absolute and algebraic scene-based NUC approach offers a robust solution.
    • This technique enhances radiometric accuracy in infrared imaging systems.
    • It provides an efficient and non-disruptive method for NUC.