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  • Research Article
  • Open Access

Fast Adaptive Nonuniformity Correction for Infrared Focal-Plane Array Detectors

EURASIP Journal on Advances in Signal Processing20052005:560759

  • Received: 29 October 2003
  • Published:


A novel adaptive scene-based nonuniformity correction technique is presented. The technique simultaneously estimates detector parameters and performs the nonuniformity correction based on the retina-like neural network approach. The proposed method includes the use of an adaptive learning rate rule in the gain and offset parameter estimation process. This learning rate rule, together with a reduction in the averaging window size used for the parameter estimation, may provide an efficient implementation that should increase the original method's scene-based ability to estimate the fixed-pattern noise. The performance of the proposed algorithm is then evaluated with infrared image sequences with simulated and real fixed-pattern noise. The results show a significative faster and more reliable fixed-pattern noise reduction, tracking the parameters drift, and presenting a good adaptability to scene changes and nonuniformity conditions.

Keywords and phrases

  • infrared detectors
  • focal-plane array
  • nonuniformity correction
  • fixed-pattern noise
  • neural networks
  • least mean square

Authors’ Affiliations

Department of Electrical Engineering, University of Concepcion, Casilla 160-C, Correo 3, Concepcion, Chile


© Vera and Torres 2005