A Recursive Least Square Adaptive Filter for Nonuniformity Correction of Infrared Image Sequences

  • Flavio Torres
  • Sergio N. Torres
  • César San Martín
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3773)


In this paper, an adaptive scene-based nonuniformity correction methodology for infrared image sequences is developed. The method estimates detector parameters and carry out the non-uniformity correction based on the recursive least square filter approach, with adaptive supervision. The key advantage of the method is based in its capacity for estimate detectors parameters, and then compensate for fixed-pattern noise in a frame by frame basics. The ability of the method to compensate for nonuniformity is demonstrated by employing several infrared video sequences obtained using two infrared cameras.


Image Sequence Processing Infrared Imaging RLS 


Infrared Image and Video Processing Infrared Sensor-Imaging 


  1. 1.
    Torres, S., Hayat, M.: Kalman Filtering for Adaptive Nonuniformity Correction in Infrared Focal Plane Arrays. The JOSA-A Opt. Soc. of America. 20, 470–480 (2003)CrossRefGoogle Scholar
  2. 2.
    Torres, S., Pezoa, J., Hayat, M.: Scene-based Nonuniformity Correction for Focal Plane Arrays Using the Method of the Inverse Covariance Form. OSA App. Opt. Inf. Proc. 42, 5872–5881 (2003)Google Scholar
  3. 3.
    Scribner, D., Sarkady, K., Kruer, M.: Adaptive Nonuniformity Correction for Infrared Focal Plane Arrays using Neural Networks. In: Proceeding of SPIE, vol. 1541, pp. 100–109 (1991)Google Scholar
  4. 4.
    Scribner, D., Sarkady, K., Kruer, M.: Adaptive Retina-like Preprocessing for Imaging Detector Arrays. In: Proceeding of the IEEE International Conference on Neural Networks, vol. 3, pp. 1955–1960 (1993)Google Scholar
  5. 5.
    Torres, S., Vera, E., Reeves, R., Sobarzo, S.: Adaptive Scene-Based Nonuniformity Correction Method for Infrared Focal Plane Arrays. In: Proceeding of SPIE, vol. 5076, pp. 130–139 (2003)Google Scholar
  6. 6.
    Vera, E., Torres, S.: Fast Adaptive Nonuniformity Correction for Infrared Focal Plane Arrays. To be published in EURASIP Journal on Applied Signal Processing (2005)Google Scholar
  7. 7.
    Ljung, L., Söderström, T.: Theory and practice of recursive identification. MIT Press, Cambridge (1983)zbMATHGoogle Scholar
  8. 8.
    Eleftheriou, E., Falconer, D.D.: Tracking properties and steady-state performance of RLS adaptive filter algorithms. IEEE Trans. Acoust. Speech Signal Process (ASSP) 34, 1097–1110 (1986)CrossRefGoogle Scholar
  9. 9.
    Ewada, E.: Comparasion of RLS, LMS and sign algorithms for tracking randomly time-varying channels. IEEE Trans. Signal Process 42, 2937–2944 (1994)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Flavio Torres
    • 1
  • Sergio N. Torres
    • 2
  • César San Martín
    • 1
    • 2
  1. 1.Department of Electrical EngineeringUniversity of La FronteraTemucoChile
  2. 2.Department of Electrical EngineeringUniversity of ConcepciónConcepciónChile

Personalised recommendations