Abstract
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.
This work was partially supported by Proyecto DIUFRO EP No 120323 and Grant Milenio ICM P02-049. The authors wish to thank Ernest E. Armstrong (OptiMetrics Inc., USA) and Pierre Potet (CEDIP Infrared Systems, France) for collecting the data.
Chapter PDF
Similar content being viewed by others
Keywords
Topic
References
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)
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)
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)
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)
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)
Vera, E., Torres, S.: Fast Adaptive Nonuniformity Correction for Infrared Focal Plane Arrays. To be published in EURASIP Journal on Applied Signal Processing (2005)
Ljung, L., Söderström, T.: Theory and practice of recursive identification. MIT Press, Cambridge (1983)
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)
Ewada, E.: Comparasion of RLS, LMS and sign algorithms for tracking randomly time-varying channels. IEEE Trans. Signal Process 42, 2937–2944 (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Torres, F., Torres, S.N., Martín, C.S. (2005). A Recursive Least Square Adaptive Filter for Nonuniformity Correction of Infrared Image Sequences. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_56
Download citation
DOI: https://doi.org/10.1007/11578079_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
eBook Packages: Computer ScienceComputer Science (R0)