Abstract
In this paper, a minimum variance estimator for the gain nonuniformity (NU) in infrared (IR) focal plane array (FPA) imaging system is presented. Recently, we have developed a recursive filter estimator for the offset NU using only the collected scene data, assuming that the offset is a constant in a block of frames where it is estimated. The principal assumption of this scene-based NU correction (NUC) method is that the gain NU is a known constant and does not vary in time. However, in several FPA real systems the gain NU drift is significant. For this reason, in this work we present a gain NU drift estimation based on the offset NU recursive estimation assuming that gain and offset are jointly distributed. The efficacy of this NUC technique is demonstrated by employing several real infrared video se quences.
Keywords
Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Milton, A., Barone, F., Kruer, M.: Influence of nonuniformity on infrared focal plane array performance. Optical Engineering 24, 855–862 (1985)
Mooney, J., Shepherd, F., Ewing, W., Murguia, J., Silverman, J.: Responsivity nonuniformity limited performance of infrared staring cameras. Optical Engineering 28, 1151–1161 (1989)
Harris, J., Chiang, Y.: Nonuniformity correction of infrared image sequences using constant statistics constraint. IEEE Trans. on Image Processing 8, 1148–1151 (1999)
Hayat, M., Torres, S., Amstrong, E., Cain, S., Yasuda, B.: Statistical algorithm fo nonuniformity correction in focal plane arrays. Applied Optics 38, 773–780 (1999)
Averbuch, A., Liron, G., Bobrovsky, B.: Scene based non-uniformity correction in thermal images using Kalman filter. Image and Vision Computing 25, 833–851 (2007)
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)
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)
Martin, C.S., Torres, S., Pezoa, J.E.: Statistical recursive filtering for offset nonuniformity estimation in infrared focal-plane-array sensors, in press Infrared Physics & Technology (2008)
Poor, H.V.: An introduction to signal detection and estimation, 2nd edn. Springer, New York (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
San-Martin, C., Hermosilla, G. (2009). Minimum Variance Gain Nonuniformity Estimation in Infrared Focal Plane Array Sensors. In: Bayro-Corrochano, E., Eklundh, JO. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2009. Lecture Notes in Computer Science, vol 5856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10268-4_122
Download citation
DOI: https://doi.org/10.1007/978-3-642-10268-4_122
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10267-7
Online ISBN: 978-3-642-10268-4
eBook Packages: Computer ScienceComputer Science (R0)