Minimum variance gain nonuniformity estimation in infrared focal plane array sensors

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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. © 2009 Springer-Verlag Berlin Heidelberg.

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APA

San-Martin, C., & Hermosilla, G. (2009). Minimum variance gain nonuniformity estimation in infrared focal plane array sensors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5856 LNCS, pp. 1047–1053). https://doi.org/10.1007/978-3-642-10268-4_122

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