TY - GEN
T1 - Minimum variance gain nonuniformity estimation in infrared focal plane array sensors
AU - San-Martin, César
AU - Hermosilla, Gabriel
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
KW - Image sequence processing
KW - Infrared focal plane arrays
KW - Minimum variance estimator
KW - Signal processing
UR - http://www.scopus.com/inward/record.url?scp=78651257606&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-10268-4_122
DO - 10.1007/978-3-642-10268-4_122
M3 - Conference contribution
AN - SCOPUS:78651257606
SN - 3642102670
SN - 9783642102677
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1047
EP - 1053
BT - Progress in Pattern Recognition, Image Analysis, Computer Vision and Applications - 14th Iberoamerican Conference on Pattern Recognition, CIARP 2009, Proceedings
T2 - 14th Iberoamerican Conference on Pattern Recognition, CIARP 2009
Y2 - 15 November 2009 through 18 November 2009
ER -