DOI: 10.3724/SP.J.1010.2013.00491

Journal of Infrared and Millimeter Waves (红外与毫米波学报) 2013/32:6 PP.491-497

A nonuniformity correction method based on Bayesian framework

In this study,we have created a bridge,which can connect the reference-based NUC and scene-based NUC.The right probability of the scene-based NUC parameters was calculated based on the Bayesian framework.The right probability composed of prior and observation probability was used to determine whether the calculated scene-based NUC parameters are suitable to correct the nonuniformity.The local same distribution constraint is defined in this paper,and the Infrared Focal Plane (IRFPA) gain space relativity has been discovered from the reference-based parameters by this paper firstly.The Bayesian prior probability is mainly determined by the local same distribution constraint,and the Bayesian observation probability is mainly determined by the IRFPA gain space relativity.This method can effectively balance the relationship between convergence speed and ghosting artifacts.Finally,the real and simulated infrared image sequences have been applied to demonstrate our algorithm’s positive effect.

Key words:scene-based nonuniformity correction,convergence,ghosting artifacts,Bayesian

ReleaseDate:2015-05-04 09:28:02

[1] Scribner D A, Sarkady K A, Caulfield J T.Adaptive retinalike preprocessing for imaging detector arrays[J].Proc.IEEE Int.Conf.Neural Networks, San Francisco, USA, 1993:1955-1960.

[2] Scribner D A, Sarkady K A, Caulfield J T.Nonuniformity correction for staring IR focal plane arrays using scenebased techniques[J].Proc.SPIE, 1990, 1308:224-233.

[3] Harris J G, Chiang Y M.Nonuniformity correction of infrared image sequences using the constant-statistics constraint [J].IEEE Transactions on Image Processing, 1999, 8(8):1148-1151.

[4] ZhangC, ZhaoW-Y.Scene-based nonuniformity correction using local constant statistics[J].J.Opt.Soc.Am.A, 2008, 25(6):1444-1453.

[5] Torres S N, Hayat M M.Kalman filtering for adaptive nonuniformity correction in infrared focal-plane arrays [J].Opt.Soc.Am.A, 2003, 20(3):470-480.

[6] Shehadeh M, Kuybeda O.Robust nonuniformity correction in infrared images[J].Proc.IEEE Int.Conf.Electrical and Electronics Engineers, Israel, 2008:275-279.

[7] Qian W X, Chen Q, Gu G-H.Space low-pass and temporal high-pass nonuniformity correction Algorithm[J].Optical Review, 2010, 17(11):24-29.

[8] Qian W X, Chen Q, Gu G-H, et al.Correction method for stripe nonuniformity[J].Applied Optics, 2010, 49(10):1764-1773.

[9] Parker D R, Gustafson S C, Oxley M E, et al.Development of a Bayesian framework for determining uncertainty in receiver operating characteristic curve estimates[J].IEEE Transactions on Knowledge and Data Engineering, 2010, 22(1):31-45.

[10] Celik T.Change detection in satellite images using a genetic algorithm approach[J].IEEE Geoscience and Remote Sensing Letters, 2010, 17(2):386-390.

[11] Hardie R C, Baxley F, Brys B, et al.Scene-based nonuniformity correction with reduced ghosting using a gated LMS algorithm[J].Optical Express, 2009, 17(17):14918-14933.

[12] Torres S N, Hayat M M.Kalman filtering for adaptive nonuniformity correction in infrared focal plane arrays[J].The Journal of the Optical Society of America A 2003, 20(3):470-480.

[13] Torres S N, Vera E M, Reeves R A, et al.Adaptive scene-based nonuniformity correction method for infrared focal plane arrays[J].SPIE Conference on Infrared Imaging Systems:Design Analysis, Modeling, and Testing XIV, Orlando, Florida, 2003, 5076:75-80.

[14] Vera E M, Torres S N.Fast adaptive nonuniformity correction for infrared focal-plane array detectors[J].Eurasip Journal on Applied Signal Processing 2005, 13:1994-2004.