Method Study On Nonuniformity Correction Of Infrared Focal Plane Array

Infrared focal plane array (IRFPA) can be superior for infrared imaging systems not only because of its simplicity and compactness in structure, but also because of its high sensitivity and low power depletion. And infrared focal plane array is applied to imaging system widely and attracted lots of attention. The classical character of IRFPA image signal is that different image cells correspondent different detector elements, so even the radiant emittances are the same, there will still be different outputs because of incompatible infrared responsivity, temperature change, optic system, nosies, et al, this will influence the capability of infrared system serious, hence, nonuniformity correction (NUC) becomes necessary. IRFPA nonuniformity correction is the key technique of infrared imaging.A combined nonuniformity correction algorithm is advanced in this paper, to realize nonuniformity correction, blind-pisel detection and image intensification of infrared imagery, which enhance the nonuniformity correction precision, to arrive application requirement.The paper firstly describes the reasons of the nonuniformity in the IRFPA. Then several methods of nonuniformity correction (NUC) for IRFPA are analyzed and compared, which leads to that the adaptive correction scheme is the best for the IR imaging system.Following that, the combined correction algorithm is introduced, which has the advantage of the two-point NUC and ANN, the combined algorithm adjusts gain and offset correction coefficient automatically through neural network, so it can avoid the shift of two-point NUC, and adopt two-point calibrater correction coefficient as neural network iterative initial value, so it converges to the target value faster than conventional ANN correction algorithm.In this paper, we also consider the phenomenon that "ghosting" artifact and target fade-out which exists in adaptive nonuniformity correction algorithm. About Blind-pisel detection and image intensification, we adopt median filter and do some improvement with filter window to abbreviate time.Experiments were performed between nonuniformity correction algorithms which have existed and the new algorithm which has been advanced in this paper. The simulation results suggest that the combined NUC algorithm's effectiveness and superiority. At the end of this paper, the key parameters' selection are been discussed.