Optical EngineeringEdge-directed adaptive nonuniformity correction for staring infrared focal plane arrays
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An in-depth analysis is made in the case of object degeneration and ghosting artifacts in a neural-network-based nonuniformity correction algorithm (NN-NUC) for infrared focal plane arrays (IRFPAs). It is found that updating the correction coefficients blindly in the NN-NUC scheme without taking the object edge into account is the root of the problem. Based on this conclusion, an edge-directed NN-NUC scheme (ED-NN-NUC) is proposed to eliminate ghosting artifacts and object degeneration. Comparison experiments with simulated data and real IRFPA infrared data show that the root of the problem pointed out is correct and the proposed scheme is rational and effective.