Combined nonuniformity correction algorithm of infrared focal plane arrays based on substrate temperature

The advantages and disadvantages in nonuniformity correction(NUC) algorithms based on calibration and scene of infrared focal plane arrays(IRFPA) were analysed separately. The combined NUC algorithm was presented. The thermal imaging system extracted the gain and offset factor from the FLASH which storged beforehand according to the substrate temperature of the IRFPA at the moment of power on. These factor was adopted to remove the nonuniformity of the detector simply. Based on the analysis of the characteristic of residual noise after initial correction, the P-M filter was used to replace the linear spatial average filter in the Neural Network nonuniformity correction algorithm(NN-NUC),which could preserve the image edge. Experimental results show that the proposed algorithm can accelerate the rate of convergence, reduces the correction error largely, and avoids the image degradation caused by the response drift of IRFPA.