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分析了红外焦平面阵列(IRFPA)基于定标的非均匀性校正法(NUC)和基于场景的NUC算法各自的优势和问题,在此基础上提出了联合非均匀性校正方法。根据上电时刻焦平面衬底的温度值,从FLASH中提取事先存储的对应温度区间的增益和偏置校正参数,初步消除探测器的非均匀性。通过分析初步校正后图像残余非均匀性噪声的特性,提出了一种自适应非均匀性校正算法NSCT,对经过NSCT分解后的子带图像,利用贝叶斯阈值逐点进行信号方差和噪声方差估计,计算出残余非均匀性噪声后并加以去除。实验结果表明,该算法能有效提高校正精度,并具有更强的环境适应性。
The advantages and problems of IRFPA calibration based non-uniformity correction (NUC) and scene-based NUC are analyzed. Based on this, the joint nonuniformity correction method is proposed. According to the temperature of the focal plane substrate at the power-on, the pre-stored corresponding temperature range gain and offset correction parameters are extracted from the FLASH to initially eliminate the detector non-uniformity. By analyzing the characteristics of the initial corrected residual nonuniformity noise, an adaptive nonuniformity correction algorithm (NSCT) is proposed. After NSCT decomposition, the signal variance and noise variance are calculated point by point using the Bayesian threshold It is estimated that the residual non-uniform noise is calculated and removed. Experimental results show that the proposed algorithm can effectively improve the accuracy of correction and has a better adaptability to the environment.