强激光与粒子束, 2016, 28 (12): 121001, 网络出版: 2016-12-26  

基于衬底温度和贝叶斯估计的红外非均匀性校正

Infrared non-uniformity correction based on substrate temperature and Bayesian estimation
作者单位
1 中国科学院 长春光学精密机械与物理研究所, 长春 130033
2 中国科学院大学, 北京 100049
摘要
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。
Abstract
The advantages and disadvantages in nonuniformity correction method (NUC) based on calibration and scene of infrared focal plane array (IRFPA) were analyzed respectively. On this basis, a combined non-uniformity correction method was presented. According to the temperature of focal plane substrate at the moment of power on, previously stored gain and bias correction parameters were extracted from the FLASH for the corresponding temperature interval to eliminate the non-uniformity of detector preliminarily. After preliminary correction, a self-adaptive non-uniformity correction algorithm was presented in order to eliminate residual noises. The images after preliminary correction were decomposed by non-subsampled contourlet transform(NSCT), and the Bayesian threshold was used to estimate the signal and noise variance point by point. As a result, the residual non-uniformity noise was figured out and then got rid of. Experimental results show that such an algorithm could improve both the correction accuracy and the environmental adaptability effectively.

唐艳秋, 孙强, 赵建, 姚凯男. 基于衬底温度和贝叶斯估计的红外非均匀性校正[J]. 强激光与粒子束, 2016, 28(12): 121001. Tang Yanqiu, Sun Qiang, Zhao Jian, Yao Kainan. Infrared non-uniformity correction based on substrate temperature and Bayesian estimation[J]. High Power Laser and Particle Beams, 2016, 28(12): 121001.

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