基于自适应滤波的红外焦平面阵列非均匀性校正算法

 红外探测器响应漂移特性会降低红外焦平面阵列（IRFPA）非均匀性校正的精度。针对该问题提出了一种基于场景的IRFPA非均匀性校正算法。该算法利用所获得的序列成像场景信息，采用一种基于快速自适应滤波器的最优化递归估计方法来获得非均匀性校正参数，并利用当前的成像信息来更新校正参数，以此降低探测器响应漂移特性对非均匀性校正的影响。算法仿真实验显示，对非线性参数为26.12%的同一图像，使用该算法、两点校正算法和卡尔曼滤波校正算法校正1 h后，可分别将非线性参数降至1.856%,3.122%和1.893%，说明该算法可获得稳定而较好的非均匀性校正效果。

Nonuniformity correction algorithm for infrared focalplane arrays based on adaptive-filter

The performance of nonuniformity correction(NUC) would be deteriorated by time shift in the response of detectors in infrared focal plane arrays(IRFPAs). Therefore, a scene-based NUC algorithm is presented. In this algorithm, an adaptive filter bank is applied to estimate NUC parameters for every detector in IRFPAs. And the parameters are renewed by utilizing current imaging information to reduce the influence imposed by response drift on NUC. For an image with a nonuniformity of 26.12%, nonuniformities after 1 h correction are 3.122% for two-point NUC algorithm, 1.893% for Kalman-filter NUC algorithm and around 1.856% for the presented algorithm, which means the presented algorithm can achieve the best NUC effect steadily.