自适应卡尔曼滤波器在红外非均匀性校正中的应用

Application of Adaptive Kalman Filter for Infrared Non-uniformity Correction

针对红外非均匀性校正中基于定标的非均匀性校正算法和基于场景的非均匀性校正算法的优势和不足,提出了卡尔曼滤波算法应用于红外非均匀性校正。建立了探测元的响应模型,描述了卡尔曼滤波器的处理流程。卡尔曼滤波算法可以根据实际场景自适应地跟踪校正系数的漂移,使得校正系数更符合实际场景,有效地校正红外非均匀性,提高红外图像的质量。实验表明,经过卡尔曼滤波处理,减弱了红外图像的噪声,所用算法及实现方法可以满足实际需求。

According to the advantages and disadvantages in correction algorithms based on calibration and scene of in- frared non-uniformity correction, an algorithm based on Kalman filtering was proposed and implemented. Kalman filtering algorithm can modify the drift in the correction according to the actual scenes, and the resulting correction coefficients are more in agreement with the actual scenes and the infrared non-uniformity correction accuracy is effectively improved. The laboratory data shows that the algorithm and its implementation method can reduce the noise of infrared pictures and meets the actual demands.