提出了一种基于帧间预测的非均匀校正算法,它可以通过场景配准从当前已校正图像中估计出下一帧未校正图像的真值,然后将所得的场景估计与相应的噪音图像用于线性拟合,其拟合参量即可用来进行非均匀校正.该方法的主要优点在于抗噪音能力强,预测准确度高,且能够实时处理.详细阐述了算法的基本原理及其流程,并用真实红外数据对算法性能进行验证,取得了较好的效果.

An interframe-prediction based algorithm is developed for nonuniformity correction.The algorithm relies on the accuracy of registration.If the registration is accurate,it can estimate the true values of the next uncorrected frame through the current corrected one.With these scene estimates and the corresponding observed values by detectors,a line-fitting procedure is used to estimate the nonuniformity parameters,which can then be used for correction.The strength of the algorithm lies in its good noise immunity,high prediction precision and ability of real-time processing.The fundamental and the flow of the proposed technique are described and the performance is demonstrated with real infrared imagery.