提出了一种场景自适应的非均匀性校正固定图案噪声去除方法.基于多帧配准和相邻帧之间的全局位移估计，利用最小均方算法迭代计算均方误差函数，同时结合误差函数均方差以及互相关峰值，从而能够自适应场景变化.所提出的算法充分利用相邻多帧之间的相关性，对模拟和实际红外图像序列非均匀性的校正效果突出.实验结果表明本方法能够精确估计非均匀性参数，收敛速度较快，几乎不残留鬼影.

A novel adaptive scene-based nonuniformity correction method for fixed-pattern noise removal was put forward. It is based on the multiframe registration and estimation of global translation between several adjacent frames. The resulting mean square error function was optimized making use of the least mean square algorithm. Combining the local variance of an error function with the correlation peak value, the convergence speed can be controlled adaptively. The proposed method takes advantage of the correlation of adjacent frames sufficiently, thus it can provide enhanced results for diverse simulated and real infrared image sequences with nonuniformity. The experimental results show that the accurate estimations of the nonuniformity parameters of each detector in a focal plane array speed up the convergence, meanwhile, retain few ghosting artifacts.