场景统计类红外图像非均匀性校正算法研究

场景统计类非均匀性校正算法对场景分布进行假定，获得探测单元接收红外能量的一、二阶矩，进而估计探测单元的响应参数，校正非均匀性。分析比较了现有的场景统计类非均匀性校正算法，并应用交互多模(IMM)算法校正非均匀性，实验结果表明以连续图像序列作为观测数据时，能够有效地校正非均匀性，扩展了卡尔曼滤波法的适用范围。对各种方法进行仿真，表明删算法具有较好的收敛特性。

Scene-based statistical algorithms for nonuniformity correction of infrared images

Scene-based statistical algorithms for nonuniformity correction assume the distribution of scene value to estimate the mean and variance of infrared energy received by each detector, then estimate the response parameters of each detector. In this way nonuniformity can be corrected. Current scene statistical algorithms for nonuniformity correction are analyzed. Interacting multiple model (IMM) is applied to correct nonuniformity. The experimental result shows that even taking consecutive frames as observing data, the nonuniformity can be corrected satisfactorily using IMM algorithm. It extends the applicability of Kalman filtering. More simulations for other algorithms have been done,and results indicate that the IMM algorithm has a better convergent performance.