红外焦平面阵列非均匀性自适应校正方法

分析基于场景的红外焦平面阵列非均匀性校正方法中的景物退化和鬼影现象，提出了一种基于边缘约束高斯滤波的红外焦平面阵列非均匀性自适应校正方法。该方法设计了一个边缘约束高斯滤波器来获取理想的估计图像，利用最陡下降法得到计算增益校正因子和偏移量校正因子的迭代公式，并通过迭代步长的自适应控制来增快算法的收敛速度。通过仿真实验和真实红外图像处理对比实验表明:相较于目前已有的方法，该方法在有效抑制景物退化和鬼影现象的同时，较好地去除原始红外图像的固定图案噪声，保留了图像细节信息，提高了图像质量。

Adaptive nonuniformity correction method for infrared focal plane arrays

The scene degradation and ghosting in scene-based nonuniformity correction methods for infrared focal plane arrays were analyzed here, and a novel approach based on Gaussian filtering with edge constraint was proposed for nonuniformity correction of infrared focal plane arrays. A Gaussian filter with edge constraint was designed to obtain the desired estimation of the image. The gain and offset correction factors in the iterative formula were calculated using the steepest descent method. Meantime, the convergence speed was increased through adaptive control of the iterative step. Both simulation and experiments on real infrared images demonstrate that this approach can remove the fixed pattern noise more effectively compared with the existing methods. It can effectively suppress the scene degradation and ghosting, retain the detailed image information, and improve the image quality.