Minimization of fixed pattern noise in photon event counting imaging
Minimization of fixed pattern noise in photon event counting imaging
复制标题
光子事件计数成像中固定模式噪声的最小化
DOI：
--
复制
发表时间：
2002
期刊：
影响因子：
--
通讯作者：
B. L. Morgan
中科院分区：
文献类型：
--
作者：
K. Suhling;W. AireyRobert;B. L. Morgan
利用耦合到电荷耦合器件相机的光子计数像增强器进行的微光紫外和光学成像通常会在图像中产生不同级别的固定图案噪声。在这里，我们证明可以通过适当选择光子事件质心算法来最小化这一点。我们比较了重心质心算法、高斯质心算法和混合质心算法产生的固定图案噪声，其中当一个机翼为零时使用重心，否则使用高斯质心。这种方法产生的图像质量最好，固定图案噪声参数(9.99%)比单独使用高斯质心(16.4%)低，并且不需要查找表校正。此外，混合算法还通过克服与高斯质心相关的小脉冲质心失败来产生最大的检测量子效率。用蒙特卡尔模型模拟了记录事件时的数字化误差。
Low light-level ultraviolet and optical imaging with a photon counting image intensifier coupled to a charge coupled device camera generally results in varying levels of fixed pattern noise in the image. Here, we demonstrate that this can be minimized by the appropriate choice of photon event centroiding algorithm. We compare the fixed pattern noise generated by a center of gravity centroiding algorithm, a Gaussian centroiding algorithm, and a hybrid centroiding algorithm which uses center of gravity centroiding when one wing is zero, and Gaussian centroiding otherwise. This approach yields the best image quality with a lower fixed pattern noise parameter (9.99%) than the sole use of Gaussian centroiding (16.4%), and there is no need for a look-up table correction. In addition, the hybrid algorithm also yields maximum detective quantum efficiency by overcoming small pulse centroiding failure associated with Gaussian centroiding. The digitization error when recording the events is modeled with a Monte Carl...