泊松二项式分布在 TEM 图像分析中的作用。
The role of Poisson's binomial distribution in the analysis of TEM images.
机构信息
Delft Center for Systems and Control, Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands.
出版信息
Ultramicroscopy. 2011 Nov;111(11):1553-6. doi: 10.1016/j.ultramic.2011.08.010. Epub 2011 Sep 8.
Frank's observation that a TEM bright-field image acquired under non-stationary conditions can be modeled by the time integral of the standard TEM image model [J. Frank, Nachweis von objektbewegungen im lichtoptis- chen diffraktogramm von elektronenmikroskopischen auf- nahmen, Optik 30 (2) (1969) 171-180.] is re-derived here using counting statistics based on Poisson's binomial distribution. The approach yields a statistical image model that is suitable for image analysis and simulation.
弗兰克指出，在非稳定条件下获取的 TEM 明场图像可以通过标准 TEM 图像模型的时间积分来建模[J. Frank，Nachweis von objektbewegungen im lichtoptischen diffraktogramm von elektronenmikroskopischen aufnahmen，Optik 30（2）（1969）171-180]。本文使用基于泊松二项分布的计数统计重新推导了这种方法，得到了一个适合图像分析和模拟的统计图像模型。
Zotero 插件