Chen Zhaoxue, Chen Hao
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2014 Feb;31(1):53-7.
As the most popular simplified model of the optical imaging system, the acquisition of the Gaussian point spread function (PSF) parameter is one of the hotspots and key points on which people do research in the field of image restoration. Based on the idea by which there exists deterministic mathematical relationship between Gaussian OTF feature points as well as its parameter and the frequency representation of the image in an existed literature, we proposed an automatic, accurate, stable, and improved approach. This method is able to give prominence to the related calculation feature by a Gaussian convolution and degeneration operation and finally realize the automatic esti mation of PSF parameter of a microscopic image. Experiments have proved that a good restoration result can be achieved utilizing the estimated PSF by the present method, which is of considerable application and reference value in restoration of other sorts with Gaussian approximate PSF model or 3D microscopic image restoration.
作为光学成像系统最流行的简化模型，高斯点扩散函数（PSF）参数的获取是图像恢复领域人们研究的热点和重点之一。基于现有文献中高斯光学传递函数（OTF）特征点及其参数与图像频率表示之间存在确定性数学关系的思想，我们提出了一种自动、准确、稳定且改进的方法。该方法能够通过高斯卷积和退化运算突出相关计算特征，最终实现微观图像PSF参数的自动估计。实验证明，利用本方法估计的PSF能够取得良好的恢复效果，在具有高斯近似PSF模型的其他类型图像恢复或三维微观图像恢复中具有相当大的应用和参考价值。
