基于三维高斯模型的参数盲解卷积算法

提出了一种新的基于三维高斯点扩展函数（PSF）模型的参数盲解卷积（PBD）算法，并将此算法用于显微光学切片的图像复原。由于PBD算法需要在估计样本函数的同时估计PSF的参数，一般采用的PSF的模型较为复杂，计算量大，收敛慢；而基于三维高斯PSF模型的算法只需要估计2个参数，因此计算量大大降低了。经过实验验证，该算法能够较好地复原光学切片的图像，并且估计出PSF的参数。

Parametric Blind Deconvolution Based on 3-D Gaussian Model

A parametric blind deconvolution(PBD) algorithm was presented based on a new model of the 3-D Gaussian point spread function(PSF) to restore the microscopic optical slices.The PBD algorithm needed to simultaneously estimate the specimen function and the parameters of the PSF,while the PSF model was complicated,needed a large number of computation and converged slowly.Based on the Gaussian PSF model presented,this algorithm only needed to estimate two parameters,so the amount of the computation was greatly reduced.The experiments proved that this algorithm can preferably restore the optical slices and estimate the parameters of the PSF.