In the process of obtaining3D images by Computational Optical Sectioning Microscopy method ( COSM), every slice image is disturbed by other defocusing messages and the3D images are blurred. 在计算光学切片显微技术成像中,每幅切片图像都要受到其他离焦层信息的干扰,引起图像模糊。
In the paper an algorithm for maximum-likelihood image restoration based on the expectation maximization ( EM) algorithm using the depth-variant imaging model in three-dimensional optical sectioning microscopy is proposed. 该文提出了一种基于EM算法的最大似然图像复原算法,此算法是基于三维显微光学切片中成像随深度变化的模型实现的。
Image restoration algorithms based on singular value decomposition of 3-D optical sectioning microscopy 基于奇值分解的三维光学切片显微图像恢复算法研究
So a regularized EM algorithm is used to avoid such disadvantages and to recover the detail of image in the depth-variant imaging model in three-dimensional optical sectioning microscopy. 所以又提出基于深度变化成像模型的调整EM算法,可以避免上述缺点,较好地恢复图像微弱细节。
Optical Sectioning Though the Combination of Structured Light and Microscopy 结构光和显微术相结合实现光学层析