The Research Of The Deconvolution Algorithm Based On 3D Gauss PSF In COSM

In the 3D microscopical imaging, 2D serial images could be recorded when the microscope is focused on different planes of the biological specimen. So the 3D information of the specimen could be recorded through these serial images. But each in-focus plane does not only have information from its own plane, but also from out-of-focus planes, which leads to the image degrading. Usually, there are two ways to restore the image. One is the Laser Scanning Confocal Microscopy (LSCM). It can get the 3D image of the object through the light route by debluring. The other one is the Computational Optical Sectioning Microscopy (COSM). It can get the correct 3D configuration of the object by separating the light information of the in-focus plane from the out-of-focus planes. Compared with the LSCM, the COSM has the advantages of high SNR, no bleaching and low price. But because of a large amount of data, it also has the disadvantage of low computation rate.In this paper, we present a Parametric Blind Deconvolution algorithm (PBD) based on 3D Gauss Point Spread Function (PSF). The PBD algorithm needs to estimate the specimen function and the parameters of the PSF simultaneously. The practical medel of the PSF is so complex that it requires a large computation and it converges slowly. But based on the simplified 3D Gauss model, the PBD algorithm only needs to estimate two parameters. While retaining the restoring effect, the...