Restoration method for COSM image based on RBF neural network
基于RBF神经网络的COSM图像复原算法

In the process of obtaining 3D images by Computational Optical Sectioning Microscopy method (COSM), every slice image is disturbed by other defocusing messages and the 3D images are blurred. In order to resolve this problem, a new restoration method based on the RBF neural network was proposed. The nonlinear mapping relationships between the 3D blurred images with defocusing messages and 3D clear images were established by training the Radial Basis Function (RBF) neural network that has the ability of learning and generalizing with a group of COSM images. Then 3D images that need restoring could be restored by the trained neural network. Experiment demonstrates that the speed of this method is high and this method has satisfying restoration performance in both visual impression and quantitative analysis.