Restoration method for 3D image of the wide-field microscope based on the network

The restoration for 3D (three dimensions) image of wide-field microscope needs to process very large data size, and it spend much time. In this paper, a new method is proposed for 3D image restoration of wide-field microscope based on the BP neural network. The initial step of the method is to transform a 3D image into a series of 2D images. Then, the mapping relationship between the 2D blurring image with defocusing message and 2D clear image is established by training the BP neural network, which has a high ability of learning. Following, every 2D section image of the stack is restored in succession. As a result, the restoration of 3D image of wide-field microscope is achieved. Extensive tests demonstrate that this method has a satisfying restoration effect both in visual impression and quantitative analysis. For adopting small dimensional neural network, the training time is little, and the operational amount is small. Thus, it is possible to realize the real time restoration.