Convolutional Neural Network for Phase-Only Hologram Optimization Based on the Point Source Method With the Holographic Viewing-Window

Abstract

An optimization algorithm for phase-only hologram (POH) based on the point source method (PSM) with the holographic viewing-window (HVW) by using a convolutional neural network (CNN) is proposed. The network training adopts an unsupervised strategy that maps the target image to optimized constant phases (OCPs) corresponding to the wavefront of each point source instead of random constant phases (RCPs), and then the optimized POH can be obtained by wavefront superposition. The simulation and experimental results show that the speckle noise of the reconstruction is significantly suppressed compared with the initial random phase method (RPM), which demonstrates the feasibility of the proposed method and shows a strong generalization ability of the trained CNN. The HVW of a holographic near-eye display (NED) has a continuous observation range of about 6 mm in the horizontal direction without using additional optical expansion elements, and a complete high-quality image can be observed within this range.

Optimization algorithm for amplitude-only hologram based on digital micromirror device

“…It is worth noting that there is a one-to-one correspondence between each phase value in the OCP matrix and each amplitude value in the input matrix. Each OCP needs to be added with the phase of the relevant wavefront, that is, the complex amplitude distribution on the hologram plane is 22 :…”

“…Second, if the viewpoint sampling interval is too small, it will cause image crosstalk and thus degrade the reconstruction quality. To solve these problems, this paper utilizes a method of observing the reconstructed image through HVW 22 , which uses the property of wavefront superposition of point sources to ensure that each point of the hologram contains the wavefront information of all point sources, and the common area of the wavefront superposition is HVW so that during the observation process, we can observe the complete reconstructed image naturally and continuously as if we were looking at the outside scene through a window.…”