Fourier, Fresnel, and Image CGHs of three-dimensional objects observed from many different projections

Abstract

We describe new techniques of synthesizing three types of computer-generated hologram (CGH); Fourier, Fresnel and image CGHs. These holograms, aimed to reconstruct three-dimensional (3-D) objects, are synthesized by means of a unique algorithm of fusing multiple perspective views of the observed scene. The hologram is initially generated in the computer as a Fourier hologram. Then, it can be converted to either Fresnel or image holograms by computing the desired wave propagation and the interference process. By illuminating the ready-to-use CGHs with a collimated plane wave, a 3-D image of the objects is reconstructed. Diffraction efficiency enhancement of the above algorithm by superimposing a random phase on the object during the CGH formation is also presented. Computer simulation and experimental results of the constructed 3-D objects demonstrate the suggested technique.

GAN-Holo: Generative Adversarial Networks-Based Generated Holography Using Deep Learning

“…Computer-generated holography (CGH) is a methodology for calculating the holographic interference pattern that produces a random optical field by using digital computers. ere are various iterative methods that have been used for generating CGH, including the Fresnel method [1] and the Gerchberg-Saxton (GS) method [2], the optimal-rotation-angle method [3], iterative finite-element mesh adaption [4], quantized kinogram by genetic algorithm [5], and vectorial beam shaping [6].…”

Vector lifting scheme for phase-shifting holographic data compression

“…Under such assumptions, some mathematical models have been developed, of which two important and commonly used ones are Fresnel holograms and Fourier holograms. 9 Both of them are based on Discrete Fourier transforms.…”