On resolution and viewing of holographic image generated by 3D holographic display

In this article, we propose a reference light wave multiplexing scheme to increase the information capacity of computer-generated holograms. The holograms were generated by different reference light waves and superimposed together as a multiplexed hologram. A modified Gerchberg–Saxton algorithm was used to improve image quality, and different images could be reconstructed when the multiplexed hologram was illuminated by corresponding reference light waves. We performed both numerical simulations and optical experiments to demonstrate the feasibility of the proposed scheme. Numerical simulations showed that the proposed method could reconstruct multiple images successfully by a single multiplexed hologram and optical experiments are consistently good with numerical simulations. It is expected that the proposed method has great potential to be widely applied in holographic displays in the future.

Download Full-text

A real-space interactive holographic display based on a large-aperture HOE

10.1117/12.2021633 ◽

2013 ◽

Cited By ~ 6

Author(s):

Javid Khan ◽

Chi Can ◽

Alan Greenaway ◽

Ian Underwood

Keyword(s):

Real Space ◽

Holographic Display ◽

Large Aperture

Download Full-text

Holographic Display System to Suppress Speckle Noise Based on Beam Shaping

Photonics ◽

10.3390/photonics8060204 ◽

2021 ◽

Vol 8 (6) ◽

pp. 204

Author(s):

Di Wang ◽

Yi-Wei Zheng ◽

Nan-Nan Li ◽

Qiong-Hua Wang

Keyword(s):

Optical Element ◽

Speckle Noise ◽

Beam Shaping ◽

Diffractive Optical Element ◽

The Other ◽

Spatial Light Modulators ◽

Viewing Angle ◽

Display System ◽

Holographic Display ◽

Light Modulators

In this paper, a holographic system to suppress the speckle noise is proposed. Two spatial light modulators (SLMs) are used in the system, one of which is used for beam shaping, and the other is used for reproducing the image. By calculating the effective viewing angle of the reconstructed image, the effective hologram and the effective region of the SLM are calculated accordingly. Then, the size of the diffractive optical element (DOE) is calculated accordingly. The dynamic DOEs and effective hologram are loaded on the effective regions of the two SLMs, respectively, while the wasted areas of the two SLMs are performed with zero-padded operations. When the laser passes through the first SLM, the light can be modulated by the effective DOEs. When the modulated beam illuminates the second SLM which is loaded with the effective hologram, the image is reconstructed with better quality and lower speckle noise. Moreover, the calculation time of the hologram is reduced. Experiments indicate the validity of the proposed system.

Download Full-text

Computing 3D Phase-Type Holograms Based on Deep Learning Method

Photonics ◽

10.3390/photonics8070280 ◽

2021 ◽

Vol 8 (7) ◽

pp. 280

Author(s):

Huadong Zheng ◽

Jianbin Hu ◽

Chaojun Zhou ◽

Xiaoxi Wang

Keyword(s):

Deep Learning ◽

Signal To Noise Ratio ◽

Contrast Ratio ◽

Angular Spectrum ◽

Structural Similarity ◽

Computational Time ◽

Experimental Investigations ◽

Training Strategy ◽

Holographic Display ◽

Phase Type

Computer holography is a technology that use a mathematical model of optical holography to generate digital holograms. It has wide and promising applications in various areas, especially holographic display. However, traditional computational algorithms for generation of phase-type holograms based on iterative optimization have a built-in tradeoff between the calculating speed and accuracy, which severely limits the performance of computational holograms in advanced applications. Recently, several deep learning based computational methods for generating holograms have gained more and more attention. In this paper, a convolutional neural network for generation of multi-plane holograms and its training strategy is proposed using a multi-plane iterative angular spectrum algorithm (ASM). The well-trained network indicates an excellent ability to generate phase-only holograms for multi-plane input images and to reconstruct correct images in the corresponding depth plane. Numerical simulations and optical reconstructions show that the accuracy of this method is almost the same with traditional iterative methods but the computational time decreases dramatically. The result images show a high quality through analysis of the image performance indicators, e.g., peak signal-to-noise ratio (PSNR), structural similarity (SSIM) and contrast ratio. Finally, the effectiveness of the proposed method is verified through experimental investigations.

Download Full-text