Tomoyoshi Shimobaba

Real-time digital holographic microscopy using the graphic processing unit.

Digital holographic microscopy (DHM) is a well-known powerful method allowing both the amplitude and phase of a specimen to be simultaneously observed. In order to obtain a reconstructed image from a hologram, numerous calculations for the Fresnel diffraction are required. The Fresnel diffraction can be accelerated by the FFT (Fast Fourier Transform) algorithm. However, real-time reconstruction from a hologram is difficult even if we use a recent central processing unit (CPU) to calculate the Fresnel diffraction by the FFT algorithm. In this paper, we describe a real-time DHM system using a graphic processing unit (GPU) with many stream processors, which allows use as a highly parallel processor. The computational speed of the Fresnel diffraction using the GPU is faster than that of recent CPUs. The real-time DHM system can obtain reconstructed images from holograms whose size is 512 x 512 grids in 24 frames per second.

Band-Limited Angular Spectrum Method for Numerical Simulation of Free-Space Propagation in Far and Near Fields

A novel method is proposed for simulating free-space propagation. This method is an improvement of the angular spectrum method (AS). The AS does not include any approximation of the propagation distance, because the formula thereof is derived directly from the Rayleigh-Sommerfeld equation. However, the AS is not an all-round method, because it produces severe numerical errors due to a sampling problem of the transfer function even in Fresnel regions. The proposed method resolves this problem by limiting the bandwidth of the propagation field and also expands the region in which exact fields can be calculated by the AS. A discussion on the validity of limiting the bandwidth is also presented.

Fast calculation of computer-generated-hologram on AMD HD5000 series GPU and OpenCL

In this paper, we report fast calculation of a computer-generated-hologram using a new architecture of the HD5000 series GPU (RV870) made by AMD and its new software development environment, OpenCL. Using a RV870 GPU and OpenCL, we can calculate 1,920 x 1,024 resolution of a CGH from a 3D object consisting of 1,024 points in 30 milli-seconds. The calculation speed realizes a speed approximately two times faster than that of a GPU made by NVIDIA.

HORN-6 special-purpose clustered computing system for electroholography.

We developed the HORN-6 special-purpose computer for holography. We designed and constructed the HORN-6 board to handle an object image composed of one million points and constructed a cluster system composed of 16 HORN-6 boards. Using this HORN-6 cluster system, we succeeded in creating a computer-generated hologram of a three-dimensional image composed of 1,000,000 points at a rate of 1 frame per second, and a computer-generated hologram of an image composed of 100,000 points at a rate of 10 frames per second, which is near video rate, when the size of a computer-generated hologram is 1,920 x 1,080. The calculation speed is approximately 4,600 times faster than that of a personal computer with an Intel 3.4-GHz Pentium 4 CPU.

Simplified electroholographic color reconstruction system using graphics processing unit and liquid crystal display projector.

We have constructed a simple color electroholography system that has excellent cost performance. It uses a graphics processing unit (GPU) and a liquid crystal display (LCD) projector. The structure of the GPU is suitable for calculating computer-generated holograms (CGHs). The calculation speed of the GPU is approximately 1,500 times faster than that of a central processing unit. The LCD projector is an inexpensive, high-performance device for displaying CGHs. It has high-definition LCD panels for red, green and blue. Thus, it can be easily used for color electroholography. For a three-dimensional object consisting of 1,000 points, our system succeeded in real-time color holographic reconstruction at rate of 30 frames per second.

An electroholographic colour reconstruction by time division switching of reference lights

In this paper, we report an electroholographic reconstruction method for a colour three-dimensional (3D) object, using the time division switching of reference lights. We use a reflective liquid crystal display (LCD) panel with a high refresh rate as a spatial light modulator. A colour 3D object is divided into red, green and blue components, from which we compute three computer-generated holograms (CGHs). The LCD panel displays the CGHs in sequence at a refresh rate of about 100 Hz. The LCD panel also outputs synchronized signals, indicating that one of the CGHs is currently displayed on the LCD panel. Red, green and blue light emitting diodes (LEDs), as used for reference lights, are switched by the synchronized signals. As a result of the afterimage effect on human eyes, we can clearly observe a coloured 3D object.

Numerical calculation library for diffraction integrals using the graphic processing unit: the GPU-based wave optics library

In optics, several diffraction integrals, such as the angular spectrum method and the Fresnel diffraction, are used for calculating scalar light propagation. The calculation result provides us with the optical characteristics of an optical device, the numerical reconstruction image from a hologram, and so forth. The acceleration of the calculation commonly uses the fast Fourier transform; however, in order to analyze a three-dimensional characteristic of an optical device and compute real-time reconstruction from holograms, recent computers do not have sufficient computational power. In this paper, we develop a numerical calculation library for the diffraction integrals using the graphic processing unit (GPU), the GWO library, and report the performance of the GWO library. The GPU chip allows us to use a highly parallel processor. The maximum computational speed of the GWO library is about 20 times faster than a personal computer.

Electroholographic display unit for three-dimensional display by use of special-purpose computational chip for holography and reflective LCD panel

We developed an electroholography unit, which consists of a special-purpose computational chip for holography and a reflective liquid-crystal display (LCD) panel, for a three-dimensional (3D) display. The special-purpose chip can compute a computer-generated hologram of 800x600 grids in size from a 3D object consisting of approximately 400 points in approximately 0.15 seconds. The pixel pitch and resolution of the LCD panel are 12 mum and 800x600 grids, respectively. We implemented the special purpose chip and LCD panel on a printed circuit board of approximately 28cmx13cm in size. After the calculation, the computer-generated hologram produced by the special-purpose chip is displayed on the LCD panel. When we illuminate a reference light to the LCD panel, we can observe a 3D animation of approximately 3cmx3cmx3cm in size. In the present paper, we report the electroholographic display unit together with a simple 3D display system.

Interactive color electroholography using the FPGA technology and time division switching method

In this paper, we report an interactive color electroholography system using the field-programmable gate array (FPGA) technology and the time division switching method for color reconstruction. We implemented 30 dedicated-processors for a computer-generated hologram (CGH) into an FPGA chip, and the FPGA chip can generate full-parallax CGHs, on which we record color information for a color 3D object, faster than a personal computer. The time division switching method can reconstruct a color 3D object from the CGHs, to make use of the afterimage effect on human eyes. The system allows us to perform interactive operations for a reconstructed color 3D object using a keyboard, while viewing the reconstructed color 3D object.

High-speed FDTD simulation algorithm for GPU with compute unified device architecture

We proposed an FDTD algorithm for GPU with CUDA. Our GPU-FDTD algorithm performed high-speed FDTD simulation using GPU with CUDA, and maintained single-floating point accuracy. In the larger computational domain, the speedup factor becomes worse. The result suggests that the bottleneck of the FDTD simulation is memory bandwidth. Our GPU-FDTD algorithm can be applied to 3-D FDTD simulation. In future, we plan to implement our GPU-FDTD algorithm to the 3-D FDTD simulation.