International Symposium on Holography and Related Technologies 2015 (IWH2015)
Ginowan (Okinawa), Th2-3, (2015.12.3).

Comparison of computation time and image quality between CGHs
calculated by the point cloud and polygon-based method
Noriaki Nakatsuji1), Kyoji Matsushima1), Tomoyoshi Ito2) and Tomoyoshi Shimobaba2)
1)
Department of Electrical and Electronic Engineering, Kansai University,
3-3-35, Yamate-cho, Suita, Osaka 564-8680, Japan2)

Graduate School of Engineering, Chiba University,
1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan

1. Introduction
The point-based method or point cloud is commonly used for calculating object fields and fringes of computergenerated holograms (CGH). However, many high-definition CGHs such as the “The Venus” were created byusing the polygon-based method [1]. This was because the point cloud was generally too time-consuming tocalculate high-definition CGHs that are commonly composed of billions and sometimes ten billion pixels.
Computation by the polygon-based method is most likely faster than that by the point cloud. However, it is not
actually confirmed by comparison how fast the polygon-based method is. In addition, the reconstructedsurfaces look noisy in the polygon-based method because it uses random phase in order to diffuse light emitted
by a polygonal surface. Therefore, there is a great interest in a comparison of computation time and image
quality between the polygon-based method and point cloud.
These comparisons were difficult before because of slowness of point cloud. It was even impossible tocreate high-definition CGHs by point cloud. Recently, however, GPUs allow us to generate CGHs by point
cloud much faster [2]. In this paper, we measure computation time of object fields for quasi high-definition
CGHs with the same 3D scene by using the point cloud with GPU and the polygon-based method. Additionally,
we actually fabricate these CGHs and compare the optical reconstruction to verify the quality.
2. Methods for comparison
The 3D scenes used for the comparison are shownin Fig. 1. Here, binary images are mapped on themodels as the texture. An important issue of thecomparison is how to make it fair. Since two
methods are very different in the principle, they havemuch different parameters such as the number ofpoint sources and polygons. The number of point
sources especially affects the computation time andimage quality of CGHs by point cloud. Therefore,
we adopt the parameter based the human vision.
Angular resolution of human eyes is 1/60 degree inaverage persons. Thus, suppose that viewers see theCGH 250 mm apart from the CGH, we adopted thelinear density of point sources of 9.84 mm1.
Other parameters used for creating the CGHs
are summarized in Table 1. The parameters of PCsand software used for calculation are also shown inTable 2. Here, note that one of the newest GPU isused for calculation by point cloud, whereas anexisting PC and software are used for that in thepolygon-based method.

yHologram

25Flat modelx250z100(a) Flat model

25

Units: mm
yHologram

Polyhedron modelx250z100(b) Polyhedron modelFig.1 3D scenes of the test CGHs.

Units: mm

International Symposium on Holography and Related Technologies 2015 (IWH2015)
Ginowan (Okinawa), Th2-3, (2015.12.3).

Table 2 Parameters of PCs used for calculation.

Table 1 Parameters of the test CGHs.
Number of pixels

32,768 × 32,768

Pixel pitches

0.8 μm × 0.8 μm
632.8 nm

Design wavelength
Model
Number of point sources(Point cloud)Number of polygons(Polygon-based method)

FlatPolyhedron

60516

80962

20072

PC1 (polygon-based method)
CPUIntel Xeon E5-2690 v2 (3.00 GHz)
Main memory
512 GB
Number of real cores
20
Software*
MKL 11.2/WFL 3.3.2/PSL 1.5
PC2 (point cloud)
NVIDIA GeForce GTX
TITAN X (1.08 GHz)
12 GB
3072
CUDA 7.5
Intel Core i7-5930K (3.50 GHz)GPU
Global memory
Number of CUDA cores
SoftwareHost CPUs]

3. Results of comparison
The computation time and pictures of opticalreconstruction by coherent light are shown inFig.2 and Fig.3, respectively. These show * WFL/PSL are software library distributed in our site.
calculation by combination of point cloud and GPU is faster than thatby CPU and the polygon-based method in the 3D model, but the flatmodel gives an opposite result; the polygon-based method with CPU
2is still faster than point cloud. As for image quality, we cannot findconsiderable differences between these CGHs at a glance.

1453s

References1) K. Matsushima and S. Nakahara: “Extremely high-definition fullparallax computer-generated hologram created by the polygon-based
method”, Appl. Opt. 48, H54-H63 (2009).
2) N. Masuda, T. Ito, T. Tanaka, A. Shiraki, and T. Sugie: “Computergenerated holography using a graphics processing unit”, Opt.
Express 14, 603-608 (2006).

(a) Point cloud

Polygon

Point

752s

Polygon11199sPoint

The computation time and image quality of CGHs calculated by using
point cloud with GPU were compared with that by the polygon-based
method with CPU.
This work was supported by the JSPS KAKENHI (15K00512) andthe MEXT strategic research foundation at private universities (20132017).

Computation time [4. Conclusion

228s0
Flat model PolyhedronmodelFig. 3 Measured computation time.

(b) Polygon-based method

Fig. 2 Pictures of optical reconstruction of CGHs calculated by using (a) point cloud and (b) the polygon based method.