Volume 47 Issue 6
Jul.  2018
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Gu Huarong. Data compression coding technologies for computer-generated holographic three-dimensional display[J]. Infrared and Laser Engineering, 2018, 47(6): 603006-0603006(6). doi: 10.3788/IRLA201847.0603006
Citation: Gu Huarong. Data compression coding technologies for computer-generated holographic three-dimensional display[J]. Infrared and Laser Engineering, 2018, 47(6): 603006-0603006(6). doi: 10.3788/IRLA201847.0603006

Data compression coding technologies for computer-generated holographic three-dimensional display

doi: 10.3788/IRLA201847.0603006
  • Received Date: 2018-05-15
  • Rev Recd Date: 2018-06-05
  • Publish Date: 2018-06-25
  • Holographic three-dimensional(3D) display can reconstruct the light field of a real scene, providing all depth cues and becoming one of the best solutions for true 3D display. Computer-generated holographic 3D display only needs to know the mathematical description of the object light wave, can flexibly control the wavefront, and display a virtual 3D object. However, the huge amount of data and the amount of calculations hinder the practical application of computer-generated holographic 3D display. This paper presented data compression coding techniques for multiple stages in computer-generated holographic 3D display, including sparse sampling of 3D objects, optimization and parameter optimization of holographic 3D video compression coding, holographic fractal compression algorithm, effectively reducing the amount of data. And the parallel computing capabilities of GPUs were utilized to enable fast calculation of holograms.
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    [3] Zhou Hao, Gu Jihua, Chen Daqing. Multi-plane imaging in digital holography[J]. Infrared and Laser Engineering, 2015, 44(2):513-518. (in Chinese)
    [4] Xu X W, Solanki S, Liang X N, et al. Full high-definition digital 3D holographic display and its enabling technologies[C]//SPIE, 2010, 7730:77301C.
    [5] Kwon M W, Kim S C, Yoon S E, et al. Object tracking mask-based NLUT on GPUs for real-time generation of holographic videos of three-dimensional scenes[J]. Opt Express, 2015, 23(3):2101-2120.
    [6] Cai X O, Wang H. On holographic information content and its compression[J]. Optik, 2006, 117(3):131-137.
    [7] Lucente M. Interactive computation of holograms using a look-up table[J]. Journal of Electronic Imaging, 1993, 2(1):28-34.
    [8] Kim S C, Kim E S. Effective generation of digital holograms of three-dimensional objects using a novel look-up table method[J]. Appl Opt, 2008, 47(19):D55-D62.
    [9] Wikipedia. H.264/MPEG-4 AVC[EB/OL].[2018-01-05]. https://en.wikipedia.org/wiki/H.264/MPEG-4_AVC, 2018.
    [10] Wikipedia. High Efficiency Video Coding[EB/OL].[2018-03-28]. https://en.wikipedia.org/wiki/High_Efficiency_Video_Coding, 2018.
    [11] Wikipedia. VP9[EB/OL].[2018-01-01]. https://en.wikipedia.org/wiki/VP9, 2018.
    [12] Wang Z, Bovik A C, Sheikh H R, et al. Image quality assessment:from error visibility to structural similarity[J]. IEEE Transactions on Image Processing, 2004, 13(4):600-612.
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Data compression coding technologies for computer-generated holographic three-dimensional display

doi: 10.3788/IRLA201847.0603006
  • 1. State Key Laboratory of Precision Measurement Technology and Instruments,Department of Precision Instrument,Tsinghua University,Beijing 100084,China

Abstract: Holographic three-dimensional(3D) display can reconstruct the light field of a real scene, providing all depth cues and becoming one of the best solutions for true 3D display. Computer-generated holographic 3D display only needs to know the mathematical description of the object light wave, can flexibly control the wavefront, and display a virtual 3D object. However, the huge amount of data and the amount of calculations hinder the practical application of computer-generated holographic 3D display. This paper presented data compression coding techniques for multiple stages in computer-generated holographic 3D display, including sparse sampling of 3D objects, optimization and parameter optimization of holographic 3D video compression coding, holographic fractal compression algorithm, effectively reducing the amount of data. And the parallel computing capabilities of GPUs were utilized to enable fast calculation of holograms.

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