Efficient generation of holographic movies with frame interpolation using a coherent neural network

• Hirose Akira

  Department of Electronic Engineering, The University of Tokyo

• Higo Tomoaki

  Department of Electronic Engineering, The University of Tokyo

• Tanizawa Ken

  Department of Electronic Engineering, The University of Tokyo

Abstract

Computer-generated hologram (CGH) is recently expanding its application fields. However, the calculation cost is very high, in particular, in the generation of CGH streams for three-dimensional movies. This paper proposes a small-calculation-cost method to generate CGH streams based on a coherent neural network (CNN) that deals with complex-amplitude information with generalization ability in the carrier-frequency domain. After carrier-frequency-dependent learning, we can generate a CGH stream, by sweeping a virtual carrier frequency in the CNN, with neural interpolation thanks to the frequency-domain generalization. Experiments demonstrate a successful stream generation with 1/6 the conventional calculation time.

Journal

• IEICE Electronics Express

  IEICE Electronics Express 3 (19), 417-423, 2006

  The Institute of Electronics, Information and Communication Engineers

Keywords

• coherent neural network (CNN)
• computer generated hologram (CGH)
• optical tweezers
• generalization
• spatial light modulator (SLM)

Details

• CRID: 1390001205213808640
• NII Article ID: 130000088338
• DOI: 10.1587/elex.3.417
• ISSN: 13492543
• Web Site: http://www.jstage.jst.go.jp/article/elex/3/19/3_19_417/_pdf
• Text Lang: en
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed