Efficient digital holographic 3d human image reconstruction and improvement on mobile devices


Advanced digital holography attracts a lot of attentions for 3D visualization nowadays. The representation of high-resolution digital holographic 3D human images suffers from computational inefficiency on the mobile devices due to the limited hardware for digital holographic processing. Specifically, to reconstruct the high-quality holographic image needs to compensate for the phase aberration, which needs lots of expensive optical hardware components to acquire measurements such as different axial distances, illumination angles, wavelengths, polarization states, and so on. To reduce computational complexity in digital holographic 3D human image reconstruction, we propose an efficient and effective algorithm to simplify Fresnel transforms for the mobile devices. Our algorithm reduces the number of FFTs and fastens the calculation of the exponential function in the Fresnel integral for the digital holography image reconstruction. Specifically, we reformulate the Fresnel integral and use a polynomial approximation to approximate the exponential function. In the holographic image quality improvement, we modify a maximum a posteriori (MAP) estimation to improve the quality of the reconstructed holographic 3D image restoration. Our algorithm outperforms previous approaches in not only smaller running time but also the better quality of the digital holographic 3D human image representation for the mobile devices.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9


  1. 1.

    An app is software running on a mobile device such as a mobile phone, PDAs or MP3 players performing specific tasks typically restricted to desktop or notebook computers. These apps are either pre-installed on the mobile devices during manufacture, or downloaded by users from Apple stores, android market, or other mobile software distribution platforms.


  1. 1.

    Ahrenberg L, Page AJ, Hennelly BM, McDonald JB, Naughton TJ (2009) In: Using Commodity Graphics Hardware for Real-Time Digital Hologram View-Reconstruction, vol 5 of 4, Journal of Display Technology

  2. 2.

    AndroidWorks N https://developer.nvidia.com/AndroidWorks

  3. 3.

    Bruckstein AM, Holt RJ, Netravali AN In: Holographic Representations of Images (1998), vol. 7 of 11, IEEE Transactions on Image Processing

  4. 4.

    Chan SH, Khoshabeh R, Gibson KB, Gill PE, Nguyen TQ (2011) An augmented lagrangian method for total variation video restoration. IEEE Trans Image Process 20 of 11:3097–3111

  5. 5.

    Chan CH, Kittler J (2012) Blur kernel estimation to improve recognition of blurred faces. In: IEEEE International Conference on Image Processing (ICIP), pp 1989–1993

  6. 6.

    Cheng C-J, Hwang W-J, Chen C-T, Lai X-J (2014) In: Efficient FPGA-Based Fresnel Transform Architecture for Digital Holography, vol. 10 of 4, Journal of Display Technology

  7. 7.

    Cody W, Waite W (1980) In: Software Manual for the Elementary Functions. Prentice-Hall

  8. 8.

    Cuche E, Marquet P, Depeursinge C (2000) Spatial filtering for zero-order and twin-image elimination in digital off-axis holography. Appl Opt 39:4070–4075

  9. 9.

    Demetrakopoulos TH, Mittra R (1974) In: Digital and optical reconstruction of images from suboptical diffraction patterns, vol. 13 of 3. Applied Optical, pp 665–V570

  10. 10.

    Domingo Mery DF (2000) A fast non-iterative algorithm for the removal of blur caused by uniform linear motion in x-ray images. 15th World Conference on Nondestructive Testing

  11. 11.

    Database, J. P. https://jpeg.org/plenodb/

  12. 12.

    Driggers RG (2003) Encyclopedia of optical engineering: Abe-las. CRC Press Publishing, pp 412–427

  13. 13.

    Ferraro P, De Nicola S, Coppola G, Finizio A, Alfieri D, Pierattini G (2004) Controlling image size as a function of distance and wavelength in fresnel-transform reconstruction of digital holograms. Opt Lett 29:854–856

  14. 14.

    Fucai Zhang IY, Yaroslavsky LP (2004) Algorithm for reconstruction of digital holograms with adjustable magnification. Opt Lett 29:1668–1670

  15. 15.

    Fukuoka T, Yutaka Mori TN (2015) Speckle reduction by spatial-domain mask in digital holography. J Displ Technol 12 of 4:315–322

  16. 16.

    GABOR D (1948) In: A new microscopic principle. Nature

  17. 17.

    Gao Z, Wang DY, Xuec YB, Xucd GP, Zhangc H, Wang YL (2018) 3d object recognition based on pairwise multi-view convolutional neural networks. J Vis Commun Image Represent 56:305–315

  18. 18.

    Gao Z, Wang DY, Wan SH, Zhang H, Wang YL (2019) Cognitive-inspired class-statistic matching with triple-constrain for camera free 3d object retrieval. Fut Gener Comp Syst 94:641–653

  19. 19.

    Gonzalez RC, Woods RE (2001) Digital image processing. Prentice-Hall Publishing

  20. 20.

    Goodman JW (2005) In: Introduction to Fourier Optics. 3rd edn, Greenwood Village CO Roberts and Company

  21. 21.

    Hong H, Zhang T (2003) Fast restoration approach for rotational motion blurred image based on deconvolution along the blurring paths. Photo-Opt Instrum Eng 12 (42):3471–3486

    Google Scholar 

  22. 22.

    Huang H, Qiua P, Panezai S, Hao S, Zhang D, Yang Y, Maa Y, Gaoa H, Gao L, Zhang Z, Zheng Z (2019) Continuous wave terahertz high-resolution imaging via synthetic hologram extrapolation method using pyroelectric detector. In: Optics and Laser Technology, vol 120 of 3

  23. 23.

    Imbe M, Nomura T Selective calculation for the improvement of reconstructed images in single exposure generalized phase-shifting digital holography, vol 53. Opt. Eng.

  24. 24.

    Jiji CV, Chaudhuri S (2006) single-frame image super-resolution through contourlet learning. EURASIP J Appl Signal Process 2006 2:1–11

    Google Scholar 

  25. 25.

    Kantabutra V (1996) In: On Hardware for Computing Exponential and Trigonometric functions, vol 45 of 3. IEEE Transactions on Computers

  26. 26.

    Kim S.-C, Kim E.-S (2008) In: Effective generation of digital holograms of three dimensional objects using a novel look-up table method, vol 47 of 19. Applied Optics

  27. 27.

    Kreis TM, Adams M, Werner P. O. J (1997) Methods of digital holography: A comparison. In: Proceedings of SPIE, vol 3098

  28. 28.

    Latychevskaia T, Fink H.-W Resolution enhancement in digital holography by self extrapolation of holograms. Opt Express 6:7726–7733

  29. 29.

    Lauterborn W, Kurz T (2003) In: Coherent Optics Fundamentals and Applications. Springer, pp 129–151

  30. 30.

    Lefevre V, Damien Stehle PZ (2008) Worst cases for the exponential function in the ieee 754r decimal64 format. In: Reliable Implementation of Real Number Algorithms: Theory and Practice, vol 5045. Springer, pp 114–126

  31. 31.

    Liu S-J, Wang D, Wang Q-H (2019) Speckle noise suppression method in holographic display using time multiplexing technique. Opt Commun 436:253–257

  32. 32.

    Lucente M (1993) In: Interactive computation of holograms using a lookup table, vol 2 of 1, J. Electron. Imaging

  33. 33.

    Masuda N, Ito T, Tanaka T, Shiraki A, Sugie T (2006) Computer generated holography using a graphics processing unit. Opt Express 14 of 2:587–592

  34. 34.

    Microsoft hololens (2015). In: https://www.microsoft.com/microsoft-hololens/en-us

  35. 35.

    Mohammad Tofighi KK, Cetin AE (2014) Denoising using projection onto convex sets (pocs) based framework. ICIP

  36. 36.

    Muller J (1997) In: Elementary Functions Algorithms and Implementation. Birkhauser Boston

  37. 37.

    Nishitsuji T, Shimobaba T, Sakurai T, Takada N, Masuda N, Ito T (2011) In: Fast calculation of Fresnel diffraction calculation using AMD GPU and OpenGL. OSA Tech. Dig

  38. 38.

    OK E (2006) Diffraction fourier optics and imaging. Wiley interscience

  39. 39.

    Pandey N, Kelly DP, Naughton TJ, and Hennelly BM (2009) In: Speed up of Fresnel transforms for digital holography using precomputed chirp and GPU processing, vol 7442. Proceedings of SPIE

  40. 40.

    Paturzo M, Memmolo P, Finizio A, N?s?nen R, Naughton TJ, Ferraro P (2010) In: Synthesis and display of dynamic holographic 3D scenes with real-world objects, vol 18 of 9. Optical Society of America, pp 8806–8815

  41. 41.

    Prasad S (2002) Statistical-information-based performance criteria for richardson-lucy image deblurring. J Opt Soc Amer 19(7):1286–1296

    Article  Google Scholar 

  42. 42.

    Ren Z, So HK-H, Lam EY (2019) Fringe pattern improvement and super-resolution using deep learning in digital holography. In: IEEE Transactions on industrial informatics

  43. 43.

    Ren Z, Zhimin X, Lam EY (2019) End-to-end deep learning framework for digital holographic reconstruction. Advanced Photonics:1 of 1

  44. 44.

    Rivenson Yair, Wu Y, Ozcan A (2019) Deep learning in holography and coherent imaging. In: Light science and applications

  45. 45.

    Roberto Corda CP (2019) A dataset of hologram reconstructions at different distances and viewpoints for quality evaluation. In: Eleventh international conference on quality of multimedia experience (qoMEX)

  46. 46.

    Rudin SL, Osher S, Fatemi E (1992) Nonlinear total variation based noise removal algorithms. Physica D 60:259–268

    MathSciNet  Article  Google Scholar 

  47. 47.

    Schuler CJ, Burger HC, Harmeling S, Scholkopf B (2013) A machine learning approach for non-blind image deconvolution. In: IEEE Proceedings of CVPR, pp 1067–1074

  48. 48.

    Shen H, Zhang L, Huang B, Li P (2007) A map approach for joint motion estimation, segmentation, and super resolution. IEEE Trans Image Process 16 (2):479–490

    MathSciNet  Article  Google Scholar 

  49. 49.

    Shuqun Zhang JZ Image resolution enhancement in digital holography. International Conference on Natural Computation

  50. 50.

    TensorFlow (2017) https://www.tensorflow.org/

  51. 51.

    Tikhonov AN (1963) Solution of incorrectly formulated problems and the regularization method. Soviet Math. Dokl.:1035–V1038

  52. 52.

    Tsang PWM, Cheung K, Poon T-C (2012) Real-time relighting of digital holograms based on wavefront recording plane method. Opt Express 20 of s2:5962–5967

  53. 53.

    Uddin MS, Sultana M, Islam Md Z (2011) Microsoft hololens. In: Fast Holographic Image Reconstruction using Graphics Processing Unit, vol 2. Journal of science and engineering, pp 35–42

  54. 54.

    Uzan A, Rivenson Y, Stern A Speckle denoising in digital holography by nonlocal means filtering, vol 52

  55. 55.

    Wang Z, Alan Conrad Bovik HRS, Simoncelli EP (2004) Image quality assessment from error visibility to structural similarity. IEEE Trans Image Process 13 (4):600–613

    Article  Google Scholar 

  56. 56.

    Wang Z, Lv GQ, Feng QB, Wang AT, Ming H (2019) Resolution priority holographic stereogram based on integral imaging with enhanced depth range. Opt Express 27 of 3:2689–2702

  57. 57.

    Xiao F, Farrell J, Catrysse P, Wandell B (2009) Mobile imaging: The big challenge of the small pixel. In: Digital Photography, vol 7250. SPIE, pp 72500

  58. 58.

    Yagle AE, Al-Salem FM (2003) Fast non-iterative single-blur 2-d blind deconvolution of separable and low-rank point-spread functions from finite-support images. In: D, vol 5205. Proceedings of SPIE, pp 390–398

  59. 59.

    Yitzhaky Y, Kopeika NS (1997) Identification of blur parameters from motion blurred images. CVGIP: Graph Model Image Process 59(5):321–332

    Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Chung-Hua Chu.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Chu, C. Efficient digital holographic 3d human image reconstruction and improvement on mobile devices. Multimed Tools Appl (2020). https://doi.org/10.1007/s11042-020-09089-w

Download citation


  • Digital holographic image reconstruction
  • Mobile devices
  • Image restoration
  • Hologram