# Compression of Phase-Only Holograms with JPEG Standard and Deep Learning

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## Abstract

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## 1. Introduction

## 2. Computer Generated Phase-Only Hologram with Error Diffusion Method

## 3. JPEG Image Compression and Proposed Artifact Reduction Scheme by Deep Convolutional Network

## 4. Results and Discussion

## 5. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**An example of complex hologram (

**left**); and phase-only hologram (

**right**) with a size of 4 × 4 pixels.

**Figure 3.**Propagation of errors to four different neighboring pixels with corresponding weighting coefficients in error diffusion algorithm.

**Figure 4.**(

**a**) Structure of deep convolutional network for the quality enhancement of JPEG compressed holograms in our work; and (

**b**) overall flowchart of our proposed “JPEG+deep learning” hologram compression scheme.

**Figure 7.**(

**a**) Original hologram; (

**b**) JPEG compressed hologram; and (

**c**) restored hologram with our proposed scheme.

**Figure 8.**Reconstructed images from original holograms, JPEG compressed holograms and restored holograms in numerical simulation.

**Figure 10.**Reconstructed images from original holograms, JPEG compressed holograms and restored holograms in optical experiments.

**Table 1.**PSNR (dB), SSIM, MS-SSIM, VIF and IFC values of reconstructed results from JPEG compressed holograms and restored holograms with our proposed scheme.

Cameraman | Pepper | ||||
---|---|---|---|---|---|

0.5 m | 0.3 m | 0.5 m | 0.3 m | ||

Compression ratio | 7.2113 | 7.1111 | 7.2113 | 7.1608 | |

Reconstructed image from compressed hologram | PSNR | 19.10 | 17.83 | 18.92 | 17.64 |

SSIM | 0.1651 | 0.0967 | 0.2007 | 0.1036 | |

MS-SSIM | 0.6091 | 0.4628 | 0.6907 | 0.5252 | |

VIF | 0.3946 | 0.2183 | 0.6396 | 0.3438 | |

IFC | 0.4522 | 0.2519 | 0.5543 | 0.2835 | |

Reconstructed image from restored hologram | PSNR | 28.86 | 26.86 | 29.88 | 27.16 |

SSIM | 0.6036 | 0.4465 | 0.6767 | 0.4852 | |

MS-SSIM | 0.8798 | 0.8022 | 0.9138 | 0.8343 | |

VIF | 0.5378 | 0.4316 | 0.6841 | 0.6306 | |

IFC | 0.9027 | 0.5098 | 1.2064 | 0.6379 |

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## Share and Cite

**MDPI and ACS Style**

Jiao, S.; Jin, Z.; Chang, C.; Zhou, C.; Zou, W.; Li, X. Compression of Phase-Only Holograms with JPEG Standard and Deep Learning. *Appl. Sci.* **2018**, *8*, 1258.
https://doi.org/10.3390/app8081258

**AMA Style**

Jiao S, Jin Z, Chang C, Zhou C, Zou W, Li X. Compression of Phase-Only Holograms with JPEG Standard and Deep Learning. *Applied Sciences*. 2018; 8(8):1258.
https://doi.org/10.3390/app8081258

**Chicago/Turabian Style**

Jiao, Shuming, Zhi Jin, Chenliang Chang, Changyuan Zhou, Wenbin Zou, and Xia Li. 2018. "Compression of Phase-Only Holograms with JPEG Standard and Deep Learning" *Applied Sciences* 8, no. 8: 1258.
https://doi.org/10.3390/app8081258