Compression of phase-only holograms with JPEG standard and deep convolutional neural network
It is a critical issue to reduce the enormous amount of data in the processing,storage and transmission of a hologram in digital format.In photograph compression,the JPEG standard is commonly supported by almost every system and device.It will be favorable if JPEG standard is applicable to hologram compression,with advantages of universal compatibility.However,the reconstructed image from a JPEG compressed hologram will suffer from severe quality degradation since some high frequency features in the hologram will be lost in the compression.In this work,we employ a deep convolutional neural network to reduce the artifacts in a JPEG compressed hologram.Simulation and experiment results reveal that our proposed"JPEG+deep learning"hologram compression scheme can achieve satisfactory reconstruction results for a computer-generated phase-only hologram.
hologram holography phase-only compression deep learning JPEG
Shuming Jiao Zhi Jin Chenliang Chang Changyuan Zhou Wenbin Zou Xia Li
Shenzhen Key Lab of Advanced Telecommunication and Information Processing,College of Information Eng Shenzhen Key Lab of Advanced Telecommunication and Information Processing,College of Information Eng Jiangsu Key Laboratory for Opto-Electronic Technology,School of Physics and Technology,Nanjing Norma
国内会议
新疆伊宁
英文
86-100
2018-08-01（万方平台首次上网日期，不代表论文的发表时间）