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

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 holog...
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Autor*in:	Shuming Jiao [verfasserIn] Zhi Jin [verfasserIn] Chenliang Chang [verfasserIn] Changyuan Zhou [verfasserIn] Wenbin Zou [verfasserIn] Xia Li [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	hologram holography phase-only compression deep learning JPEG convolutional neural network

Übergeordnetes Werk:	In: Applied Sciences - MDPI AG, 2012, 8(2018), 8, p 1258
Übergeordnetes Werk:	volume:8 ; year:2018 ; number:8, p 1258

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/app8081258

Katalog-ID:	DOAJ03815837X

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source	In Applied Sciences 8(2018), 8, p 1258 volume:8 year:2018 number:8, p 1258
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topic_facet	hologram holography phase-only compression deep learning JPEG convolutional neural network Technology T Engineering (General). Civil engineering (General) Biology (General) Physics Chemistry
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container_title	Applied Sciences
authorswithroles_txt_mv	Shuming Jiao @@aut@@ Zhi Jin @@aut@@ Chenliang Chang @@aut@@ Changyuan Zhou @@aut@@ Wenbin Zou @@aut@@ Xia Li @@aut@@
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callnumber-first	T - Technology
author	Shuming Jiao
spellingShingle	Shuming Jiao misc TA1-2040 misc QH301-705.5 misc QC1-999 misc QD1-999 misc hologram misc holography misc phase-only misc compression misc deep learning misc JPEG misc convolutional neural network misc Technology misc T misc Engineering (General). Civil engineering (General) misc Biology (General) misc Physics misc Chemistry Compression of Phase-Only Holograms with JPEG Standard and Deep Learning
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topic_title	TA1-2040 QH301-705.5 QC1-999 QD1-999 Compression of Phase-Only Holograms with JPEG Standard and Deep Learning hologram holography phase-only compression deep learning JPEG convolutional neural network
topic	misc TA1-2040 misc QH301-705.5 misc QC1-999 misc QD1-999 misc hologram misc holography misc phase-only misc compression misc deep learning misc JPEG misc convolutional neural network misc Technology misc T misc Engineering (General). Civil engineering (General) misc Biology (General) misc Physics misc Chemistry
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title	Compression of Phase-Only Holograms with JPEG Standard and Deep Learning
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title_sort	compression of phase-only holograms with jpeg standard and deep learning
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title_auth	Compression of Phase-Only Holograms with JPEG Standard and Deep Learning
abstract	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 suffers from severe quality degradation since some high frequency features in the hologram will be lost during the compression process. In this work, we employ a deep convolutional neural network to reduce the artifacts in a JPEG compressed hologram. Simulation and experimental results reveal that our proposed “JPEG + deep learning” hologram compression scheme can achieve satisfactory reconstruction results for a computer-generated phase-only hologram after compression.
abstractGer	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 suffers from severe quality degradation since some high frequency features in the hologram will be lost during the compression process. In this work, we employ a deep convolutional neural network to reduce the artifacts in a JPEG compressed hologram. Simulation and experimental results reveal that our proposed “JPEG + deep learning” hologram compression scheme can achieve satisfactory reconstruction results for a computer-generated phase-only hologram after compression.
abstract_unstemmed	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 suffers from severe quality degradation since some high frequency features in the hologram will be lost during the compression process. In this work, we employ a deep convolutional neural network to reduce the artifacts in a JPEG compressed hologram. Simulation and experimental results reveal that our proposed “JPEG + deep learning” hologram compression scheme can achieve satisfactory reconstruction results for a computer-generated phase-only hologram after compression.
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title_short	Compression of Phase-Only Holograms with JPEG Standard and Deep Learning
url	https://doi.org/10.3390/app8081258 https://doaj.org/article/31c2d7db03494cff847091e8a2f0d9ef http://www.mdpi.com/2076-3417/8/8/1258 https://doaj.org/toc/2076-3417
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author2	Zhi Jin Chenliang Chang Changyuan Zhou Wenbin Zou Xia Li
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Compression of Phase-Only Holograms with JPEG Standard and Deep Learning

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