Denoising 3D Integral Images by Unsupervised Deep Learning

Danielle Yaffe; Ayalla Reuven; Adrian Stern

doi:10.1364/3D.2023.DM1A.4

Denoising 3D Integral Images by Unsupervised Deep Learning

Danielle Yaffe, Ayalla Reuven, Adrian Stern

School of Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

3-D imaging techniques suffer from noise and deterioration of image quality. This work explores an unsupervised deep learning method for integral imaging denoising using a single shot that overcomes the problem of limited clean data.

Original language	English
Title of host publication	3D Image Acquisition and Display
Subtitle of host publication	Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023
Publisher	Optical Society of America
ISBN (Electronic)	9781957171289
DOIs	https://doi.org/10.1364/3D.2023.DM1A.4
State	Published - 1 Jan 2023
Event	3D Image Acquisition and Display: Technology, Perception and Applications, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023 - Part of Imaging and Applied Optics Congress 2023 - Boston, United States Duration: 14 Aug 2023 → 17 Aug 2023

Publication series

Name	3D Image Acquisition and Display: Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023

Conference

Conference	3D Image Acquisition and Display: Technology, Perception and Applications, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023 - Part of Imaging and Applied Optics Congress 2023
Country/Territory	United States
City	Boston
Period	14/08/23 → 17/08/23

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Space and Planetary Science
Electrical and Electronic Engineering
Instrumentation
General Computer Science
Control and Systems Engineering

Access to Document

10.1364/3D.2023.DM1A.4

Cite this

Yaffe, D., Reuven, A., & Stern, A. (2023). Denoising 3D Integral Images by Unsupervised Deep Learning. In 3D Image Acquisition and Display: Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023 (3D Image Acquisition and Display: Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023). Optical Society of America. https://doi.org/10.1364/3D.2023.DM1A.4

Yaffe, Danielle ; Reuven, Ayalla ; Stern, Adrian. / Denoising 3D Integral Images by Unsupervised Deep Learning. 3D Image Acquisition and Display: Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023. Optical Society of America, 2023. (3D Image Acquisition and Display: Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023).

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title = "Denoising 3D Integral Images by Unsupervised Deep Learning",

abstract = "3-D imaging techniques suffer from noise and deterioration of image quality. This work explores an unsupervised deep learning method for integral imaging denoising using a single shot that overcomes the problem of limited clean data.",

author = "Danielle Yaffe and Ayalla Reuven and Adrian Stern",

note = "Publisher Copyright: {\textcopyright} 2023 The Author (s).; 3D Image Acquisition and Display: Technology, Perception and Applications, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023 - Part of Imaging and Applied Optics Congress 2023 ; Conference date: 14-08-2023 Through 17-08-2023",

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doi = "10.1364/3D.2023.DM1A.4",

language = "English",

series = "3D Image Acquisition and Display: Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023",

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Yaffe, D, Reuven, A & Stern, A 2023, Denoising 3D Integral Images by Unsupervised Deep Learning. in 3D Image Acquisition and Display: Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023. 3D Image Acquisition and Display: Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023, Optical Society of America, 3D Image Acquisition and Display: Technology, Perception and Applications, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023 - Part of Imaging and Applied Optics Congress 2023, Boston, United States, 14/08/23. https://doi.org/10.1364/3D.2023.DM1A.4

Denoising 3D Integral Images by Unsupervised Deep Learning. / Yaffe, Danielle; Reuven, Ayalla; Stern, Adrian.
3D Image Acquisition and Display: Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023. Optical Society of America, 2023. (3D Image Acquisition and Display: Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 3-D imaging techniques suffer from noise and deterioration of image quality. This work explores an unsupervised deep learning method for integral imaging denoising using a single shot that overcomes the problem of limited clean data.

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T3 - 3D Image Acquisition and Display: Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023

BT - 3D Image Acquisition and Display

PB - Optical Society of America

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Y2 - 14 August 2023 through 17 August 2023

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Yaffe D, Reuven A, Stern A. Denoising 3D Integral Images by Unsupervised Deep Learning. In 3D Image Acquisition and Display: Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023. Optical Society of America. 2023. (3D Image Acquisition and Display: Technology, Perception and Applications in Proceedings Optica Imaging Congress, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023). doi: 10.1364/3D.2023.DM1A.4

Denoising 3D Integral Images by Unsupervised Deep Learning

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