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Digital Holography Imaging Techniques and Applications Using Sensors

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 672

Special Issue Editor


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Guest Editor
1. Department of Optics, Optometry and Vision Science, University of Valencia, 46100 Burjassot, Spain
2. Biomedical Technology Center of the Medical Faculty, University of Muenster, 48149 Muenster, Germany
Interests: digital holographic microscopy; quantitative phase imaging; superresolution imaging; biomedical imaging; lensless holography; multimodal microscopy

Special Issue Information

Dear Colleagues,

In the few last decades, digital holography (DH) has experimented with exponential growth with the fast development of digital sensors, computers and coherent sources. Hence, many different DH techniques have been recently developed as well as a lot of different applications can be found nowadays in diverse fields such as virtual reality, information security, manufacturing or label-free microscopy.

This Special Issue, therefore, aims to gather original contributions and review articles on current advances in DH regarding techniques, technology and applications.

Topics include but are not limited to:

  • DH techniques;
  • Machine learning in DH;
  • DH microscopy;
  • Holographic tomography;
  • Lensless DH;
  • Lab-on-chip holography;
  • Computer-generated holograms;
  • Augmented and virtual reality;
  • 3D display and imaging;
  • Information security and defense;
  • Compressive sensing in DH;
  • Single-pixel DH;
  • DH applications in manufacturing.

Dr. Jose Angel Picazo-Bueno
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital holography
  • machine learning
  • digital holographic microscopy
  • holographic tomography
  • lensless holography
  • lab-on-chip holography
  • computer-generated holograms
  • virtual and augmented reality
  • 3D display and imaging
  • compressive sensing and single-pixel holography
  • information security

Published Papers (1 paper)

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Research

15 pages, 13016 KiB  
Article
Image Processing Techniques for Improving Quality of 3D Profile in Digital Holographic Microscopy Using Deep Learning Algorithm
by Hyun-Woo Kim, Myungjin Cho and Min-Chul Lee
Sensors 2024, 24(6), 1950; https://doi.org/10.3390/s24061950 - 19 Mar 2024
Viewed by 434
Abstract
Digital Holographic Microscopy (DHM) is a 3D imaging technology widely applied in biology, microelectronics, and medical research. However, the noise generated during the 3D imaging process can affect the accuracy of medical diagnoses. To solve this problem, we proposed several frequency domain filtering [...] Read more.
Digital Holographic Microscopy (DHM) is a 3D imaging technology widely applied in biology, microelectronics, and medical research. However, the noise generated during the 3D imaging process can affect the accuracy of medical diagnoses. To solve this problem, we proposed several frequency domain filtering algorithms. However, the filtering algorithms we proposed have a limitation in that they can only be applied when the distance between the direct current (DC) spectrum and sidebands are sufficiently far. To address these limitations, among the proposed filtering algorithms, the HiVA algorithm and deep learning algorithm, which effectively filter by distinguishing between noise and detailed information of the object, are used to enable filtering regardless of the distance between the DC spectrum and sidebands. In this paper, a combination of deep learning technology and traditional image processing methods is proposed, aiming to reduce noise in 3D profile imaging using the Improved Denoising Diffusion Probabilistic Models (IDDPM) algorithm. Full article
(This article belongs to the Special Issue Digital Holography Imaging Techniques and Applications Using Sensors)
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