Literature DB >> 24007070

Real-time, auto-focusing digital holographic microscope using graphics processors.

Mert Doğar1, Hazar A İlhan, Meriç Özcan.   

Abstract

The most significant advantage of holographic imaging is that one does not need to do focusing alignment for the scene or objects while capturing their images. To focus on a particular object recorded in a digital hologram, a post-processing on the recorded image must be performed. This post-processing, so called the reconstruction, is essentially the calculation of wave propagation in free space. If the object's optical distance to the recording plane is not known a priori, focusing methods are used to estimate this distance. However, these operations can be quite time consuming as the hologram sizes increase. When there is a time constraint on these procedures and the image resolution is high, traditional central processing units (CPUs) can no longer satisfy the desired reconstruction speeds. Then, especially for real-time operations, additional hardware accelerators are required for reconstructing high resolution holograms. To this extend, today's commercial graphic cards offer a viable solution, as the holograms can be reconstructed tens of times faster with a graphics processing unit than with the state-of-the-art CPUs. Here we present an auto-focusing megapixel-resolution digital holographic microscope (DHM) that uses a graphics processing unit (GPU) as the calculation engine. The computational power of the GPU allows the DHM to work in real-time such that the reconstruction distance is estimated unsupervised, and the post-processing of the holograms are made completely transparent to the user. We compare DHM with GPU and CPU and present experimental results showing a maximum of 70 focused reconstructions per second (frps) with 1024 × 1024 pixel holograms.

Entities:  

Year:  2013        PMID: 24007070     DOI: 10.1063/1.4818285

Source DB:  PubMed          Journal:  Rev Sci Instrum        ISSN: 0034-6748            Impact factor:   1.523


  3 in total

1.  Autofocus method for automated microscopy using embedded GPUs.

Authors:  J M Castillo-Secilla; M Saval-Calvo; L Medina-Valdès; S Cuenca-Asensi; A Martínez-Álvarez; C Sánchez; G Cristóbal
Journal:  Biomed Opt Express       Date:  2017-02-22       Impact factor: 3.732

2.  Parallel implementations to accelerate the autofocus process in microscopy applications.

Authors:  Juan C Valdiviezo-N; Francisco J Hernandez-Lopez; Carina Toxqui-Quitl
Journal:  J Med Imaging (Bellingham)       Date:  2020-01-17

3.  Digital Holography as Computer Vision Position Sensor with an Extended Range of Working Distances.

Authors:  Miguel Asmad Vergara; Maxime Jacquot; Guillaume J Laurent; Patrick Sandoz
Journal:  Sensors (Basel)       Date:  2018-06-22       Impact factor: 3.576

  3 in total

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