Literature DB >> 28463310

Fast autofocusing in digital holography using the magnitude differential.

Meng Lyu, Caojin Yuan, Dayan Li, Guohai Situ.   

Abstract

Typical methods of automatic estimation of focusing in digital holography calculate every single reconstructed frame to get a critical function and then ascertain the focal plane by finding the extreme value of that function. Here, we propose a digital holographic autofocusing method that computes the focused distance using the first longitudinal difference of the magnitude of the reconstructed image. We demonstrate the proposed method with both numerical simulations and optical experiments of amplitude-contrast and phase-contrast objects. The results suggest that the proposed method performs better than other existing methods, in terms of applicability and computation efficiency, with potential applications in industrial and biomedical inspections where automatic focus tracking is necessary.

Year:  2017        PMID: 28463310     DOI: 10.1364/AO.56.00F152

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  1 in total

1.  Machine Learning Assisted Classification of Cell Lines and Cell States on Quantitative Phase Images.

Authors:  Andrey V Belashov; Anna A Zhikhoreva; Tatiana N Belyaeva; Anna V Salova; Elena S Kornilova; Irina V Semenova; Oleg S Vasyutinskii
Journal:  Cells       Date:  2021-09-29       Impact factor: 6.600

  1 in total

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