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On the assessment of de-noising algorithms in digital holographic interferometry and related approaches

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Abstract

As a general rule, the development of specific processing algorithms requires to accurately simulate data of interest by generating it as close as possible to the reality. In digital holographic interferometry and related approaches, the experimental phase data that are used for metrology purposes are corrupted by the speckle decorrelation noise. Thus, they require to be processed with advanced algorithms. To check the performances of de-noising algorithms before applying to real experimental data, simulations have to be carried out to provide quantitative errors and other related metrics of those performances. In litterature, many published papers dealing with the problem of phase de-noising in digital holographic interferometry consider Gaussian statistics and the hypothesis of noise stationarity, for simulating test data. However, considering the point spread function of digital holographic imaging systems, the noise in the phase data does not follow the Gaussian statistics. This means that considering Gaussian noise in data simulations is to make a big mistake on the nature of the noise in the holographic system. Therefore, in this paper, one aims at demonstrating that the Gaussian statistics are not well appropriated for simulating noise in holography, because such an approach systematically overestimates the performances of the algorithms. Then, using appropriate metrics such as mean standard deviation error, quality index, and peak-signal-to-noise-ratio, the paper demonstrates that the realistic speckle noise must be taken into account and correctly simulated for benchmarking overall algorithm performances.

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Authors and Affiliations

  1. Laboratoire d’Acoustique de l’Université du Mans, CNRS 6613, Institut d’Acoustique-Graduate School (IA-GS), Le Mans Université, Avenue Olivier Messiaen, 72085, Le Mans, France

    Silvio Montrésor & Pascal Picart

  2. École Nationale Supérieure d’Ingénieurs du Mans, rue Aristote, 72085, Le Mans Cedex 9, France

    Pascal Picart

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  1. Silvio Montrésor
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  2. Pascal Picart
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Correspondence to Pascal Picart.

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Montrésor, S., Picart, P. On the assessment of de-noising algorithms in digital holographic interferometry and related approaches. Appl. Phys. B 128, 59 (2022). https://doi.org/10.1007/s00340-022-07783-1

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