Wiener Teager–Kaiser energy method for phase derivative estimation: application to speckle interferometry

Muhire, Desire; Tounsi, Yassine; Zada, Sara; Mashaly, Ahmed S.; Nassim, Abdelkrim

doi:10.1117/1.oe.56.11.114101

Cited by 3 publications

(1 citation statement)

References 28 publications

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“…However, it also causes blurring at sharp edges. Baselice et al [109] employed this filter for denoising ultrasound images and Muhire et al [110] applied for speckle denoising of images obtained from digital speckle pattern interferometry. The Wiener filters have been improved by taking into account the information contained in Fourier and wavelet domains [100] of the noisy image.…”

Section: Local Denoising Methodsmentioning

confidence: 99%

Speckle denoising techniques in imaging systems

Kumar

Tounsi

Kaur³

et al. 2020

J. Opt.

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In digital coherent imaging and measurement systems, the image/fringe pattern quality is severely degraded by multiplicative uncorrelated noise, called speckle, resulting due to the coherent nature of the light source, which restricts the development of several applications of these systems in various fields. Digital holography, holographic interferometry, speckle metrology, and shearography are the most revealing non-invasive imaging and measurement tools in many areas including scientific, engineering, biomedical, and industrial applications. However, the presence of undesired speckle noise in the processed image/phase distribution may lead to ambiguity in the observation or analysis of the associated physical parameters, and thus, limit their applications in many fields. To overcome this problem, a variety of algorithms/methods/techniques have been developed to eliminate the inherent speckle-noise introduced in the images/phase distribution obtained from these systems, depending on the requirement and the understanding of the noise characteristics. The speckle denoising is the pre-processing step in these systems and their performance determines the accuracy of the measurand physical parameter. This review article aims to cover some important state-of-art speckle denoising algorithms. For the purpose of demonstration, the performance and comprehensive study of these algorithms are evaluated on simulation and experimental data.

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Section: Local Denoising Methodsmentioning

confidence: 99%

Speckle denoising techniques in imaging systems

Kumar

Tounsi

Kaur³

et al. 2020

J. Opt.

Self Cite

View full text Add to dashboard Cite

show abstract

Wavelets Teager–Kaiser Hilbert approach for AM–FM signal demodulation: application in the field of speckle metrology

et al. 2020

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Deep Learning-Based 3D Measurements with Near-Infrared Fringe Projection

Wang

et al. 2022

Sensors

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Fringe projection profilometry (FPP) is widely applied to 3D measurements, owing to its advantages of high accuracy, non-contact, and full-field scanning. Compared with most FPP systems that project visible patterns, invisible fringe patterns in the spectra of near-infrared demonstrate fewer impacts on human eyes or on scenes where bright illumination may be avoided. However, the invisible patterns, which are generated by a near-infrared laser, are usually captured with severe speckle noise, resulting in 3D reconstructions of limited quality. To cope with this issue, we propose a deep learning-based framework that can remove the effect of the speckle noise and improve the precision of the 3D reconstruction. The framework consists of two deep neural networks where one learns to produce a clean fringe pattern and the other to obtain an accurate phase from the pattern. Compared with traditional denoising methods that depend on complex physical models, the proposed learning-based method is much faster. The experimental results show that the measurement accuracy can be increased effectively by the presented method.

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Wiener Teager–Kaiser energy method for phase derivative estimation: application to speckle interferometry

Cited by 3 publications

References 28 publications

Speckle denoising techniques in imaging systems

Speckle denoising techniques in imaging systems

Wavelets Teager–Kaiser Hilbert approach for AM–FM signal demodulation: application in the field of speckle metrology

Deep Learning-Based 3D Measurements with Near-Infrared Fringe Projection

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