2-D Continuous Wavelet Transform for ESPI phase-maps denoising

Escalante, Nivia; Villa, Jesús; Rosa, Ismael de la; Rosa, Enrique de la; Gonzalez-Ramirez, E.; Gutierrez, O Aquines; Olvera, Carlos Alberto Olvera; Araiza, María

doi:10.1016/j.optlaseng.2013.03.007

Cited by 22 publications

(6 citation statements)

References 11 publications

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“…In particular, the 2D continuous wavelet transform have recently been proposed for the processing of interferometric images. Advantages of denoising and demodulation of interferograms using the 2D CWT has been discussed in [44][45][46][47][48][49][50][51][52][53][54][55].…”

Section: The 2d Continuous Wavelet Transform For Processing Fringe Pamentioning

confidence: 99%

“…A comparison of the performance of this method compared with the windowed Fourier transform method [22] and the localized Fourier transform method [21] is shown in Table 1.I n this case, the normalized-mean-square-erro r( N M S E )w a su s e da st h em e t r i ca p p l i e do v e ra synthetic noisy phase map ψ (Figure 10). Although the performance against noise of the WFT is better that the 2D CWT method, this last is much simpler to implement, as discussed in [53].…”

Section: The 2d Cwt For Wrapped Phase Maps Denoisingmentioning

confidence: 99%

“…In particular, it has been shown that 1-D and 2D continuous wavelet transform (CWT) using Gabor atoms is a natural choice for proper analyses of fringe images. This kind of analysis has been used for fringe pattern denoising and fringe pattern demodulation showing several advantages, for example in laser plasma interferometry [38], in shadow moiré [39][40][41], in profilometry [42][43][44], in speckle interferometry [45], in digital holography [46], and other optical measurement techniques [47][48][49][50][51][52][53][54][55].…”

Section: Introductionmentioning

confidence: 99%

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The 2D Continuous Wavelet Transform: Applications in Fringe Pattern Processing for Optical Measurement Techniques

Hernández¹,

Rosa²,

GustavoRodríguez³

et al. 2018

Wavelet Theory and Its Applications

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Optical metrology and interferometry are widely known disciplines that study and develop techniques to measure physical quantities such as dimensions, force, temperature, stress, etc. A key part of these disciplines is the processing of interferograms, also called fringe patterns. Owing that this kind of images contains the information of interest in a codified form, processing them is of main relevance and has been a widely studied topic for many years. Several mathematical tools have been used to analyze fringe patterns, from the classic Fourier analysis to regularization methods. Some methods based on wavelet theory have been proposed for this purpose in the last years and have evidenced virtues to consider them as a good alternative for fringe pattern analysis. In this chapter, we resume the theoretical basis of fringe pattern image formation and processing, and some of the most relevant applications of the 2D continuous wavelet transform (CWT) in fringe pattern analysis.

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Section: The 2d Continuous Wavelet Transform For Processing Fringe Pamentioning

confidence: 99%

Section: The 2d Cwt For Wrapped Phase Maps Denoisingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The 2D Continuous Wavelet Transform: Applications in Fringe Pattern Processing for Optical Measurement Techniques

Hernández¹,

Rosa²,

GustavoRodríguez³

et al. 2018

Wavelet Theory and Its Applications

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“…The main aim of any fringe filtering technique being to remove the speckle noise effectively while preserving the details of the fringe pattern pertaining to the true interference phase, a number of noise filtering techniques of the phase fringe pattern have been proposed, such as the anisotropic sine/cosine average filter [1], the local histogram-data-orientated filter [2], the tangent least-squares fitting filter [3], the adaptive filter [4], etc. The fringe filtering techniques based on the use of regularized cost function with the complex-valued Markov random fields [5], windowed Fourier transform [6], local polynomial approximation of phase [7], localized Fourier transform [8] and 2D continuous wavelet tranform [9] have also been reported. The comparisons of few of the fringe filtering techniques can be found in [10,11].…”

Section: Introductionmentioning

confidence: 99%

Patch-wise denoising of phase fringe patterns based on matrix enhancement

Kulkarni

Rastogi

2016

Optics and Lasers in Engineering

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We propose a new approach for the denoising of a phase fringe pattern recorded in an optical interferometric setup. The phase fringe pattern which is generally corrupted by high amount of speckle noise is first converted into an exponential phase field. This phase field is divided into number of overlapping patches. Owing to the small size of each patch, the presence of a simple structure of the interference phase is assumed in it. Accordingly, the singular value decomposition (SVD) of the patch allows to separate the signal and noise components effectively. The patch is reconstructed only with the signal component. In order to further improve the robustness of the proposed method, an enhanced data matrix is generated using the patch and the SVD of this enhanced matrix is computed. The matrix enhancement results in an increased dimension of the noise subspace which thus accommodates more amount of noise component. Reassignment of the filtered pixels of the preceding patch in the current patch improves the noise filtering accuracy. The fringe denoising capability in function of the noise level and the patch size is studied. Simulation and experimental results are provided to demonstrate the practical applicability of the proposed method.

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“…However, the key point of these methods relies on an accurate estimation of fringe orientation, which is difficult to determine due to the noise in the image. The wavelet transform is an effective algorithm to remove the noise in the frequency domain, but it is not to be very effective at image edges [12]. WA has been proven that it can effectively filter off the noise in the ESSPI interferograms, but the drawback is that the performance lies on an appropriate threshold.…”

Section: Introductionmentioning

confidence: 99%

Combined denoising filter for fringe pattern in electronic speckle shearing pattern interferometry

Jia

Zhang

et al. 2015

Opt. Eng

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. (2015) Combined denoising filter for fringe pattern in electronic speckle shearing pattern interferometry. Optical Engineering, 54 (4). 043105. Permanent WRAP URL:http://wrap.warwick.ac.uk/93988 Copyright and reuse:The Warwick Research Archive Portal (WRAP) makes this work by researchers of the University of Warwick available open access under the following conditions. Copyright © and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable the material made available in WRAP has been checked for eligibility before being made available.Copies of full items can be used for personal research or study, educational, or not-for profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way.

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2-D Continuous Wavelet Transform for ESPI phase-maps denoising

Cited by 22 publications

References 11 publications

The 2D Continuous Wavelet Transform: Applications in Fringe Pattern Processing for Optical Measurement Techniques

The 2D Continuous Wavelet Transform: Applications in Fringe Pattern Processing for Optical Measurement Techniques

Patch-wise denoising of phase fringe patterns based on matrix enhancement

Combined denoising filter for fringe pattern in electronic speckle shearing pattern interferometry

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