Robust method to process nonuniform intensity holograms in digital holographic microscopy for nanoscale surface metrology.

In this work, we propose a method based on nonlinear optimization to process holograms corrupted with nonuniform intensity fluctuations in digital holographic microscopy. Our method focuses on formulating an objective function from the recorded signal and subsequently minimizing it using a second-order optimization algorithm. We demonstrate the effectiveness of our method for phase extraction in the presence of severe noise and rapid intensity variations through extensive numerical simulations.

Deep learning assisted non-contact defect identification method using diffraction phase microscopy.

Reliable detection of defects from optical fringe patterns is a crucial problem in non-destructive optical interferometric metrology. In this work, we propose a deep-learning-based method for fringe pattern defect identification. By attributing the defect information to the fringe pattern's phase gradient, we compute the spatial phase derivatives using the deep learning model and apply the gradient map to localize the defect.

Quantitative phase gradient metrology using diffraction phase microscopy and deep learning.

In quantitative phase microscopy, measurement of the phase gradient is an important problem for biological cell morphological studies. In this paper, we propose a method based on a deep learning approach that is capable of direct estimation of the phase gradient without the requirement of phase unwrapping and numerical differentiation operations. We show the robustness of the proposed method using numerical simulations under severe noise conditions.

Multiple phase extraction using graphics processing unit assisted unitary transformation method in digital holographic interferometry.

The article presents a method to estimate multiple phase maps from a moiré fringe signal obtained using digital holographic interferometry. The proposed method uses a unitary transformation based signal subspace approach, and shows high robustness against noise. In addition, the method facilitates the estimation of multiple phase maps in a single shot operation without the need for spectral filtering or multiple images.

Phase derivative estimation in digital holographic interferometry using a deep learning approach.

In digital holographic interferometry, reliable estimation of phase derivatives from the complex interference field signal is an important challenge since these are directly related to the displacement derivatives of a deformed object. In this paper, we propose an approach based on deep learning for direct estimation of phase derivatives in digital holographic interferometry. Using a Y-Net model, our proposed approach allows for simultaneous estimation of phase derivatives along the vertical and horizontal dimensions.

Dynamic displacement measurement in digital holographic interferometry using eigenspace analysis.

Non-contact measurement of displacement undergone by a deformed object is an important application problem in digital holographic interferometry. Such measurements usually demand reliable estimation of interference phase even in the presence of severe noise. This article describes a method for non-contact displacement testing by investigating a robust phase retrieval approach in digital holographic interferometry.

Automated defect identification from carrier fringe patterns using Wigner-Ville distribution and a machine learning-based method.

The paper presents a method for automated defect identification from fringe patterns. The method relies on computing the fringe signal's Wigner-Ville distribution followed by a supervised machine learning algorithm. Our machine learning approach enables robust detection of fringe pattern defects of varied shapes and alleviates the limitations associated with thresholding-based techniques that require careful control of the threshold parameter.

Demodulation of noisy interferograms with rapid phase variations and amplitude fluctuations using a surrogate principle-based optimization method.

This paper presents an optimization-based method for phase extraction from interferograms corrupted with noise, rapid phase variations, and localized amplitude fluctuations. In the proposed method, the phase retrieval problem is addresed by modeling a cost function using non-convex non-smooth total generalized variational regularization. Further, the surrogate principle is used to transform the cost function into convex form for convenient optimization framework.

Dynamic noncontact surface profilometry using a fast eigenspace method in diffraction phase microscopy.

Dynamic measurement of surface profile is an important requirement in nondestructive testing, especially for the inspection of large samples with consecutive area scans or test objects under translation. In this paper, we propose the application of an eigenspace signal analysis method in diffraction phase microscopy for reliable and noncontact dynamic surface metrology. We also propose the inclusion of a graphics processing unit (GPU) computing framework in our method to enable fast interferogram processing for dynamics-based investigations.

Step phase reconstruction using an anisotropic total variation regularization method in a diffraction phase microscopy.

This paper presents an approach to estimate the phase distribution with step features or edge characteristics from an interferogram obtained in diffraction phase microscopy. The proposed approach relies on formulation of a cost function for the interferogram and subsequent application of anisotropic total variation regularization based optimization. In our approach, the cost function is minimized by using a proximal gradient method based iterative approach with alternative updates of the amplitude and the phase.

Rapid deformation analysis in digital holographic interferometry using graphics processing unit accelerated Wigner-Ville distribution.

High-speed measurement of temporally varying displacement derivatives of a deformed object is an important and challenging problem in precision metrology. This paper proposes an approach for temporal deformation analysis using digital holographic interferometry, where a series of digital holograms is recorded corresponding to a test object subjected to variable load. Numerical reconstruction followed by superposition of these holograms provides a huge stack of interference or fringe pattern data, which needs to be processed to extract the displacement derivative information.

Phase recovery method in digital holographic interferometry using high-resolution signal parameter estimation.

This paper proposes a method for reliable estimation of phase in digital holographic interferometry. The method is based on analyzing the interference field signal locally using a high-resolution signal subspace technique. The proposed method offers single-shot phase retrieval ability and high robustness against severe noise.

Demodulation of moire fringes in digital holographic interferometry using an extended Kalman filter.

This paper presents a method for extracting multiple phases from a single moire fringe pattern in digital holographic interferometry. The method relies on component separation using singular value decomposition and an extended Kalman filter for demodulating the moire fringes. The Kalman filter is applied by modeling the interference field locally as a multi-component polynomial phase signal and extracting the associated multiple polynomial coefficients using the state space approach.

Phase correlation imaging of unlabeled cell dynamics.

We present phase correlation imaging (PCI) as a novel approach to study cell dynamics in a spatially-resolved manner. PCI relies on quantitative phase imaging time-lapse data and, as such, functions in label-free mode, without the limitations associated with exogenous markers. The correlation time map outputted in PCI informs on the dynamics of the intracellular mass transport.

Spatiotemporal characterization of a fibrin clot using quantitative phase imaging.

Studying the dynamics of fibrin clot formation and its morphology is an important problem in biology and has significant impact for several scientific and clinical applications. We present a label-free technique based on quantitative phase imaging to address this problem. Using quantitative phase information, we characterized fibrin polymerization in real-time and present a mathematical model describing the transition from liquid to gel state.

Nanoscale topography and spatial light modulator characterization using wide-field quantitative phase imaging.

We demonstrate an optical technique for large field of view quantitative phase imaging of reflective samples. It relies on a common-path interferometric design, which ensures high stability without the need for active stabilization. The technique provides single-shot, full-field and robust measurement of nanoscale topography of large samples.

Fringe demodulation using the two-dimensional phase differencing operator.

The Letter proposes a method for phase estimation from a fringe pattern. The proposed method relies on a parametric approach where the phase is locally approximated as a two-dimensional (2D) polynomial, with the ensuing polynomial coefficients as the respective parameters. These coefficients are then estimated using the phase differencing operator.

Multiple signal classification technique for phase estimation from a fringe pattern.

The paper introduces a multiple signal classification technique based method for fringe analysis. In the proposed method, the phase of a fringe pattern is locally approximated as a polynomial. The polynomial phase signal is then transformed to obtain signals comprising of only even- or odd-order polynomial coefficients.

Estimation of multiple phases from a single fringe pattern in digital holographic interferometry.

Simultaneous measurement of multidimensional displacements using digital holographic interferometry involves multi-directional illumination of the deformed object and requires the reliable estimation of the resulting multiple interference phase distributions. The paper introduces an elegant method to simultaneously estimate the desired multiple phases from a single fringe pattern. The proposed method relies on modeling the reconstructed interference field as a piecewise multicomponent polynomial phase signal.

Simultaneous measurement of in-plane and out-of-plane displacement derivatives using dual-wavelength digital holographic interferometry.

The paper introduces a method for simultaneously measuring the in-plane and out-of-plane displacement derivatives of a deformed object in digital holographic interferometry. In the proposed method, lasers of different wavelengths are used to simultaneously illuminate the object along various directions such that a unique wavelength is used for a given direction. The holograms formed by multiple reference-object beam pairs of different wavelengths are recorded by a 3-color CCD camera with red, green, and blue channels.

Application of complex-lag distributions for estimation of arbitrary order phase derivatives in digital holographic interferometry.

This Letter proposes a method to estimate phase derivatives of arbitrary order in digital holographic interferometry. Based on the desired order, the generalized complex-lag distribution is computed from the reconstructed interference field. Subsequently, the phase derivative is estimated by tracing the peak of the distribution.

Simultaneous multidimensional deformation measurements using digital holographic moiré.

This paper proposes an elegant technique for the simultaneous measurement of in-plane and out-of-plane displacements of a deformed object in digital holographic interferometry. The measurement relies on simultaneously illuminating the object from multiple directions and using a single reference beam to interfere with the scattered object beams on the CCD plane. Numerical reconstruction provides the complex object wave-fields or complex amplitudes corresponding to prior and postdeformation states of the object.