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A fringe pattern normalization algorithm is proposed using the smoothing Kalman filter. The background intensity and the fringe amplitude are estimated consecutively. These estimates are subsequently utilized to obtain the normalized fringe pattern. The fringe pattern normalization can be performed by scanning it either in a row-column-wise or in a zigzag manner. The simulation and experimental results are provided to substantiate the practical applicability of the proposed 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. The potential of the proposed method is demonstrated via numerical simulations to identify different types of defect patterns at various noise levels. In addition, the practical applicability of the method is validated by experimental results.

The paper proposes a high throughput and non-contact technique based on diffraction phase microscopy and space-frequency method for non-invasive measurement of displacement and displacement derivatives. The technique relies on common-path interferometric design and interferogram processing based on the windowed Fourier transform, and has inherent advantages such as high stability, good throughput, single shot operation and robustness against noise and external disturbances. The utility of the proposed technique is demonstrated for practical applications in surface metrology using experimental results.

Optical interferometric techniques have come to forefront in precision metrology applications such as surface profilometry, deformation analysis and defect testing. Reliable phase measurement from a recorded fringe pat- tern is the primary goal in most of these interferometric techniques. A primary constraint for accurate phase measurement is non uniform intensity fluctuations in fringe patterns caused by irregular illumination, uneven reflectivities and pixel defects. This problem is further aggravated in dynamics studies with multiple image capture where the intensity fluctuations can vary with time and thus lead to several fringe patterns getting affected. In this paper, this problem is investigated using the second order optimization framework along with the total variation regularization on a graphic processing unit (GPU). In our study, a series of fringe patterns are simulated with additive white Gaussian noise at signal to noise ratio of 20 dB. To induce fringe corruption due to the non uniform intensity conditions, the object wave amplitude is varied using an ellipse shaped filter which enables brighter conditions or stronger amplitudes inside the elliptical boundary and relatively darker conditions or weaker amplitudes outside of it. For time varying studies, we varied the size of the filter sequentially to gener- ate a series of interferograms with temporally varying non-uniform intensities. Further, orientations of elliptical illuminations are changed to verify the robustness of the algorithm. For processing a series of interferograms each with size of 512 by 512 pixels with dynamic range of 10 (ratio of brightest to darkest amplitude), we obtained root mean square error less than 0.25 radians for every interferogram using the proposed method. The results show that the proposed method is robust for handling non-uniform intensity corruptions in fringe patterns for dynamics based investigations.

The paper introduces a method for studying flow dynamics using diffractive optical element based background-oriented schlieren (BOS). Our method relies on fringe demodulation using root multiple signal classification technique which provides high robustness against noise. Further, a graphics processing unit (GPU) based implementation is proposed which offers significant improvement in computational efficiency, and thus enables high speed analysis of flows. The performance of the method is demonstrated via numerical simulations and the practical applicability is also shown by analyzing a diffusion phenomenon in liquids by BOS., Journal

In this paper, we propose a fringe analysis method to address the problem of phase retrieval from interferogram corrupted with fringe amplitude non-uniformity, and show its practical application for nanoscale surface profilometry. The proposed method relies on the implementation of second order optimization combined with total variation regularization using graphic processing unit based computing. The capability of the proposed method is demonstrated via numerical simulations by inducing different amplitude non-uniformity patterns in the interferograms and through experimental non-invasive surface topography using 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. The practical viability of the proposed method is demonstrated for noninvasive nanoscale topography of a test target.

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. The performance of the proposed approach for retrieving phase maps with rapid edge variations is shown via numerical simulations. Further, the experimental validity of the proposed method is demonstrated for surface topography in diffraction phase microscopy.