Fast Phase Unwrapping Algorithm Research Articles

Corrosion quantification of plate-type structures using Lamb wavefield and monogenic signal processing

Corrosion is one of the most common damage types which seriously affects structural safety. In this paper, a Lamb wavefield-based monogenic signal processing algorithm is proposed to quantify the corrosion parameters, including location, area, shape and depth, in plate-type structures. The monogenic signal processing based on Riesz transform will cause a serious problem, that is, phase wrapping. To solve this problem, a robust fast phase unwrapping algorithm is developed. Then, the phase spatial distribution of the extracted Lamb wavefield can be extracted, which can be used to calculate the wavenumber distribution. The wavenumber distribution is related to the structure thickness or corrosion depth, which can be further used for corrosion imaging. Simulated Lamb wavefield signals calculated by finite element simulation are employed to evaluate the parameters of circular corrosion and complex umbrella corrosion. The results show that the proposed algorithm has a great advantage in corrosion identification accuracy and calculation time compared with the existing algorithms. A completely non-contact laser ultrasonic system is established for acquiring Lamb wavefield containing square corrosion, and it is proved that the proposed algorithm is able to quantify the corrosion location, area, shape and depth with good accuracy in the experiment.

Lamb wavefield-based monogenic signal processing for quantifying delamination in composite laminates

Delamination is one of the common damages affecting the safety of composite structures. In this paper, a Lamb wavefield-based monogenic signal processing algorithm is proposed to quantify the delamination parameters in composite laminates, including location, size, shape, and depth. A quality-guided fast phase unwrapping algorithm is developed to solve the problem of phase wrapping after Riesz transform-based monogenic signal processing. Then, space distribution of the phase of Lamb wavefield can be extracted for calculating wavenumber distribution, which is related to the structural thickness or delamination depth and can be used for delamination imaging. Simulated Lamb wavefield signals calculated by finite element simulation are employed to evaluate the parameters of delamination in composite laminates. Compared with other traditional methods, the damage identification algorithm based on Riesz transform has excellent identification effect and shorter calculation time. The results show that the algorithm can be used not only for single delamination recognition but also for multi-delamination recognition with good accuracy. In particular, the interaction between incident waves along different ply directions and delamination is explored, and its influence on delamination quantification is studied, whose results are worthy of attention in engineering application. Finally, a completely non-contact laser ultrasonic system is established to obtain the Lamb wavefield with delamination. Experiments show that the algorithm can accurately quantify the location, size, shape, and depth of delamination.

Fast phase unwrapping algorithm based on region segmenting with mathematical morphology

Fast phase unwrapping algorithm based on region segmenting with mathematical morphology

Improved fast phase unwrapping algorithm based on parallel acceleration

Aiming at the shortcoming of low serial operational efficiency in the quality-map-guided phase-unwrapping algorithm proposed by Miguel, an improved algorithm for parallel merging of multiple low-reliability blocks is pro-posed. Under the condition that the original algorithm design idea is satisfied, the unwrapping path is redefined as the largest reliable edge of the block. In addition, based on the non-continuous characteristic of the unwrapping path of the original algorithm, a low-reliability block out-of-order merging strategy is proposed to make multiple merging tasks can be performed simultaneously. The improved algorithm uses a multi-threaded software architecture. The main thread is responsible for looping through the unprocessed blocks to check whether they meet the requirements of merging, and the child threads receive and perform the merge tasks. The experimental results show that the improved method is completely consistent with the processing results of the original algorithm, and the parallel improvement strategy can effectively use the computer's multi-core resources, so that the operational efficiency of the phase unwrapping algorithm is improved by more than 50%.

Comparison and combination of three spatial phase unwrapping algorithms

Two-dimensional (2D) phase unwrapping is a key step in the existing advanced metrology technologies such as optical interferometry, optical three-dimensional (3D) measurement, and satellite radar interferometry (SAR). In this paper, the performance of three spatial phase unwrapping algorithms, branch-cut phase unwrapping algorithm (BC), minimum discontinuity algorithm (MD), and fast phase unwrapping algorithm (FPU) were compared in the case of noise pollution. The results show that the MD algorithm has satisfactory behavior in anti-noise, but it is time consuming compared with the other two algorithms. Therefore, two hybrid algorithms, combining the MD algorithm with the BC algorithm and the FPU algorithm, respectively, were proposed in this paper. In these two new algorithms, the merits of fast speed of BC algorithm and FPU algorithm were fully taken into account, and the advantage of the strong anti-noise of MD algorithm was also exploited. The accuracy of the new algorithms is improved compared with the BC and FPU, and the speed of the new algorithms is improved compared with the MD. The effectiveness of two hybrid algorithms is verified by the results of simulation and actual experiments.

Computationally effective 2D and 3D fast phase unwrapping algorithms and their applications to Doppler optical coherence tomography.

We propose a simplification for a robust and easy to implement fast phase unwrapping (FPU) algorithm that is used to solve the phase wrapping problem encountered in various fields of optical imaging and metrology. We show that the number of necessary computations using the algorithm can be reduced compared to its original version. FPU can be easily extended from two to three spatial dimensions. We demonstrate the applicability of the two- and three-dimensional FPU algorithm for Doppler optical coherence tomography (DOCT) in numerical simulations, and in the imaging of a flow phantom and blood flow in the human retina in vivo. We introduce an FPU applicability plot for use as a guide in the selection of the most suitable version of the algorithm depending on the phase noise in the acquired data. This plot uses the circular standard deviation of the wrapped phase distribution as a measure of noise and relates it to the root-mean-square error of the recovered, unwrapped phase.

Fast phase unwrapping algorithm based on region partition for structured light vision measurement

Phase unwrapping is a key problem of phase-shifting profilometry vision measurement for complex object surface shapes. The simple path-following phase unwrapping algorithm is fast but has serious unwrapping error for complex shapes. The Goldstein+flood phase unwrapping algorithm can handle some complex shape object measurement; however, it is time consuming. We propose a fast phase unwrapping algorithm based on region partition according to a quality map of wrapped phase. In this algorithm, wrapped phase image is divided into several regions using partition thresholds, which are determined according to histogram of quality value. Each region is unwrapped by using a simple path-following phase algorithm and several groups with different priorities are generated. These groups are merged according to their priorities from high to low order and a final absolute phase is obtained. The proposed method is applied to wrapped phase images of three objects with and without noise. Experiments show that the proposed method is much faster, more accurate, and robust to noise than the Goldstein+flood algorithm in unwrapping complex phase image.

Fast pixel shifting phase unwrapping algorithm in quantitative interferometric microscopy

Quantitative interferometric microscopy is an important method for observing biological samples such as cells and tissues. As a key step in phase recovery, a fast phase unwrapping algorithm is proposed. By shifting mod 2\pi wrapped phase map for one pixel, then multiplying the original phase map and the shifted one, the phase discontinuities could be easily determined with high speed and efficiency. The method aims at enhancing phase retrieving efficiency without any background knowledge. We test our algorithm with both numerical simulation and experiments, by focusing our attentions on wrapped quantitative phase maps of cells. The results indicate that this algorithm features fast, precise and reliable.

Digital moir by a diffractive optical element for deformation analysis of ancient paintings

In this paper we propose a digital projection moiré system for full-field measurement of out-of-plane deformation of cultural heritage objects. The method is based on a new fringe generator realized by a diffractive optical element illuminated by a spherical wave phase. Two grating patterns on an object before and after deformation are captured by a CCD camera and stored in a computer. With the aid of fast Fourier transform, signal demodulating techniques and a robust and fast phase-unwrapping algorithm, a 3D mapping of deformation can be visualized. The simplicity of the system and the fact that only readily available and unsophisticated equipment is required characterize the proposed method. The theoretical basis of the device is presented. Furthermore, experimental results made with a test object and a real ancient wooden panel painting are presented to demonstrate the validity of the technique.

Fast phase-unwrapping algorithm based on a gray-scale mask and flood fill

Phase-unwrapping algorithms, an active and interesting subject in recent years, are important in a great number of measurement applications. Active research is being undertaken to develop reliable and high-speed procedures. The current process uses a gray-scale mask and the flood-fill concept from image processing for phase unwrapping. The algorithm unwraps phase from an area with higher reliability to one with lower reliability. In addition to robustness, the speed of the algorithm proposed is much faster than conventional routines. The experimental results of different algorithms are compared by analysis of a tooth plaster and a photoelastic specimen.