Reconstruction Distance Research Articles

Speckle Characteristic Based Auto-focusing Approach for Diffuse Object in Digital Holography

Multi-wavelength digital holography extends the axial measurement range to the order of several tens of microns or more and makes the inspection of optical-rough objects and objects with steep slopes possible. As the optical-rough surface would superimpose speckle field on hologram, the existing focus evaluation criteria frequently fail in indicating correct reconstruction distance. This paper proposes a focus evaluation algorithm for focus detection of diffused surfaces. The average size of the speckle is used as the index and the average size of speckle is evaluated through morphological image processing. Two roughness specimens and a gear tooth are used as test pieces to validate the feasibility of the proposed method. Compared with the existing image focus evaluation method, the proposed morphological average size of speckle approach shows good robustness and sensitivity to various kinds of diffusing surface of mechanical parts.

Integrative morphological, cytogenetic and molecular characterization of the Andean climbing catfish Astroblepus mindoensis (Regan, 1916) (Siluriformes:Astroblepidae).

Astroblepus species, commonly known as Andean climbing catfish, exhibit a unique challenge in species delimitation, leading to ongoing taxonomic debates. Here we report data on Astroblepus mindoensis, a vulnerable species endemic to Ecuador, obtained by an integrative approach that includes cytogenetic analysis, molecular identification of the specimens, and recording of morphological and morphometric characters useful for species diagnosis. Thus, this study aimed to associate the karyotype data of the specimens analyzed with morphological and molecular characters, improving and expanding the existing taxonomic information, thus contributing to the systematics of the species. Our morphology results, unlike Regan's original description, which is brief and ambiguous, provide a more detailed morphometric and meristic description. Molecular phylogenetic reconstruction and genetic distance based on a fragment of the cytochrome c oxidase subunit I (COI) showed that our samples constitute a well-supported and monophyletic clade within the A. grixalvii species complex. The cytogenetic analysis identified distinct chromosomal markers, including a single cluster of major ribosomal genes (on chromosome pair 3) and of minor ribosomal genes (on chromosome pair 12) with their localization differing from those reported in other Astroblepus species analyzed. Additionally, the presence of a heteromorphic chromosome pair in males suggests the presence of an XX/XY sex-determination system that has not been identified in other congeneric species. Further investigation is necessary to determine if these chromosomes are associated with the accumulation of repeated sequences, as typically occurs with sex chromosomes, and to assess their presence in other species of the genus.

Fast autofocusing in off-axis digital holography based on search region segmentation and dichotomy

Autofocusing is a critical step in digital holography for reconstructing high-quality intensity and phase information, especially for the dynamic detection of moving objects. Some commonly used autofocusing methods in digital holography are time-consuming as they search over a large range to find a unique reconstruction distance. In this study, we propose a new fast autofocusing method based on search region segmentation and dichotomy. First, a new search region is obtained by segmenting the original region and solving a system of inequality equations. Second, improving the focusing evaluation function and combining this function with the dichotomy method transforms the discriminating minimum of the evaluation function into the detection of the zero-crossing position, reducing the number of searches required for the autofocusing method. The effectiveness of the proposed autofocusing method is validated through numerical simulations and experiments. The proposed method can significantly improve computational efficiency while guaranteeing the detection accuracy of the focusing plane compared with conventional methods.

Accurate and fast autofocusing in off-axis digital holography based on step reduction search and particle swarm optimization

The accurate reconstruction distance is one of the important parameters in digital holography. Typical autofocusing methods have been proposed for digital holography to determine the focusing plane. In these methods, a series of holograms at fixed-step intervals always needed to be reconstructed and then locate the focal plane by using an evaluation function, a procedure that is very time-consuming. In this paper, an accurate and fast autofocusing method for off-axis digital holograms is proposed. The method first employs the step reduction search algorithm and the integral amplitude modulus (AMP) evaluation function with low computational effort to iteratively reduce the searching range of the focal plane. Then the particle swarm optimization (PSO) algorithm and a difference-in-amplitude (DIF) evaluation function with high sensitivity are used to accurately locate the focal plane. Numerical and experimental results show that the proposed method significantly improves the focusing plane detection accuracy and computational efficiency compared with the typical autofocusing methods.

Application of compressive sensing to equivalent source method on near-field acoustic holography

Near-field acoustic holography (NAH) is an acoustic visualization technique that uses a microphone array to measure the radiated sound waves from a source in the near-field. In the present study, the equivalent source method (ESM) and the 2D spatial Fourier transform based on the generalized discrete Fourier series (GDFS) are compared, and the reconstruction performance of NAH using compressed sensing (CS) combined with both theories for NAH measurements is discussed. Additionally, the influence of different array designs (regular and pseudo-random) on the reconstruction performance of NAH is investigated. Simulations and experimentation are used to demonstrate its feasibility. In the simulation, three source models (dipole, longitudinal quadrupole and simply supported rectangular plate) are tested over a range of frequencies, SNR and reconstruction distances. The consequence indicates that use of GDFS results in a large reconstruction error in all test conditions under the rectangular array, especially in the high frequency range. The combination of a pseudo-random array and ESM-L1 provides the best reconstruction performance in most test conditions. In the experiment, two sets of pseudo-random microphone arrays with different diameters were used. They were tested separately for the dual loudspeakers and vibrating plate. ESM-L1 is suitable for reconstructing sound fields with sparse source distributions, whereas ESM-L2 is suitable for reconstructing sound fields with continuous source distributions, such as the radiated acoustic field of a vibrating plate. However, the use of pseudo-random arrays in combination with ESM is indeed a better solution for NAH.

Autofocusing in digital holography based on an adaptive genetic algorithm

In digital holography (DH), determining the reconstruction distance is critical to the quality of the reconstructed image. However, traditional focal plane detection methods require considerable time investment to reconstruct and evaluate holograms at multiple distances. To address this inefficiency, this paper proposes a fast and accurate autofocusing method based on an adaptive genetic algorithm. This method only needs to find several reconstruction distances in the search area as an initial population, and then adaptively optimize the reconstruction distance through iteration to determine the optimal focal plane in the search area. In addition, an off-axis digital holographic optical system was used to capture the holograms of the USAF resolution test target and the coin. The simulation and experimental results indicated that, compared with the traditional autofocusing, the proposed method can reduce the computation time by about 70% and improve the focal plane accuracy by up to 0.5 mm.

Improvement of digital Gabor holographic microscopy using a lens in plankton studies

This work utilizes a Gabor Holographic Optical Scheme integrated with a microscope objective and a thin convex plane lens. This bi-telecentric lens system corrects spherical aberration from the objective, maintains consistent magnification across various reconstruction distances, and ensures a plane incidence on CMOS. Depending on the focal lengths of the objective and lens, the final image can be enlarged or reduced compared to the classic Gabor system, resulting in high-quality reconstructed phase images without spherical aberration. This setup was employed to capture phase distribution and intensity images of planktonic objects, such as copepods, achieving superior image quality.

Sparse reconstruction of ultrasonic guided wave signals of fluid-filled pipes by multistrategy hybrid DBO-OMP using dispersive Hanning-windowed chirplet model

Ultrasonic guided waves (UGWs) in fluid-filled pipes are subject to more severe dispersion and coherent noise than those of vacant pipes, posing significant challenges for defect identification and localization. To this end, a novel sparse signal decomposition method called multistrategy hybrid dung beetle optimization based orthogonal matching pursuit (MHDBO-OMP) using dispersive Hanning-windowed chirplet model was proposed, of which the model not only represents the nonlinear frequency and asymmetric envelope of the dispersive UGW, but also contains the mode and propagation distance information, and this model exhibits better matching and interpretability than the other UGW models. For dispersive perturbed UGW signals with multiple modes and features, MHDBO-OMP achieves high reconstruction accuracy in both signal reconstruction (RES < 0.3) and propagation distance estimation (RES < 3 cm). When applied to experimental UGW signals obtained from water/oil-filled pipes containing cracks and corrosion pits, MHDBO-OMP successfully reconstructs dispersion-compensated signals that solely contain feature signals, and the minimum location error is 0.72 cm while the average location error is 2.65 cm. © 2001 Elsevier Science. All rights reserved.

Waveform reconstruction of core-collapse supernova gravitational waves with ensemble empirical mode decomposition

ABSTRACT Gravitational waves (GWs) from core-collapse supernovae (CCSNe) have been proposed as a probe to investigate the physical properties inside supernovae. However, how to search for and extract the GW signals from CCSNe remains an open question owing to their complicated time–frequency structure. In this paper, we apply the ensemble empirical mode decomposition (EEMD) method to decompose and reconstruct simulated GW data generated by the magnetorotational mechanism and the neutrino-driven mechanism within the Advanced LIGO, using the match score as the criterion for assessing the quality of the reconstruction. The results indicate that by decomposing the data, the sum of the first six intrinsic mode functions (IMFs) can be used as the reconstructed waveform. To determine the probability that our reconstructed waveform corresponds to a real GW waveform, we calculate the false alarm probability of reconstruction (FAPR). By setting the threshold of the match score to be 0.75, we obtain the FAPRs of GW sources at distances of 5 and 10 kpc to be 6 × 10−3 and 1 × 10−2, respectively. If we normalize the maximum amplitude of the GW signal to 5 × 10−21, the FAPR at this threshold is 4 × 10−3. Furthermore, in our study, the reconstruction distance is not equivalent to the detection distance. When the strain of GWs reaches 7 × 10−21, and the match score threshold is set at 0.75, we can reconstruct GW waveforms up to approximately 36 kpc.

Refocus criterion from image-plane speckle correlation in digital holographic interferometry.

In digital holography and holographic interferometry, refocusing to the correct image plane can be challenging and may be obtained by various metrics. This paper proposes a digital refocus approach utilizing the linear relationship between in-plane speckle motion and defocus as a response to an induced phase gradient. The theory based on cross-correlations between pairs of intensity images reconstructed at different distances from the recording plane is discussed. Two simple metrics, based on the cross-correlation properties of the reconstructed speckle images, are proposed and evaluated utilizing both simulations and experiments. Experiments exhibit similar trends in which the estimate of the correct reconstruction distance differs by a small amount between the two metrics. The difference is found less than 1% in the estimate of the true reconstruction distance. The results show that either metric is able to yield a sufficient reconstruction distance for the reconstruction of the image plane.

A method for suppressing spectrum aliasing of off-axis digital holograms based on Kronecker interpolation and backpropagation

The research proposes a new method to solve the spectrum aliasing and improve the resolution of off-axis digital holograms based on Kronecker interpolation and backpropagation algorithms. The method suppresses the direct current (DC) image and increase the low-frequency information with Kronecker interpolation of the hologram. The size of the Fresnel reconstructed image can be controlled with the reconstruction distance, and this feature is used to select the appropriate reconstruction distance for the Fresnel amplitude reconstruction of interpolated holograms to separate the real and imaginary images. To obtain the complete first-order spectral information for the object, the amplitude of the desired image is obtained with spatial domain filtering and then inverted. Finally, the amplitude and phase of the object are reconstructed according to the angular spectrum reconstruction algorithm. The results show that the method can solve the spectrum aliasing problem of the holograms and thus improve the resolution of off-axis holograms. In addition, the background noise of the reconstructed phase is reduced because the influence of the zero-order spectrum can be completely avoided.

Digital holographic microscopy applied to 3D computer micro-vision by using deep neural networks

Deep neural networks (DNNs) are increasingly employed across diverse fields of applied science, particularly in areas like computer vision and image processing, where they enhance the performance of instruments. Various advanced coherent imaging techniques, including digital holography, leverage different deep architectures like convolutional neural networks (CNN) or Vision Transformers (ViT). These architectures enable the extraction of diverse metrics such as autofocusing reconstruction distance or 3D position determination, facilitating applications in automated microscopy and phase image restitution. In this work, we propose a hybrid approach utilizing an adapted version of the GedankenNet model, coupled with a UNet-like model, for the purpose of accessing micro-objects 3D pose measurements. These networks are trained on simulated holographic datasets. Our approach achieves an accuracy of 98% in inferring the 3D poses. We show that a GedankenNet can be used as a regression tool and is faster than a Tiny-ViT (TViT) model. Overall, integrating deep neural networks into digital holographic microscopy and 3D computer micro-vision holds the promise of significantly enhancing the robustness and processing speed of holograms for precise 3D position inference and control, particularly in micro-robotics applications.

On the optical performance of incoherent digital holography for extended 3D objects

Digital Holography (DH) technology has grown fast over the years, offering the possibility to encode complex information from three-dimensional real-world objects onto two-dimensional digital supports. Accessing the object as an entire numerical complex wavefront raised large expectations in the fields of imaging and display. Holographic vision through fog, smoke, and flames in the far infrared (IR) range would be, in principle, applicable to the fields of automotive, video surveillance, and homeland security. However, the need for bulky, high-coherence laser sources has dampened the enthusiasm around the development of holographic cameras for use in such a context. Here, we investigate self-interference digital holography (SIDH) as a method for obtaining refocusable wavefronts by using low-coherence light sources, a category including light bulbs, arc lamps, light-emitting diodes, low-coherence IR lasers, heat sources, and sunlight. We develop and analyze a model to study the optical performance of SIDH in terms of reconstruction distance range, lateral magnification, resolution, and limiting factors. Then, we propose a configuration for reshaping the system Point Spread Function (PSF) and enhancing resolution by tuning the visibility of high-frequency fringes. The model is experimentally verified by imaging various scenes under incoherent illumination in the visible range. As a last testbed, we provide a first proof of concept SIDH imaging in the far IR range by retrieving and refocusing the complex wavefront back-scattered by point sources illuminated by low-coherence IR light.

Multi-Object Deep-Field Digital Holographic Imaging Based on Inverse Cross-Correlation

To address the complexity of small or unique reconstruction distances in digital holography, we propose an inverse cross-correlation-based algorithm for the digital holographic imaging of multiplanar objects with a large depth of field. In this method, a planar output mapping is closely around the objects, and it is established by calculating the image inverse cross-correlation matrix of the reconstructed image at similar reconstruction distances, whereby the object edges serve as the result guide. Combining the search for edge planes with the depth estimation operator, the depth of field of digital holography is improved, thus allowing for a digital holography that is capable of meeting the requirements of the holographic imaging of multiplanar objects. Compared with the traditional depth estimation operator method, the proposed method solves the reconstruction ambiguity problem in multiple planes with a simple optical path, and no additional optical or mechanical devices need to be added, thus greatly improving the reconstruction quality. The numerical calculation results and the experimental results with multiplanar samples validate the effectiveness of the proposed method.

Extended autofocusing in dual-wavelength digital holography.

In single-wavelength digital holography (DH), the phase wrapping phenomenon limits the total object depth that can be measured due to the requirement for well-resolved phase fringes. To address this limitation, dual-wavelength DH is proposed, enabling measurement of much deeper objects. In single-wavelength DH, because the object depth is limited, the depth of focus (DOF) of DH's optical system at a reconstruction distance is sufficient to cover the object depth. To date, many autofocusing algorithms have been proposed to obtain a correct reconstruction distance. However, in dual-wavelength DH, because the object depth is extended, the DOF at a reconstruction distance cannot cover the extended object depth. The extended object depth can span multiple DOFs, causing partially out of focus object depth. Therefore, in dual-wavelength DH, relying solely on autofocusing algorithms for a single distance is insufficient. But extended autofocusing algorithms, which can autofocus objects through multiple DOFs, are demanded. However, there are no such extended autofocusing algorithms in dual-wavelength DH. Therefore, we propose an extended autofocusing algorithm for dual-wavelength DH based on a correlation coefficient. The proposed algorithm is able to focus the whole object depth when the depth spans multiple DOFs. Through theoretical analysis, simulations, and experiments, the necessity and effectiveness of the proposed algorithm are verified.

Sound field reconstruction using sparse Bayesian learning equivalent source method with hyperparametric-coupled prior

Block sparse Bayesian learning (SBL) equivalent source method (ESM) suffers from the block structure mismatch problem that leads to poor sound field reconstruction accuracy for block sparse sources. To address this issue, this paper proposes to employ a hyperparametric-coupled prior in the SBL-ESM. In the method, a hierarchical SBL model is established based on the ESM, and then the coupling constraint is imposed to the hyper-prior of equivalent source strengths by a projection transformation. The proposed method can produce a coupling effect, such that the sparsity of equivalent source strengths is controlled not only by each corresponding hyper-parameter, but also by their immediate neighbors. Therefore, it enables to promote block sparse solutions and reconstruct the sound fields of block sparse sources well without the prior information of block partition. Numerical simulations of linear-block sources are used to verify the effectiveness and superiority of the proposed method, and the effects of sound power ratio, signal-to-noise ratio and reconstruction distance on the reconstructed results are investigated. Subsequently, the performance of the proposed method is further verified through an experiment of a composite loudspeaker and an experiment of the mixed sources consisting of a small loudspeaker and an impacted steel plate.

Phase-based reconstruction optimization method for digital holographic measurement of microstructures.

Digital holography has transformative potential in measuring stacked-chip microstructures due to its noninvasive, single-shot, full-field characteristics. However, uncertainties in reconstruction distance inevitably lead to resolving blur and reconstruction distortion. Herein, we propose a phase-based reconstruction optimization method that consists of a phase-evaluation function and a structured surface-characterization model. Our proposed method involves setting a reconstruction distance range, obtaining phase information using sliced numerical reconstruction, and optimizing the reconstruction distance by finding the extreme value of the function, which identifies the focal plane of the reconstructed image. The structure of the surface topography is then characterized using the characterization model. We perform simulations of the recording, reconstruction, and characterization to verify the effectiveness of the proposed method. To further demonstrate the approach, a simple holographic recording system is constructed to measure a standard resolution target, and the measurement results are compared with a commercial instrument. The simulation and experiment demonstrate, respectively, 31.16% and 34.41% improvement in step-height characterization accuracy.

Margination of platelet-sized particles in red blood cell suspensions flowing through a Y-shaped confluence microchannel

In blood flow through microvessels, platelets are known to be distributed in high concentrations near the vessel wall, termed ‘margination’ or ‘near-wall excess’. At the confluence of two vessels, this preferential distribution of platelets is thought to be compromised and reconstituted in the downstream main vessel. The present study aimed to investigate the distance of this margination reconstruction from the confluence by in vitro experiments using platelet-sized fluorescent particles as a platelet surrogate and a Y-shaped confluence microchannel with rectangular cross sections. Fluorescence microscopy was performed using a confocal laser scanning microscope system to measure the distribution of particles in the red blood cell suspension flow. Immediately after confluence, particles were highly concentrated along a narrow band in the middle of the channel width, where particles located near the inner wall of the daughter channels flowed in. This dense band of particles faded downstream and disappeared less than 5 mm from the confluence. This margination distance is comparable to or smaller than the margination development distance in straight channels, but much smaller than that after bifurcation.

Analysis of reconstruction quality for computer-generated holograms using a model free of circular-convolution error.

Continuous complex-amplitude computer-generated holograms (CGHs) are converted to discrete amplitude-only or phase-only ones in practical applications to cater for the characteristics of spatial light modulators (SLMs). To describe the influence of the discretization correctly, a refined model that eliminates the circular-convolution error is proposed to emulate the propagation of the wavefront during the formation and reconstruction of a CGH. The effects of several significant factors, including quantized amplitude and phase, zero-padding rate, random phase, resolution, reconstruction distance, wavelength, pixel pitch, phase modulation deviation and pixel-to-pixel interaction, are discussed. Based on evaluations, the optimal quantization for both available and future SLM devices is suggested.

Decorrelation and anti-correlation from defocus indigital holographic interferometry.

This paper presents a theoretical modeling of the speckle noise decorrelation in digital Fresnel holographic interferometry in out-of-focus reconstructed images. The complex coherence factor is derived by taking into account the focus mismatch, which depends on both the sensor-to-object distance and the reconstruction distance. The theory is confirmed by both simulated data and experimental results. The very good agreement between data demonstrates the high relevance of the proposed modeling. The particular phenomenon of anti-correlation in phase data from holographic interferometry is highlighted and discussed.