Multiresolution Technique Research Articles

Three-Dimensional Flow Structures Behind a Wall-Mounted Short Cylinder with a Rear Inclined Hole

Three-dimensional (3-D) flow structures around a wall-mounted short circular cylinder, into which was drilled a rear inclined hole (RIH) going from the rear surface to the top surface of the cylinder, were instantaneously measured at Reynolds number 10,720 in a water tunnel by high-resolution tomographic particle image velocimetry (Tomo-PIV). Based on the measured instantaneous 3-D velocity distribution, the 3-D vorticity field, the criterion, and characteristics of arch-type and tip vortices were compared between the RIH cylinders and a standard cylinder. A 3-D -type arch vortex appeared behind the standard and RIH cylinders, and the height of the RIH cylinders was higher than that of the standard cylinder. Compared to the standard cylinder, the 3-D -type arch vortex and large-scale vortices broke down slowly in the wake of the RIH cylinders. A 3-D orthogonal wavelet multiresolution technique was used to decompose the 3-D velocity fields from the Tomo-PIV data. The time-averaged large-scale structures of the RIH cylinders exhibited a stronger M-shape arch vortex, and a strong -type-shape arch structure was extracted from the time-averaged intermediate-scale structures. Meanwhile, the tip vortices simultaneously existed in the large- and intermediate-scale structures. The heights of instantaneous large-scale streamwise structures were proportional to the hole height of the RIH cylinders. Large-scale spanwise vorticity components increase and the strength of vortex shedding decreases when using an RIH cylinder.

Multi-resolution technique integrated with smoothed particle element method (SPEM) for modeling fluid-structure interaction problems with free surfaces

Multi-resolution technique integrated with smoothed particle element method (SPEM) for modeling fluid-structure interaction problems with free surfaces

Application of improved multiresolution technique for the MPS method to fluid lubrication

Application of improved multiresolution technique for the MPS method to fluid lubrication

Smooth reverse subdivision of uniform algebraic hyperbolic B-splines and wavelets

In this work, we give an introduction of uniform algebraic hyperbolic [Formula: see text]-splines (UAH [Formula: see text]-splines) generated over the space spanned by [Formula: see text], in which [Formula: see text] is an integer larger than or equal to [Formula: see text] and [Formula: see text] is a tension parameter. Then, we construct a general formula of the refinement equation for any given order [Formula: see text] of these [Formula: see text]-splines. Using the matrix version of this equation, we have also constructed the subdivision formula for UAH [Formula: see text]-spline curves. In order to introduce a new reverse subdivision framework, entitled “Smooth Reverse Subdivision” associated with the cubic UAH [Formula: see text]-splines, by continuing this process, we present a new multiresolution technique for general topology curves. We illustrate our results by numerical experiments.

A scalable approach for the efficient segmentation of hyperspectral images

The number of applications of hyperspectral imaging (HSI) is steadily increasing, as technology evolves and cameras become more affordable. However, the volume of data in a hyperspectral image is large (order of Gigabytes) and standard off-the-shelf algorithms for multi-channel image analysis cannot be readily applied, due to the prohibitive computational time and large memory requirements. Therefore, new scalable approaches are required to perform hyperspectral image analysis. In this article we address an efficient methodology for conducting Unsupervised Image Segmentation – one of the basic and most fundamental image analysis operations. In the methodology proposed, unsupervised segmentation is conducted after transforming the spectral and spatial dimensions of the raw hyperspectral image into a more compact representation using multivariate and multiresolution techniques. The clusters identified in the compact image representation are then used to train a discriminative classifier. The classifier is then adapted and transferred for application to the raw image, where it will efficiently label all the original pixels. With the proposed methodology, the computational expensive operations (unsupervised clustering and classifier learning) are minimized, whereas the efficient implementation of the classifier guarantees the analysis at the native resolution. The effectiveness of the proposed methodology was tested on a real case study considering an industrial hyperspectral image capturing the reflectance spectrum for several objects made of different unknown materials. A significant reduction in the computational cost was achieved without compromising the quality of the unsupervised segmentation, demonstrating the potential of the proposed approach.

RECONSTRUCTION OF HIGH-RESOLUTION HEPATIC TUMOR CT IMAGES USING AN AUGMENTATION-BASED SUPER-RESOLUTION TECHNIQUE

Improving the resolution of medical images is crucial in diagnosis, feature extraction, and data retrieval. A significant group of super-resolution algorithms is multi-frame techniques. However, they are not appropriate to medical data since they need several frames of the same scene, which bring a high risk of radiation or require a considerable acquisition time. We propose a new data augmentation technique and employ it in a multi-frame image reconstruction algorithm to improve the resolution of pathologic liver CT images. The input to our algorithm is a 3D CT-scan of the abdominal region. Neighboring slices are considered to increase the resolution of a single slice. Augmented slices are prepared using the nearby slices and the interpolation approach. The new data is aligned to the original slice, and it is used as an augmented version of the data. Then, a multi-frame scheme is utilized to reconstruct the high-resolution image. Our method’s novelty is to remove the need for multiple scans of a patent to employ multi-resolution techniques in medical applications. The results reveal that the proposed method is superior to conventional interpolation methods and available augmentation techniques. Compared to the tricubic interpolation, the proposed method improved the PSNR by 3.1. Concerning conventional augmentation techniques, it enhanced the SSIM measure by 0.06. The proposed algorithm improved the SSIM by 0.11 compared to traditional interpolation techniques and 0.1 for recent researches. Therefore, a multi-frame super-resolution technique has the potential to reconstruct medical data better.

A high order multi-resolution WENO numerical scheme for solving viscous quantum hydrodynamic model for semiconductor devices

In this article, fifth order finite volume multi-resolution weighted essentially non-oscillatory (MR-WENO) scheme is developed for solving one-dimensional non linear viscous quantum hydrodynamical model for semiconductor devices with constant temperature. This non linear model consists of three equations, two equations for the current density and electron density, and third equation is the Poisson equation. The first two equations include the viscous and quantum correction terms. Further, numerical technique is used to obtain the solution due to high non linearity of considered model. The multi-resolution technique is used to reduce the computational cost of high resolution numerical scheme. In the procedure of derivation of the MR-WENO scheme unequal central spatial stencils are used and linear weights can be chosen any positive numbers with only restriction that their total sum is one. Various numerical test problems are considered to check the validity and accuracy of the derived numerical scheme. Further, the results obtained from considered numerical scheme are compared with those of kinetic flux vector splitting numerical scheme.

A coarse-grid projection method for accelerating incompressible MHD flow simulations

Coarse grid projection (CGP) is a multiresolution technique for accelerating numerical calculations associated with a set of nonlinear evolutionary equations along with stiff Poisson’s equations. In this article, we use CGP for the first time to speed up incompressible magnetohydrodynamics (MHD) flow simulations. Accordingly, we solve the nonlinear advection–diffusion equation on a fine mesh, while we execute the electric potential Poisson equation on the corresponding coarsened mesh. Mapping operators connect two grids together. A pressure correction scheme is used to enforce the incompressibility constrain. The study of incompressible flow past a circular cylinder in the presence of Lorentz force is selected as a benchmark problem with a fixed Reynolds number but various Stuart numbers. We consider two different situations. First, we only apply CGP to the electric potential Poisson equation. Second, we apply CGP to the pressure Poisson equation as well. The maximum speed-up factors achieved here are approximately 3 and 23, respectively, for the first and second situations. For the both situations, we examine the accuracy of velocity and vorticity fields as well as the lift and drag coefficients. In general, the results obtained by CGP are in an excellent to reasonable range of accuracy. The CGP results are significantly more accurate compared to the numerical simulations of the advection–diffusion and electric potential Poisson equations on pure coarse scale grids.

3D flow structures behind a wall-mounted short cylinder

A high-resolution Tomographic particle image velocimetry (Tomo-PIV), which consists of four high-resolution double-exposure CCD cameras, was used to measured three-dimensional (3D) flow structures behind a wall-mounted short cylinder of an aspect ratio 1 at Reynolds number 10,720 in a water tunnel. Based on the measured instantaneous 3D velocity distribution, 3D velocity fields, the vorticity, the Q criterion, the rear separation region and the characteristic of arch type vortex and tip vortices are first discussed. In order to evaluate 3D multi-scale wake flow structures and energetic flow structures, the 3D orthogonal wavelet multi-resolution technique and proper orthogonal decomposition (POD) are applied to analyze instantaneous 3D velocity fields of Tomo-PIV. A 3D W-type arch vortex behind the short cylinder is found, which is originated by the interaction between upwash and downwash flows. The head shape of arch vortex structure is associated with the aspect ratio of the cylinder. By using the 3D orthogonal wavelet multi-resolution analysis, the instantaneous arch vortex and streamwise vortices are extracted in the large-scale structures of the wavelet level 1. It also found that the intermediate-scale upwash flows play an important role in originating the head of W-type arch vortex. Strong small-scale structures appeared in the shear layer and were contained in the intermediate-scale structures. The POD analysis indicates that the first two modes account for 13.3% of the total turbulent fluctuating energy, and the first four POD modes exhibit several large-scale streamwise vortices.

3D orthogonal multi-resolution analysis of flow structures around an improved vehicle external mirror

This paper proposes vehicle door mirrors with a tip shape and ditch to reduce the aerodynamic drag. The mean drag coefficients Cd of various mirror models were first measured using load cells within a 103–105 Reynolds number range in a wind tunnel. The Cd of controlled mirrors with different ditch widths remained constant at approximately 0.75 and was lower than that of conventional mirrors. Using a large eddy simulation (LES), the 3D flow structures around modified and conventional mirrors were numerically analyzed at a Reynolds number of 2.8 × 105. Based on a three-dimensional orthogonal wavelet multi-resolution technique, the instantaneous three-dimensional vorticity and velocity were decomposed into three wavelet levels or scales: large scale with a 62 mm central scale, intermediate scale with a 29 mm central scale, and small scale with a 16 mm central scale. This indicated that the length of the region of the vorticity iso-surfaces in an improved door mirror model as the tip ditch decreases. Because the tip ditch produced the more streamwise vortices, the large-scale spanwise vortices were suppressed. The streamwise vortices and spanwise vortices of the small- and intermediate-scale structures increased, which is mainly caused by the ditch in the tip.

Multi-Steps Registration Protocol for Multimodal MR Images of Hip Skeletal Muscles in a Longitudinal Study

Image registration is crucial in multimodal longitudinal skeletal muscle Magnetic Resonance Imaging (MRI) studies to extract reliable parameters that can be used as indicators for physio/pathological characterization of muscle tissue and for assessing the effectiveness of treatments. This paper aims at proposing a reliable registration protocol and evaluating its accuracy in a longitudinal study. The hips of 6 subjects were scanned, in a multimodal protocol, at 2 different time points by a 3 Tesla scanner; the proposed multi-step registration pipeline is based on rigid and elastic transformations implemented in SimpleITK using a multi-resolution technique. The effects of different image pre-processing (muscle masks, isotropic voxels) and different parameters’ values (learning rates and mesh sizes) were quantitatively assessed using standard accuracy indexes. Rigid registration alone does not provide satisfactory accuracy for inter-sessions alignment and a further elastic step is needed. The use of isotropic voxels, combined with the muscle masking, provides the best result in terms of accuracy. Learning rates can be increased to speed up the process without affecting the final results. The protocol described in this paper, complemented by open-source software, can be a useful guide for researchers that approach for the first time the issues related to the muscle MR image registration.

Haar‐wavelet based approximation for pricing American options under linear complementarity formulations

AbstractIn this manuscript, we present a novel and highly accurate wavelet‐based approximation technique to explore the sensitivities and value of American options diagnosed by linear complementarity problems. For a detailed analysis of such financially relevant problems, we transform the actual final value problem into a dimensionless initial value problem. To avoid the unacceptable large truncation error, the unbounded domain is trimmed into a bounded domain. A remarkable observation is that to investigate the various physical and numerical aspects of the options' sensitivities; the proposed scheme is efficient as it explicitly provides the numerical approximation of all the derivatives of the solution function. The multiresolution technique of the wavelets and the convergence of the proposed wavelet scheme are comprehensively analyzed. The wavelet analysis is accompanied by illustrative examples to demonstrate the proficiency and robustness of the present method coupled with graphical representations. It has been shown that the present method is efficient to solve free boundary problems. It is worthy to note that the highly accurate and promising computational results are enough to confirm the performance of the proposed method. The simulated results of options' Greeks analyzed and discussed have vast applications in different financial institutes and trading markets.

Three-dimensional multiscale flow structures behind a wall-mounted short cylinder based on tomographic particle image velocimetry and three-dimensional orthogonal wavelet transform.

Three-dimensional (3D) flow structures around a wall-mounted short cylinder of height-to-diameter ratio 1 were instantaneously measured by a high-resolution tomographic particle image velocimetry (Tomo-PIV) at Reynolds number of 10 720 in a water tunnel. 3D velocity fields, 3D vorticity, the Q criterion, the rear separation region, and the characteristic of arch type vortex and tip vortices were first discussed. We found a strong 3D W-type arch vortex behind the short cylinder, which was originated by the interaction between upwash and downwash flows. This W-type arch vortex was reshaped to the M-shaped arch vortex downstream. It indicated that the head shape of the arch vortex structure depended on the aspect ratio of the cylinder. The large-scale streamwise vortices were originated by the downwash and upwash flows near the center location of W-type arch vortex. Then the 3D orthogonal wavelet multiresolution technique was developed to analyze instantaneous 3D velocity fields of Tomo-PIV in order to clarify 3D multiscale wake flow structures. The W-type shape arch vortex was extracted in the time-averaged intermediate-scale structure, while an M-shaped arch vortex was identified in the time-averaged large-scale structure. The tip vortices distributed in the time-averaged large- and intermediate-scale structures. The instantaneous intermediate-scale upwash vortices played an essential role in producing W-type head of arch structure. It was also observed that strong small-scale vortices appeared in the shear layer or near the bottom plate and most of them were contained in the intermediate-scale structures.

A Multiresolution Technique for the Classification of Precipitation Echoes in Radar Data

A new method for separating convective, intermediate, and stratiform rainfall based on the wavelet scale analysis is presented. A robust classification has resulted from the two choices: 1) the transformation of radar reflectivities to rain rates and 2) the inclusion of the intermediate class. The method uses a trous wavelet transform (WT) to separate heterogeneous convective features from the relatively smooth stratiform field. The heterogeneous region is further split into a convective class for the large wavelet coefficients and an intermediate class for the small wavelet coefficients. There is an improvement in the estimation of convective-stratiform fraction and frequency distribution of rain rates in comparison to the well-established Steiner method. The new method correctly reclassified a significant fraction of Steiner’s convective regions, which had low mean rain rates of 5.5 $\mathrm {mm}\cdot \mathrm {h}^{-1}$ , as stratiform regions. Similarly, Steiner’s stratiform regions, which had high mean rain rates of $15\,\,\mathrm {mm}\cdot \mathrm {h}^{-1}$ , are classified as convective by the wavelet method. The method is tested and evaluated over the Indian region during monsoon, and it is found that the three wavelet classes have distinct raindrop-size distributions.

Spacecraft close-range trajectory planning via convex optimization and multi-resolution technique

Discretization of the state and control is indispensable for solving a trajectory planning problem numerically via convex optimization, and uniform-grid discretization is the most common strategy in recent studies. However, when a higher-precision solution is desired, this kind of discretization will greatly increase the scale of optimization variables and then reduce the optimization efficiency. To remedy this weakness, a novel trajectory planning strategy for spacecraft relative motion is proposed in this paper by combining convex optimization and multi-resolution technique (MRT). In this optimization strategy, convex optimization works as an inner-layer algorithm for trajectory optimization, and the MRT works as an outer-layer algorithm for mesh refinement. Moreover, the no-fly zone constraints are considered in the trajectory optimization, and the affine approximations of the spherical and ellipsoidal no-fly zones are derived by the analytical formula of the tangent plane. Numerical simulations demonstrate the effectiveness of the proposed methods. Results show that the combined optimization method can adaptively adjust the local grid density according to the designed resolution level and performs better in computing efficiency than the traditional uniform discretization.

Modelling of high impedance faults in distribution systems and validation based on multiresolution techniques

The electric arc phenomenon associated with high impedance faults (HIFs) in distribution systems is an exciting subject that directly impacts over the reliability of electrical utilities, because fault currents are very small and present non-linearity and asymmetrical waveforms. Therefore, HIFs may be an undetectable phenomenon by overcurrent protections like fuses, re-closers, and relays. A HIF entails a challenge for its detection and location. In this sense, more realistic high impedance models, as well as reliable signal processing techniques, are needed to extract all transient characteristics aiming to detect HIFs in distribution networks. In this work, an efficient Resistive-HIF model is proposed and implemented into the Alternative Transients Program of the Electromagnetic Transients Program (ATP/EMTP) software to represent the main characteristics of HIFs. The model is compared against well-prove models by using two multiresolution approaches based on the Hermite transform and the Wavelet transform considering different frequency bands.

Denoising of image using bilateral filtering in multiresolution

One of the very efficient and resource conservative image processing methodology is with the help of bilateral filters. This technique filters the image without the help of edge smoothing but it does employs spatial averaging in a non-linear way. The filtering technique discussed above is very much dependent on the parameters of its filters. A very slight change in filter parameter values effects the outputs and results in a most drastic manner. In this paper, the author has worked on two contributions. In the applications concerning image denoising, the author has contributed in study of the parameter selection of bilateral filters which are optimal in nature. The contribution number two is about extending the present work i.e. extension of the filters which are bilateral in nature. In this process, the bilateral filtering of images is applied to the lower frequency sub-bands which is also known as approximation sub-band. This sub-band is obtained by using the wavelet transformations. Hence, a new framework for image denoising will be created which will be combination of multiresolution bilateral filtering and wavelets transformation techniques. As a matter of fact, this combination is efficient in contradicting noise from an image.

Learning Nonclassical Receptive Field Modulation for Contour Detection.

This work develops a biologically inspired neural network for contour detection in natural images by combining the nonclassical receptive field modulation mechanism with a deep learning framework. The input image is first convolved with the local feature detectors to produce the classical receptive field responses, and then a corresponding modulatory kernel is constructed for each feature map to model the nonclassical receptive field modulation behaviors. The modulatory effects can activate a larger cortical area and thus allow cortical neurons to integrate a broader range of visual information to recognize complex cases. Additionally, to characterize spatial structures at various scales, a multiresolution technique is used to represent visual field information from fine to coarse. Different scale responses are combined to estimate the contour probability. Our method achieves state-of-the-art results among all biologically inspired contour detection models. This study provides a method for improving visual modeling of contour detection and inspires new ideas for integrating more brain cognitive mechanisms into deep neural networks.

The Efficiency of Applying Compressed Sampling and Multi-Resolution Into Ultrasound Tomography

Introduction: This publication is the product of research developed within the research lines of the Smart Sensing, Signal Processing, and Applications (3SPA) research group throughout 2018, which supports the work of a doctor’s degree at VNU University of Engineering & Technology, Vietnam.
 Problem: The limitations of diagnostic ultrasound techniques using echo information has motivated the study of new imaging models in order to create additional quantitative ultrasound information in multi-model imaging devices. A promising solution is to use image sound contrast because it is capable of detecting changes in diseased tissue structures. Ultrasound tomography shows speed-of-sound changes in the propagation medium of sound waves. This technique is primarily used for imaging cancer-causing cells in womens’ breasts. The Distorted Born Iterative Method (DBIM), based on the first-order Born approximation, is an efficient diffraction tomography approach. The compressed sensing technique is utilized for DBIM to obtain the high-quality ultrasound image, although the image reconstruction process is quite long.
 Objective: The objective of the research is to propose an combined method for the efficient ultrasound tomography.
 Methodology: In this paper, we proposed an approach to enhance the imaging quality and to reduce the imaging time by applying the compressed sensing technique along with the multi-resolution technique for the DBIM.
 Results: The simulation results indicate that the imaging time is reduced by 33% and the imaging quality is improved by 83%.
 Conclusion: This project seeks to propose an improvement in ultrasound tomography. The simulated results confirmed the realibility of the propsed method.
 Originality: Through this research, a combined method of compressed sensing and multiple resolution are formulated for the first time in ultrasound tomography.
 Limitations: The lack of experiments to confirm the proposed method.

Identification of jet-like events using a multiplicity detector

We present a method for studying the detection of jets in high energy hadronic collisions using multiplicity detectors at forward rapidity. Such a study enhances the physics scope of multiplicity detectors at forward rapidities in LHC. At LHC energies the jets may be produced with significant cross section at forward rapidities. A multi-resolution wavelet analysis technique can locate the spatial position of jets due to its feature of space-scale locality. The discrete wavelet proves to be very effective in probing physics simultaneously at different locations in phase space and at different scales to identify jet-like events. The key feature this analysis exploits is the difference in particle density in localized regions of the detector due to jet-like and underlying events. We find that this method has a significant sensitivity towards detecting jet position and its size. The jets can be found with the efficiency and purity of the order of 46% with a cut of three times the root mean square of the typical wavelet coefficients distribution in minimum bias events.