Low-pass Spatial Filter Research Articles

A primary wideband calibration method for noise hydrophones based on three-transducer spherical wave reciprocity in the frequency domain.

A primary wideband calibration method for noise hydrophones is developed, which can be applied to obtain noise acoustic spectral density sensitivity in the free-field. In this method, a wideband three-transducer spherical wave reciprocity calibration method is proposed in the frequency domain. A lowpass spatial domain filter is utilized to eliminate the reflecting acoustic waves from boundaries and water surface, and the wideband frequency responses of the transducer pair are calculated. Wideband calibrations are performed in a laboratory anechoic water tank, and two hydrophones with different reference sensitivities are calibrated in the frequency range of 250 Hz to 20 kHz using noise signals. The decidecade band sensitivities are obtained by the primary wideband calibration, which is in agreement with the single frequency sensitivities. The expended uncertainty of the primary wideband calibration is analyzed and estimated to be 8.9% (k = 2).

STUDY OF POISSON NOISE REDUCTION ON GAMMA CAMERA IMAGE USING SPATIAL DOMAIN FILTER

A gamma camera image is produced by a gamma camera that detects the gamma radiation emitted by the radioactive substance or radiopharmaceutical injected into the body. The gamma camera image sometimes has noise that can interfere with the diagnosis. This image is commonly affected by a Poisson-type random noise. This research proposes using a spatial domain filter to study Poisson noise reduction in gamma camera images. The image sample used is the image of a mouse injected with Lu-177-DOTA Trastuzumab with 100 µCi activity detected using a dual-head gamma camera with NaI(Tl) detectors. The grayscale image is treated with Poisson noise, then improved using a spatial domain filter. The spatial domain filters used include Mean, Median, Wiener, and Spatial Lowpass Filters. The mean filter is the best one that can reduce Poisson noise among the four applied filters. The best filter size for noise reduction is 3 with MSE 5.07, PSNR 41.08 dB, and SSIM 0.99.

Evaluating long-term water storage trends in small catchments and aquifers from a joint inversion of 20 years of GRACE/GRACE-FO mission data

SUMMARY More than 20 yr of measurement data of the gravity missions GRACE (Gravity Recovery And Climate Experiment) and GRACE-FO (GRACE-Follow-On) allow detailed investigations of long-term trends in continental terrestrial water storage (TWS). However, the spatial resolution of conventional GRACE/GRACE-FO data products is limited to a few hundred kilometres which restrains from investigating hydrological trends at smaller spatial scales. In this study GRACE and GRACE-FO data have been used to calculate TWS trends with maximized spatial resolution. Conventionally, GRACE/GRACE-FO is presented as a series of either unconstrained gravity fields post-processed with spatial low pass filters or constrained inversions commonly known as Mascon products. This paper demonstrates that both approaches to suppress spatially correlated noise are mathematically equivalent. Moreover, we demonstrate that readily inverting all available sensor data from GRACE/GRACE-FO for a single TWS trend map, together with annual variations and a mean gravity field, provides additional spatial detail not accessible from the standard products. The variable trade-off between spatial and temporal resolution as a unique feature of satellite gravimetry allows for gravity products that are tailored towards specific geophysical applications. We show additional signal content in terms of long-term water storage trends for four dedicated examples (Lake Victoria, Northwest India, Bugachany Reservoir and High Plains Aquifer) for which external information from other remote sensing instruments corroborates the enhanced spatial resolution of the new mean-field trend product.

Angular dependence of spatial frequency modulation in diffusion media

An optical field will undergo coherent diffusion when it is mapped into thermal-motioned atoms, e.g., in a slow or storage light process. As was demonstrated before, such diffusion effect is equivalent to a spatial low-pass filter attenuating the high spatial frequency (SF) components of the optical field. Here, employing electromagnetically induced transparency (EIT) based light storage in hot atomic vapor, we demonstrate that the angular deviation between the control and probe beams could be utilized as a degree of freedom to modulate the SF of the probe beam. The principle is to change the diffusion-induced low-pass filter into a band-pass filter, whose SF response can be tuned by varying the direction and magnitude of the angular deviation. Transverse multimode light fields, such as optical images and Laguerre-Gaussian modes are utilized to study such SF modulation. Our findings could be broadly applied to the fields of quantum information processing, all-optical image manipulation and imaging through diffusive media.

The role of the eye region for familiar face recognition: Evidence from spatial low-pass filtering and contrast negation.

What information is used for familiar face recognition? While previous research suggests a particular importance of the eye region, information from the rest of the face also needs to be integrated. What type of information is used in conjunction with the eyes is largely unclear. In three experiments, participants were asked to recognise so-called face chimeras, in which the eye region was not manipulated, while the rest of the face was either presented in negative contrast (contrast chimeras) or low-pass filtered (blur chimeras). We show (1) that both chimeras are recognised substantially better than fully blurred faces, (2) that the recognition advantage for blur chimeras is specific to the eye region but cannot be explained by cues available in this part of the face alone, and (3) that a combination of negative contrast and blurring outside of the eye region eliminates the chimera advantage. We conclude that full-frequency but distorted surface reflectance cues (in contrast chimeras) or coarse shape information (in blur chimeras) can be used in combination with the eye region for effective face recognition. Our findings further suggest that the face recognition system can flexibly use both types of information, depending on availability.

Mixed layer acoustic propagation with small scale ocean dynamics

The effects of dynamic oceanographic processes in the upper ocean mixed layer on acoustic propagation are investigated using at-sea sound speed observations and acoustic transmission simulations. The sound speed environment is based on a 400 m deep and 1000 km long East-West salinity and temperature transect that was collected during April of 2005 in the North Pacific where there is a mixed layer acoustic duct with a mean depth of 89 m. The deterministic baseline of this sound speed measurement is first estimated from the observations using a spatial lowpass filter with a cut off length scale of 50-km. The remaining small length scale variations in sound speed are assumed to have two physically distinct contributions: one due to the vertical displacement of isopycnals caused by eddies and internal waves and another due to compensating temperature and salinity anomalies along isopycnals termed spice. These two contributions can be separated yielding three distinct sound speed fields: i(1) the deterministic background; (2) thedisplacement field; and (3) the spice field. Acoustic transmission loss calculations are carried out on these three fields for frequencies of 400 and 1000 Hz for sources both in and below the mixed layer duct. Statistical and deterministic results for acoustic normal modes and full field transmission loss are presented, which quantify the relative importance of displacement and spice for acoustic propagation in the upper ocean.

Measurement Model and Dynamic Performance Analysis of Inlet Electrostatic Sensor on Aircraft Engine

Online electrostatic monitoring technology, which is equipped with foreknowledge information for aircraft engine faults, can effectively enhance flight safety and reduce costs. This paper provides a theoretical foundation for inlet electrostatic sensor design, which is the key issue of this technology. First, the induced principle of inlet electrostatic sensor is analyzed. Then, factors affecting spatial sensitivity distribution are quantitatively analyzed to obtain the sensitivity distribution frequency spectrum and dynamic response performance. This sensor is equivalent to a low-pass spatial filter. Results show that bandwidth changes depending on particle speed, radial position, and axial length. The optimal ring size is designed accordingly, considering sensor sensitivity, uniformity, mechanical processing, and installation.

Simulation of Optical Spatial Filters by Using Fast Fourier Transform

Due to wave nature of the light, harmonic analysis (Fourier transform) and superposition are used in analysis and design of optical systems and Fourier optics experiments. This study aims to illustrate use of fast Fourier transform computations in order to simulate optical spatial filter results. In order to design Fourier optics experiments or devices, it is quite useful to perform computer simulation and obtain theoretical results. In this study, fast Fourier transform based simulations for low-pass and high-pass optical spatial filter setups are carried out in Matlab environment and results of these simulations are report. Results indicate that this simulation method can be used for the design and analysis of optical spatial filters in addition to the optics education.

Parallel Analog Computing Based on a 2×2 Multiple-Input Multiple-Output Metasurface Processor With Asymmetric Response

We present a polarization-insensitive metasurface processor to perform spatial asymmetric filtering of an incident optical beam, thereby allowing for real-time parallel optical processing. To enable massive parallel processing, we introduce a novel Multi Input-Multi Output (MIMO) computational metasurface with an asymmetric optical response that can perform spatial differentiation on two distinct input signals regardless of their polarization. In our scenario, two distinct signals set in x and y directions, parallel and perpendicular to the incident plane, illuminate simultaneously the metasurface processor, and the resulting differentiated signals are separated from each other via appropriate Spatial Low Pass Filters (SLPF). By leveraging Generalized Sheet Transition Conditions (GSTCs) and surface susceptibility tensors, we design an asymmetric meta-atom augmented with normal susceptibilitiesto reach asymmetric optical response at normal beam illumination. Proof-of-principle simulations are also reported along with the successful realization of signal processing functions. The proposed metasurface overcomes major shortcomings imposed by previous studies such as large architectures arising from the need of additional subblocks, slow responses, and most importantly, supporting only a single input with a given polarization. Our results set the path for future developments of material-based analog computing using efficient and easy-to-fabricate MIMO processors for compact, fast, and integrable computing elements without any Fourier lens.

A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar

Abstract. Low-level clouds play a key role in the energy budget and hydrological cycle of the climate system. The accurate long-term observation of low-level clouds is essential for understanding their climate effect and model constraints. Both ground-based and spaceborne millimeter-wavelength cloud radars can penetrate clouds but the detected low-level clouds are always contaminated by clutter, which needs to be removed. In this study, we develop an algorithm to accurately separate low-level clouds from clutter for ground-based cloud radar using multi-dimensional probability distribution functions along with the Bayesian method. The radar reflectivity, linear depolarization ratio, spectral width, and their dependence on the time of the day, height, and season are used as the discriminants. A low-pass spatial filter is applied to the Bayesian undecided classification mask by considering the spatial correlation difference between clouds and clutter. The final feature mask result has a good agreement with lidar detection, showing a high probability of detection rate (98.45 %) and a low false alarm rate (0.37 %). This algorithm will be used to reliably detect low-level clouds at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) site for the study of their climate effect and the interaction with local abundant dust aerosol in semi-arid regions.

Application of High- and Low-Pass Spatial Filters in Analysis of Cone Penetration Test (CPTu)

The paper examines the high and low pass spatial filters used in the Cone Penetration Test (CPT) recordings in the soil and aims to demonstrate their usefulness and effectiveness in the interpretation of CPT measurements. The procedure of low-pass inverse filtration was used to reduce the effects associated with the occurrence of thin layers. High-pass filters were used to find places where the boundary of layers between different Soil Behaviour Type (SBT) could potentially exist. The application of both filters was tested on natural soils and on anthropological dumping soils.

Stable thin‐wire model of buried pipe‐type power distribution cables for 3D FDTD transient simulation

Underground cables such as pipe-type cables are widely used in urban power industry. In this study, an advanced thin-wire model of the pipe-type cables is 3D FDTD simulations. In this model, the multi-conductor cables are represented with two-level transmission line equations. A stabilising technique with a 1D spatial low-pass filter is proposed to maintain computational stability. Frequency-dependent losses are fully considered by using a vector-fitting technique. The proposed thin-wire model is validated with the multi-conductor transmission line theory analytically and the traditional FDTD method numerically. Good agreements are observed. It is found that the simulation maintains stability for 360,000-time steps. Compared to the traditional FDTD method, the memory space and computation time of the proposed model can be reduced by 73% and 98%, respectively. Induced lightning currents in a cable connection station are analysed. It is found that, without considering soil ionisation and soil stratification, the peak current in the metallic armour is 1.54 times as much as the one with considering these non-linear effects. It can be reduced by 9.04% and 18.6% if the cable is buried at depths of 1 m and 1.5 m, compared with the case of a 0.5 m buried depth.

The Spatiotemporal Variability of Nonorographic Gravity Wave Energy and Relation to Its Source Functions

AbstractThe way the large-scale flow determines the energy of the nonorographic mesoscale inertia–gravity waves (IGWs) is theoretically significant and practically useful for source parameterization of IGWs. The relations previously developed on the f plane for tropospheric sources of IGWs including jets, fronts, and convection in terms of associated secondary circulations strength are generalized for application over the globe. A low-pass spatial filter with a cutoff zonal wavenumber of 22 is applied to separate the large-scale flow from the IGWs using the ERA5 data of ECMWF for the period 2016–19. A comparison with GRACILE data based on satellite observations of the middle stratosphere shows reasonable representation of IGWs in the ERA5 data despite underestimates by a factor of smaller than 3. The sum of the energies, which are mass-weighted integrals in the troposphere from the surface to 100 hPa, as given by the generalized relations is termed initial parameterized energy. The corresponding energy integral for the IGWs is termed the diagnosed energy. The connection between the parameterized and diagnosed IGW energies is explored with regression analysis for each season and six oceanic domains distributed over the globe covering the Northern and Southern Hemispheres and the tropics. While capturing the seasonal cycle, the domain area-average seasonal mean initial parameterized energy is weaker than the diagnosed energy by a factor of 3. The best performance in regression analysis is obtained by using a combination of power and exponential functions, which suggests evidence of exponential weakness.

Low-pass filtering compensation in common-path digital holographic microscopy

A low-pass filtering compensation (LPFC) method is proposed to compensate for phase aberrations in point diffraction-based common-path digital holographic microscopy. This method estimates the phase aberration from the object hologram by Fourier transform and low-pass spatial filtering. The estimated phase aberration is subtracted from the object phase image to achieve single-hologram phase compensation. The accuracy and capability of LPFC for phase compensation were demonstrated by experiments on a Ronchi grating and a human blood smear. LPFC provides phase compensation for both smooth objects and objects containing abrupt edges, in the special case of a system with relatively high-frequency objects and low-frequency slight phase aberrations. LPFC operates without the need for fitting procedures, iterative steps, or prior knowledge of the optical parameters, which substantially simplifies the process of phase compensation in quantitative phase imaging.

Low-pass spatial filter based on 3D metamaterial rasorber with wideband absorption at high frequency

This paper presents the design and analysis of a low-pass spatial filter which has wideband absorption at high frequency using a 3D metamaterial rasorber (MR). The unit cell of the 3D MR is composed of several stacked layers of square patches with tapered dimensions, which are separated by thin lossy dielectric laminas. Every two adjacent layers’ metallic patches constitute a resonance cavity, and the inside lossy dielectric substrate results in absorption at the resonance frequency. The stacked metal–dielectric laminas construct a frustum pyramid. With the dimensions of the resonance cavities tapering from the bottom layer to the top layer, the pyramid absorbs over their resonance frequencies so that wideband absorption can be achieved. Besides, the incident wave at the frequencies below all these resonance frequencies can transmit through these cavities. Hence, the pyramid also constructs a low-pass spatial filter. The operation mechanism of this 3D MR structure is analyzed from several aspects by numerical simulation, and experimental measurement has also been executed to verify the design. The 3D metamaterial rasorber performs as an absorber in the Ku-band and a low-pass filter below the X-band. The absorption band with absorptivity higher than 80% spans from 12.3 GHz to 18.2 GHz, and the insertion loss at the frequency below 11.1 GHz is less than 0.9 dB.

A Mixed Transmitting-Receiving Beamformer With a Robust Generalized Coherence Factor: Enhanced Resolution and Contrast.

Adaptive beamforming has been widely studied for ultrasound imaging over the past few decades. The minimum variance (MV) and generalized coherence factor (GCF) approaches have been validated as effective methods. However, the MV method had a limited contribution to contrast improvement, while the GCF method suffered from severe speckle distortion in previous studies. In this article, a novel ultrasound beamforming approach based on MV and GCF beamformers is proposed to enhance the spatial resolution and contrast in synthetic aperture (SA) ultrasound imaging. First, the MV optimization problem is conceptually redefined by minimizing the total power of the transmitting and receiving outputs. Estimation of the covariance matrices in transmit and receive apertures is carried out and then utilized to determine adaptive weighting vectors. Second, a data-compounding method, viewed as a spatial low-pass filter, is introduced to the GCF method to optimize the spatial spectrum of echo signals and obtain better performance. Robust principal component analysis (RPCA) processing is additionally employed to obtain the final output. Simulation, experimental, and in vivo studies are conducted on different data sets. Relative to the traditional delay-and-sum (DAS) beamformer, mean improvements in the full-width at half-maximum and contrast ratio of 89% and 94%, respectively, are achieved. Thus, considerable enhancement of the spatial resolution and contrast is obtained by the proposed method. Moreover, the proposed method performs better in terms of the computational complexity. In summary, the proposed scheme effectively enhances ultrasound imaging quality.

Application of the Radon transform for search of candidate pulses in radio astronomy

We present an algorithm for the detection of candidate astronomical pulses. It is implemented in several steps. First, a spectrogram of a dispersed astronomical pulse is linearized in observing frequency followed by application of the Radon transform. The result of the transformation is displayed as a two-dimensional function. Next, the function is smoothed using a spatial low-pass filter. Finally, the maximum of the function above 90-deg angle is compared to the maximum of the standard deviation of the noise below 90-deg angle and a decision in favor of an astronomical pulse present or absent is made. Once pulse is detected, its dispersion measure (DM) is estimated by means of a basic equation relating the slope of the linearized dispersed pulse and the DM value. Performance of the algorithm is analyzed by applying it to a set of simulated fast radio bursts, experimental data of Masui pulse, and of seven rotating radio transients. The detection algorithm demonstrates results comparable to those by the conventional pulse detection algorithm.

Pixelated Carrier Phase-Shifting Shearography Using Spatiotemporal Low-Pass Filtering Algorithm.

Shearography has been widely used in non-destructive testing due to its advantages in providing full-field, high precision, real-time measurement. The study presents a pixelated carrier phase-shifting shearography using a pixelated micropolarizer array. Based on the shearography, a series of shearograms are captured and phase maps corresponding to deformation are measured dynamically and continuously. Using the proposed spatiotemporal filtering algorithm in the complex domain, the set of phase maps are simultaneously low-pass filtered in the spatial and temporal domains, resulting in better phase quality than spatial low-pass filtering. By accumulating the temporally adjacent phase, the phase corresponding to large deformation can be evaluated; thus, large deformations can be accurately measured and protected from speckle noise, allowing internal defects to be easily identified. The capability of the proposed shearography is described by theoretical discussions and experiments.

Attenuation of Position-Dependent Periodic Disturbance for Rotary Machines by Improved Spatial Repetitive Control With Frequency Alignment

In many real-world rotary machines, there is an inherent need to attenuate time-varying but position-dependent periodic disturbances. This article proposes an improved repetitive controller, in which a spatial internal model, a spatial low-pass filter, and a frequency alignment are synthesized. The controller is digitally implemented in a uniform time-sampling system. Specifically, a universal internal model of arbitrary periodic signal in spatial domain is derived for the attenuation of the position-dependent disturbances in the rotary machine, and a spatial low-pass filter is designed for the stability of the closed-loop system. Furthermore, a frequency alignment strategy is designed to compensate the bias resulted from the filter. Moreover, the cascaded utilization of the proposed controllers is introduced to improve the performance of a position-feedback servo system. Experimental verification and comparisons validate the feasibility and effectiveness of the proposed method in both single and cascaded configurations.

Hydrodynamic and Hydrographic Modeling of Istanbul Strait

The aim of this study is to model the hydrodynamic processes of the Istanbul Strait with its stratified flow characteristics, and calibrate the most important parameters using local and global search algorithms. For that, two open boundary conditions are defined, which are in the northern and southern parts of the Strait. Observed bathymetric, hydrographic, meteorological, and water-level data are used to set up the Delft3D-FLOW model. First, the sensitivities of the model parameters on the numerical model outputs are assessed using Parameter EStimation Tool (PEST) toolbox. Then, the model is calibrated based on the objective functions, focusing on the flow rates of the upper and lower layers. The salinity and temperature profiles of the strait are only used for model validation. The results show that the calibrated model outputs of the Istanbul Strait are reliable and consistent with the in situ measurements. The sensitivity analysis reveals that the spatial low-pass filter coefficient, horizontal eddy viscosity, Prandtl–Schmidt number, slope in log–log spectrum, and Manning roughness coefficient are most sensitive parameters affecting the flow rate performance of the model. The agreement between observed salinity profiles and simulated model outputs is promising, whereas the match between observed and simulated temperature profiles is weak, showing that the model can be improved, particularly for simulating the mixing layer.