Neural nets for aligning optical components in harsh environments: Beam smoothing spatial filter as an example

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Krasowski, Michael J.

1991-01-01

The goal is to develop an approach to automating the alignment and adjustment of optical measurement, visualization, inspection, and control systems. Classical controls, expert systems, and neural networks are three approaches to automating the alignment of an optical system. Neural networks were chosen for this project and the judgements that led to this decision are presented. Neural networks were used to automate the alignment of the ubiquitous laser-beam-smoothing spatial filter. The results and future plans of the project are presented.

Multi-Antenna Data Collector for Smart Metering Networks with Integrated Source Separation by Spatial Filtering

NASA Astrophysics Data System (ADS)

Quednau, Philipp; Trommer, Ralph; Schmidt, Lorenz-Peter

2016-03-01

Wireless transmission systems in smart metering networks share the advantage of lower installation costs due to the expandability of separate infrastructure but suffer from transmission problems. In this paper the issue of interference of wireless transmitted smart meter data with third party systems and data from other meters is investigated and an approach for solving the problem is presented. A multi-channel wireless m-bus receiver was developed to separate the desired data from unwanted interferers by spatial filtering. The according algorithms are presented and the influence of different antenna types on the spatial filtering is investigated. The performance of the spatial filtering is evaluated by extensive measurements in a realistic surrounding with several hundreds of active wireless m-bus transponders. These measurements correspond to the future environment for data-collectors as they took place in rural and urban areas with smart gas meters equipped with wireless m-bus transponders installed in almost all surrounding buildings.

Eulerian Time-Domain Filtering for Spatial LES

NASA Technical Reports Server (NTRS)

Pruett, C. David

1997-01-01

Eulerian time-domain filtering seems to be appropriate for LES (large eddy simulation) of flows whose large coherent structures convect approximately at a common characteristic velocity; e.g., mixing layers, jets, and wakes. For these flows, we develop an approach to LES based on an explicit second-order digital Butterworth filter, which is applied in,the time domain in an Eulerian context. The approach is validated through a priori and a posteriori analyses of the simulated flow of a heated, subsonic, axisymmetric jet.

Applications of Bayesian spectrum representation in acoustics

NASA Astrophysics Data System (ADS)

Botts, Jonathan M.

This dissertation utilizes a Bayesian inference framework to enhance the solution of inverse problems where the forward model maps to acoustic spectra. A Bayesian solution to filter design inverts a acoustic spectra to pole-zero locations of a discrete-time filter model. Spatial sound field analysis with a spherical microphone array is a data analysis problem that requires inversion of spatio-temporal spectra to directions of arrival. As with many inverse problems, a probabilistic analysis results in richer solutions than can be achieved with ad-hoc methods. In the filter design problem, the Bayesian inversion results in globally optimal coefficient estimates as well as an estimate the most concise filter capable of representing the given spectrum, within a single framework. This approach is demonstrated on synthetic spectra, head-related transfer function spectra, and measured acoustic reflection spectra. The Bayesian model-based analysis of spatial room impulse responses is presented as an analogous problem with equally rich solution. The model selection mechanism provides an estimate of the number of arrivals, which is necessary to properly infer the directions of simultaneous arrivals. Although, spectrum inversion problems are fairly ubiquitous, the scope of this dissertation has been limited to these two and derivative problems. The Bayesian approach to filter design is demonstrated on an artificial spectrum to illustrate the model comparison mechanism and then on measured head-related transfer functions to show the potential range of application. Coupled with sampling methods, the Bayesian approach is shown to outperform least-squares filter design methods commonly used in commercial software, confirming the need for a global search of the parameter space. The resulting designs are shown to be comparable to those that result from global optimization methods, but the Bayesian approach has the added advantage of a filter length estimate within the same unified framework. The application to reflection data is useful for representing frequency-dependent impedance boundaries in finite difference acoustic simulations. Furthermore, since the filter transfer function is a parametric model, it can be modified to incorporate arbitrary frequency weighting and account for the band-limited nature of measured reflection spectra. Finally, the model is modified to compensate for dispersive error in the finite difference simulation, from the filter design process. Stemming from the filter boundary problem, the implementation of pressure sources in finite difference simulation is addressed in order to assure that schemes properly converge. A class of parameterized source functions is proposed and shown to offer straightforward control of residual error in the simulation. Guided by the notion that the solution to be approximated affects the approximation error, sources are designed which reduce residual dispersive error to the size of round-off errors. The early part of a room impulse response can be characterized by a series of isolated plane waves. Measured with an array of microphones, plane waves map to a directional response of the array or spatial intensity map. Probabilistic inversion of this response results in estimates of the number and directions of image source arrivals. The model-based inversion is shown to avoid ambiguities associated with peak-finding or inspection of the spatial intensity map. For this problem, determining the number of arrivals in a given frame is critical for properly inferring the state of the sound field. This analysis is effectively compression of the spatial room response, which is useful for analysis or encoding of the spatial sound field. Parametric, model-based formulations of these problems enhance the solution in all cases, and a Bayesian interpretation provides a principled approach to model comparison and parameter estimation. v

Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naïve Bayesian Classifier-based approach.

PubMed

Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Changsen; Liu, Feixiang

2017-02-15

Common spatial pattern (CSP) is most widely used in motor imagery based brain-computer interface (BCI) systems. In conventional CSP algorithm, pairs of the eigenvectors corresponding to both extreme eigenvalues are selected to construct the optimal spatial filter. In addition, an appropriate selection of subject-specific time segments and frequency bands plays an important role in its successful application. This study proposes to optimize spatial-frequency-temporal patterns for discriminative feature extraction. Spatial optimization is implemented by channel selection and finding discriminative spatial filters adaptively on each time-frequency segment. A novel Discernibility of Feature Sets (DFS) criteria is designed for spatial filter optimization. Besides, discriminative features located in multiple time-frequency segments are selected automatically by the proposed sparse time-frequency segment common spatial pattern (STFSCSP) method which exploits sparse regression for significant features selection. Finally, a weight determined by the sparse coefficient is assigned for each selected CSP feature and we propose a Weighted Naïve Bayesian Classifier (WNBC) for classification. Experimental results on two public EEG datasets demonstrate that optimizing spatial-frequency-temporal patterns in a data-driven manner for discriminative feature extraction greatly improves the classification performance. The proposed method gives significantly better classification accuracies in comparison with several competing methods in the literature. The proposed approach is a promising candidate for future BCI systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Classification of visible and infrared hyperspectral images based on image segmentation and edge-preserving filtering

NASA Astrophysics Data System (ADS)

Cui, Binge; Ma, Xiudan; Xie, Xiaoyun; Ren, Guangbo; Ma, Yi

2017-03-01

The classification of hyperspectral images with a few labeled samples is a major challenge which is difficult to meet unless some spatial characteristics can be exploited. In this study, we proposed a novel spectral-spatial hyperspectral image classification method that exploited spatial autocorrelation of hyperspectral images. First, image segmentation is performed on the hyperspectral image to assign each pixel to a homogeneous region. Second, the visible and infrared bands of hyperspectral image are partitioned into multiple subsets of adjacent bands, and each subset is merged into one band. Recursive edge-preserving filtering is performed on each merged band which utilizes the spectral information of neighborhood pixels. Third, the resulting spectral and spatial feature band set is classified using the SVM classifier. Finally, bilateral filtering is performed to remove "salt-and-pepper" noise in the classification result. To preserve the spatial structure of hyperspectral image, edge-preserving filtering is applied independently before and after the classification process. Experimental results on different hyperspectral images prove that the proposed spectral-spatial classification approach is robust and offers more classification accuracy than state-of-the-art methods when the number of labeled samples is small.

An optimized solution of multi-criteria evaluation analysis of landslide susceptibility using fuzzy sets and Kalman filter

NASA Astrophysics Data System (ADS)

Gorsevski, Pece V.; Jankowski, Piotr

2010-08-01

The Kalman recursive algorithm has been very widely used for integrating navigation sensor data to achieve optimal system performances. This paper explores the use of the Kalman filter to extend the aggregation of spatial multi-criteria evaluation (MCE) and to find optimal solutions with respect to a decision strategy space where a possible decision rule falls. The approach was tested in a case study in the Clearwater National Forest in central Idaho, using existing landslide datasets from roaded and roadless areas and terrain attributes. In this approach, fuzzy membership functions were used to standardize terrain attributes and develop criteria, while the aggregation of the criteria was achieved by the use of a Kalman filter. The approach presented here offers advantages over the classical MCE theory because the final solution includes both the aggregated solution and the areas of uncertainty expressed in terms of standard deviation. A comparison of this methodology with similar approaches suggested that this approach is promising for predicting landslide susceptibility and further application as a spatial decision support system.

Optical correlation based pose estimation using bipolar phase grayscale amplitude spatial light modulators

NASA Astrophysics Data System (ADS)

Outerbridge, Gregory John, II

Pose estimation techniques have been developed on both optical and digital correlator platforms to aid in the autonomous rendezvous and docking of spacecraft. This research has focused on the optical architecture, which utilizes high-speed bipolar-phase grayscale-amplitude spatial light modulators as the image and correlation filter devices. The optical approach has the primary advantage of optical parallel processing: an extremely fast and efficient way of performing complex correlation calculations. However, the constraints imposed on optically implementable filters makes optical correlator based posed estimation technically incompatible with the popular weighted composite filter designs successfully used on the digital platform. This research employs a much simpler "bank of filters" approach to optical pose estimation that exploits the inherent efficiency of optical correlation devices. A novel logarithmically mapped optically implementable matched filter combined with a pose search algorithm resulted in sub-degree standard deviations in angular pose estimation error. These filters were extremely simple to generate, requiring no complicated training sets and resulted in excellent performance even in the presence of significant background noise. Common edge detection and scaling of the input image was the only image pre-processing necessary for accurate pose detection at all alignment distances of interest.

3D-FFT for Signature Detection in LWIR Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Medvick, Patricia A.; Lind, Michael A.; Mackey, Patrick S.

Improvements in analysis detection exploitation are possible by applying whitened matched filtering within the Fourier domain to hyperspectral data cubes. We describe an implementation of a Three Dimensional Fast Fourier Transform Whitened Matched Filter (3DFFTMF) approach and, using several example sets of Long Wave Infra Red (LWIR) data cubes, compare the results with those from standard Whitened Matched Filter (WMF) techniques. Since the variability in shape of gaseous plumes precludes the use of spatial conformation in the matched filtering, the 3DFFTMF results were similar to those of two other WMF methods. Including a spatial low-pass filter within the Fourier spacemore » can improve signal to noise ratios and therefore improve detection limit by facilitating the mitigation of high frequency clutter. The improvement only occurs if the low-pass filter diameter is smaller than the plume diameter.« less

Techniques for noise removal and registration of TIMS data

USGS Publications Warehouse

Hummer-Miller, S.

1990-01-01

Extracting subtle differences from highly correlated thermal infrared aircraft data is possible with appropriate noise filters, constructed and applied in the spatial frequency domain. This paper discusses a heuristic approach to designing noise filters for removing high- and low-spatial frequency striping and banding. Techniques for registering thermal infrared aircraft data to a topographic base using Thematic Mapper data are presented. The noise removal and registration techniques are applied to TIMS thermal infrared aircraft data. -Author

Subband Approach to Bandlimited Crosstalk Cancellation System in Spatial Sound Reproduction

NASA Astrophysics Data System (ADS)

Bai, Mingsian R.; Lee, Chih-Chung

2006-12-01

Crosstalk cancellation system (CCS) plays a vital role in spatial sound reproduction using multichannel loudspeakers. However, this technique is still not of full-blown use in practical applications due to heavy computation loading. To reduce the computation loading, a bandlimited CCS is presented in this paper on the basis of subband filtering approach. A pseudoquadrature mirror filter (QMF) bank is employed in the implementation of CCS filters which are bandlimited to 6 kHz, where human's localization is the most sensitive. In addition, a frequency-dependent regularization scheme is adopted in designing the CCS inverse filters. To justify the proposed system, subjective listening experiments were undertaken in an anechoic room. The experiments include two parts: the source localization test and the sound quality test. Analysis of variance (ANOVA) is applied to process the data and assess statistical significance of subjective experiments. The results indicate that the bandlimited CCS performed comparably well as the fullband CCS, whereas the computation loading was reduced by approximately eighty percent.

Matched-filtering generalized phase contrast using LCoS pico-projectors for beam-forming.

PubMed

Bañas, Andrew; Palima, Darwin; Glückstad, Jesper

2012-04-23

We report on a new beam-forming system for generating high intensity programmable optical spikes using so-called matched-filtering Generalized Phase Contrast (mGPC) applying two consumer handheld pico-projectors. Such a system presents a low-cost alternative for optical trapping and manipulation, optical lattices and other beam-shaping applications usually implemented with high-end spatial light modulators. Portable pico-projectors based on liquid crystal on silicon (LCoS) devices are used as binary phase-only spatial light modulators by carefully setting the appropriate polarization of the laser illumination. The devices are subsequently placed into the object and Fourier plane of a standard 4f-setup according to the mGPC spatial filtering configuration. Having a reconfigurable spatial phase filter, instead of a fixed and fabricated one, allows the beam shaper to adapt to different input phase patterns suited for different requirements. Despite imperfections in these consumer pico-projectors, the mGPC approach tolerates phase aberrations that would have otherwise been hard to overcome by standard phase projection. © 2012 Optical Society of America

Characteristics and performance of a two-lens slit spatial filter for high power lasers

NASA Astrophysics Data System (ADS)

Xiong, Han; Gao, Fan; Zhang, Xiang; Zhuang, Zhenwu; Zhao, Jianjun; Yuan, Xiao

2017-05-01

The characteristics of a two-lens slit spatial filtering system on image relay and spatial filtering are discussed with detailed theoretical calculation and numerical simulation. The slit spatial filter can be used as the cavity spatial filter in large laser systems, such as National Ignition Facility, which can significantly decrease the focal intensity in cavity spatial filter and suppress or even avoid the pinhole (slit) closure while keeping the output power and beam quality. Additionally, the overall length of the cavity spatial filter can be greatly reduced with the use of the two-lens slit spatial filter.

An innovations approach to decoupling of multibody dynamics and control

NASA Technical Reports Server (NTRS)

Rodriguez, G.

1989-01-01

The problem of hinged multibody dynamics is solved using an extension of the innovations approach of linear filtering and prediction theory to the problem of mechanical system modeling and control. This approach has been used quite effectively to diagonalize the equations for filtering and prediction for linear state space systems. It has similar advantages in the study of dynamics and control of multibody systems. The innovations approach advanced here consists of expressing the equations of motion in terms of two closely related processes: (1) the innovations process e, a sequence of moments, obtained from the applied moments T by means of a spatially recursive Kalman filter that goes from the tip of the manipulator to its base; (2) a residual process, a sequence of velocities, obtained from the joint-angle velocities by means of an outward smoothing operations. The innovations e and the applied moments T are related by means of the relationships e = (I - L)T and T = (I + K)e. The operation (I - L) is a causal lower triangular matrix which is generated by a spatially recursive Kalman filter and the corresponding discrete-step Riccati equation. Hence, the innovations and the applied moments can be obtained from each other by means of a causal operation which is itself casually invertible.

Spatial modeling in ecology: the flexibility of eigenfunction spatial analyses.

PubMed

Griffith, Daniel A; Peres-Neto, Pedro R

2006-10-01

Recently, analytical approaches based on the eigenfunctions of spatial configuration matrices have been proposed in order to consider explicitly spatial predictors. The present study demonstrates the usefulness of eigenfunctions in spatial modeling applied to ecological problems and shows equivalencies of and differences between the two current implementations of this methodology. The two approaches in this category are the distance-based (DB) eigenvector maps proposed by P. Legendre and his colleagues, and spatial filtering based upon geographic connectivity matrices (i.e., topology-based; CB) developed by D. A. Griffith and his colleagues. In both cases, the goal is to create spatial predictors that can be easily incorporated into conventional regression models. One important advantage of these two approaches over any other spatial approach is that they provide a flexible tool that allows the full range of general and generalized linear modeling theory to be applied to ecological and geographical problems in the presence of nonzero spatial autocorrelation.

Optical calculation of correlation filters for a robotic vision system

NASA Technical Reports Server (NTRS)

Knopp, Jerome

1989-01-01

A method is presented for designing optical correlation filters based on measuring three intensity patterns: the Fourier transform of a filter object, a reference wave and the interference pattern produced by the sum of the object transform and the reference. The method can produce a filter that is well matched to both the object, its transforming optical system and the spatial light modulator used in the correlator input plane. A computer simulation was presented to demonstrate the approach for the special case of a conventional binary phase-only filter. The simulation produced a workable filter with a sharp correlation peak.

Computational Approaches to Spatial Orientation: From Transfer Functions to Dynamic Bayesian Inference

PubMed Central

MacNeilage, Paul R.; Ganesan, Narayan; Angelaki, Dora E.

2008-01-01

Spatial orientation is the sense of body orientation and self-motion relative to the stationary environment, fundamental to normal waking behavior and control of everyday motor actions including eye movements, postural control, and locomotion. The brain achieves spatial orientation by integrating visual, vestibular, and somatosensory signals. Over the past years, considerable progress has been made toward understanding how these signals are processed by the brain using multiple computational approaches that include frequency domain analysis, the concept of internal models, observer theory, Bayesian theory, and Kalman filtering. Here we put these approaches in context by examining the specific questions that can be addressed by each technique and some of the scientific insights that have resulted. We conclude with a recent application of particle filtering, a probabilistic simulation technique that aims to generate the most likely state estimates by incorporating internal models of sensor dynamics and physical laws and noise associated with sensory processing as well as prior knowledge or experience. In this framework, priors for low angular velocity and linear acceleration can explain the phenomena of velocity storage and frequency segregation, both of which have been modeled previously using arbitrary low-pass filtering. How Kalman and particle filters may be implemented by the brain is an emerging field. Unlike past neurophysiological research that has aimed to characterize mean responses of single neurons, investigations of dynamic Bayesian inference should attempt to characterize population activities that constitute probabilistic representations of sensory and prior information. PMID:18842952

Extending Correlation Filter-Based Visual Tracking by Tree-Structured Ensemble and Spatial Windowing.

PubMed

Gundogdu, Erhan; Ozkan, Huseyin; Alatan, A Aydin

2017-11-01

Correlation filters have been successfully used in visual tracking due to their modeling power and computational efficiency. However, the state-of-the-art correlation filter-based (CFB) tracking algorithms tend to quickly discard the previous poses of the target, since they consider only a single filter in their models. On the contrary, our approach is to register multiple CFB trackers for previous poses and exploit the registered knowledge when an appearance change occurs. To this end, we propose a novel tracking algorithm [of complexity O(D) ] based on a large ensemble of CFB trackers. The ensemble [of size O(2 D ) ] is organized over a binary tree (depth D ), and learns the target appearance subspaces such that each constituent tracker becomes an expert of a certain appearance. During tracking, the proposed algorithm combines only the appearance-aware relevant experts to produce boosted tracking decisions. Additionally, we propose a versatile spatial windowing technique to enhance the individual expert trackers. For this purpose, spatial windows are learned for target objects as well as the correlation filters and then the windowed regions are processed for more robust correlations. In our extensive experiments on benchmark datasets, we achieve a substantial performance increase by using the proposed tracking algorithm together with the spatial windowing.

Fast estimate of Hartley entropy in image sharpening

NASA Astrophysics Data System (ADS)

Krbcová, Zuzana; Kukal, Jaromír.; Svihlik, Jan; Fliegel, Karel

2016-09-01

Two classes of linear IIR filters: Laplacian of Gaussian (LoG) and Difference of Gaussians (DoG) are frequently used as high pass filters for contextual vision and edge detection. They are also used for image sharpening when linearly combined with the original image. Resulting sharpening filters are radially symmetric in spatial and frequency domains. Our approach is based on the radial approximation of unknown optimal filter, which is designed as a weighted sum of Gaussian filters with various radii. The novel filter is designed for MRI image enhancement where the image intensity represents anatomical structure plus additive noise. We prefer the gradient norm of Hartley entropy of whole image intensity as a measure which has to be maximized for the best sharpening. The entropy estimation procedure is as fast as FFT included in the filter but this estimate is a continuous function of enhanced image intensities. Physically motivated heuristic is used for optimum sharpening filter design by its parameter tuning. Our approach is compared with Wiener filter on MRI images.

Adaptive Laplacian filtering for sensorimotor rhythm-based brain-computer interfaces

NASA Astrophysics Data System (ADS)

Lu, Jun; McFarland, Dennis J.; Wolpaw, Jonathan R.

2013-02-01

Objective. Sensorimotor rhythms (SMRs) are 8-30 Hz oscillations in the electroencephalogram (EEG) recorded from the scalp over sensorimotor cortex that change with movement and/or movement imagery. Many brain-computer interface (BCI) studies have shown that people can learn to control SMR amplitudes and can use that control to move cursors and other objects in one, two or three dimensions. At the same time, if SMR-based BCIs are to be useful for people with neuromuscular disabilities, their accuracy and reliability must be improved substantially. These BCIs often use spatial filtering methods such as common average reference (CAR), Laplacian (LAP) filter or common spatial pattern (CSP) filter to enhance the signal-to-noise ratio of EEG. Here, we test the hypothesis that a new filter design, called an ‘adaptive Laplacian (ALAP) filter’, can provide better performance for SMR-based BCIs. Approach. An ALAP filter employs a Gaussian kernel to construct a smooth spatial gradient of channel weights and then simultaneously seeks the optimal kernel radius of this spatial filter and the regularization parameter of linear ridge regression. This optimization is based on minimizing the leave-one-out cross-validation error through a gradient descent method and is computationally feasible. Main results. Using a variety of kinds of BCI data from a total of 22 individuals, we compare the performances of ALAP filter to CAR, small LAP, large LAP and CSP filters. With a large number of channels and limited data, ALAP performs significantly better than CSP, CAR, small LAP and large LAP both in classification accuracy and in mean-squared error. Using fewer channels restricted to motor areas, ALAP is still superior to CAR, small LAP and large LAP, but equally matched to CSP. Significance. Thus, ALAP may help to improve the accuracy and robustness of SMR-based BCIs.

Spatial arrangement of color filter array for multispectral image acquisition

NASA Astrophysics Data System (ADS)

Shrestha, Raju; Hardeberg, Jon Y.; Khan, Rahat

2011-03-01

In the past few years there has been a significant volume of research work carried out in the field of multispectral image acquisition. The focus of most of these has been to facilitate a type of multispectral image acquisition systems that usually requires multiple subsequent shots (e.g. systems based on filter wheels, liquid crystal tunable filters, or active lighting). Recently, an alternative approach for one-shot multispectral image acquisition has been proposed; based on an extension of the color filter array (CFA) standard to produce more than three channels. We can thus introduce the concept of multispectral color filter array (MCFA). But this field has not been much explored, particularly little focus has been given in developing systems which focuses on the reconstruction of scene spectral reflectance. In this paper, we have explored how the spatial arrangement of multispectral color filter array affects the acquisition accuracy with the construction of MCFAs of different sizes. We have simulated acquisitions of several spectral scenes using different number of filters/channels, and compared the results with those obtained by the conventional regular MCFA arrangement, evaluating the precision of the reconstructed scene spectral reflectance in terms of spectral RMS error, and colorimetric ▵E*ab color differences. It has been found that the precision and the the quality of the reconstructed images are significantly influenced by the spatial arrangement of the MCFA and the effect will be more and more prominent with the increase in the number of channels. We believe that MCFA-based systems can be a viable alternative for affordable acquisition of multispectral color images, in particular for applications where spatial resolution can be traded off for spectral resolution. We have shown that the spatial arrangement of the array is an important design issue.

Complementary theta resonance filtering by two spatially segregated mechanisms in CA1 hippocampal pyramidal neurons.

PubMed

Hu, Hua; Vervaeke, Koen; Graham, Lyle J; Storm, Johan F

2009-11-18

Synaptic input to a neuron may undergo various filtering steps, both locally and during transmission to the soma. Using simultaneous whole-cell recordings from soma and apical dendrites from rat CA1 hippocampal pyramidal cells, and biophysically detailed modeling, we found two complementary resonance (bandpass) filters of subthreshold voltage signals. Both filters favor signals in the theta (3-12 Hz) frequency range, but have opposite location, direction, and voltage dependencies: (1) dendritic H-resonance, caused by h/HCN-channels, filters signals propagating from soma to dendrite when the membrane potential is close to rest; and (2) somatic M-resonance, caused by M/Kv7/KCNQ and persistent Na(+) (NaP) channels, filters signals propagating from dendrite to soma when the membrane potential approaches spike threshold. Hippocampal pyramidal cells participate in theta network oscillations during behavior, and we suggest that that these dual, polarized theta resonance mechanisms may convey voltage-dependent tuning of theta-mediated neural coding in the entorhinal/hippocampal system during locomotion, spatial navigation, memory, and sleep.

Altering spatial priority maps via statistical learning of target selection and distractor filtering.

PubMed

Ferrante, Oscar; Patacca, Alessia; Di Caro, Valeria; Della Libera, Chiara; Santandrea, Elisa; Chelazzi, Leonardo

2018-05-01

The cognitive system has the capacity to learn and make use of environmental regularities - known as statistical learning (SL), including for the implicit guidance of attention. For instance, it is known that attentional selection is biased according to the spatial probability of targets; similarly, changes in distractor filtering can be triggered by the unequal spatial distribution of distractors. Open questions remain regarding the cognitive/neuronal mechanisms underlying SL of target selection and distractor filtering. Crucially, it is unclear whether the two processes rely on shared neuronal machinery, with unavoidable cross-talk, or they are fully independent, an issue that we directly addressed here. In a series of visual search experiments, participants had to discriminate a target stimulus, while ignoring a task-irrelevant salient distractor (when present). We systematically manipulated spatial probabilities of either one or the other stimulus, or both. We then measured performance to evaluate the direct effects of the applied contingent probability distribution (e.g., effects on target selection of the spatial imbalance in target occurrence across locations) as well as its indirect or "transfer" effects (e.g., effects of the same spatial imbalance on distractor filtering across locations). By this approach, we confirmed that SL of both target and distractor location implicitly bias attention. Most importantly, we described substantial indirect effects, with the unequal spatial probability of the target affecting filtering efficiency and, vice versa, the unequal spatial probability of the distractor affecting target selection efficiency across locations. The observed cross-talk demonstrates that SL of target selection and distractor filtering are instantiated via (at least partly) shared neuronal machinery, as further corroborated by strong correlations between direct and indirect effects at the level of individual participants. Our findings are compatible with the notion that both kinds of SL adjust the priority of specific locations within attentional priority maps of space. Copyright © 2017 Elsevier Ltd. All rights reserved.

Similar Processes but Different Environmental Filters for Soil Bacterial and Fungal Community Composition Turnover on a Broad Spatial Scale

PubMed Central

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P. A.; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

PubMed

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

New estimation architecture for multisensor data fusion

NASA Astrophysics Data System (ADS)

Covino, Joseph M.; Griffiths, Barry E.

1991-07-01

This paper describes a novel method of hierarchical asynchronous distributed filtering called the Net Information Approach (NIA). The NIA is a Kalman-filter-based estimation scheme for spatially distributed sensors which must retain their local optimality yet require a nearly optimal global estimate. The key idea of the NIA is that each local sensor-dedicated filter tells the global filter 'what I've learned since the last local-to-global transmission,' whereas in other estimation architectures the local-to-global transmission consists of 'what I think now.' An algorithm based on this idea has been demonstrated on a small-scale target-tracking problem with many encouraging results. Feasibility of this approach was demonstrated by comparing NIA performance to an optimal centralized Kalman filter (lower bound) via Monte Carlo simulations.

Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York

PubMed Central

Goovaerts, Pierre; Jacquez, Geoffrey M

2004-01-01

Background Complete Spatial Randomness (CSR) is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial pattern is present. This paper presents a geostatistical approach to filter the noise caused by spatially varying population size and to generate spatially correlated neutral models that account for regional background obtained by geostatistical smoothing of observed mortality rates. These neutral models were used in conjunction with the local Moran statistics to identify spatial clusters and outliers in the geographical distribution of male and female lung cancer in Nassau, Queens, and Suffolk counties, New York, USA. Results We developed a typology of neutral models that progressively relaxes the assumptions of null hypotheses, allowing for the presence of spatial autocorrelation, non-uniform risk, and incorporation of spatially heterogeneous population sizes. Incorporation of spatial autocorrelation led to fewer significant ZIP codes than found in previous studies, confirming earlier claims that CSR can lead to over-identification of the number of significant spatial clusters or outliers. Accounting for population size through geostatistical filtering increased the size of clusters while removing most of the spatial outliers. Integration of regional background into the neutral models yielded substantially different spatial clusters and outliers, leading to the identification of ZIP codes where SMR values significantly depart from their regional background. Conclusion The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the background variation extant in real-world systems. In particular, this new methodology allows one to identify geographic pattern above and beyond background variation. The implementation of this approach in spatial statistical software will facilitate the detection of spatial disparities in mortality rates, establishing the rationale for targeted cancer control interventions, including consideration of health services needs, and resource allocation for screening and diagnostic testing. It will allow researchers to systematically evaluate how sensitive their results are to assumptions implicit under alternative null hypotheses. PMID:15272930

Asymmetric 2D spatial beam filtering by photonic crystals

NASA Astrophysics Data System (ADS)

Gailevicius, D.; Purlys, V.; Maigyte, L.; Gaizauskas, E.; Peckus, M.; Gadonas, R.; Staliunas, K.

2016-04-01

Spatial filtering techniques are important for improving the spatial quality of light beams. Photonic crystals (PhCs) with a selective spatial (angular) transmittance can also provide spatial filtering with the added benefit transversal symmetries, submillimeter dimensions and monolithic integration in other devices, such as micro-lasers or semiconductor lasers. Workable bandgap PhC configurations require a modulated refractive index with period lengths that are approximately less than the wavelength of radiation. This imposes technical limitations, whereby the available direct laser write (DLW) fabrication techniques are limited in resolution and refractive index depth. If, however, a deflection mechanism is chosen instead, a functional filter PhC can be produced that is operational in the visible wavelength regime. For deflection based PhCs glass is an attractive choice as it is highly stable medium. 2D and 3D PhC filter variations have already been produced on soda-lime glass. However, little is known about how to control the scattering of PhCs when approaching the smallest period values. Here we look into the internal structure of the initially symmetric geometry 2D PhCs and associating it with the resulting transmittance spectra. By varying the DLW fabrication beam parameters and scanning algorithms, we show that such PhCs contain layers that are comprised of semi-tilted structure voxels. We show the appearance of asymmetry can be compensated in order to circumvent some negative effects at the cost of potentially maximum scattering efficiency.

SU-F-J-189: A Method to Improve the Spatial Resolution of Prompt Gamma Based Compton Imaging for Proton Range Verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Draeger, E; Chen, H; Polf, J

Purpose: To test two new techniques, the distance-of-closest approach (DCA) and Compton line (CL) filters, developed as a means of improving the spatial resolution of Compton camera (CC) imaging. Methods: Gammas emitted from {sup 22}Na, {sup 137}Cs, and {sup 60}Co point sources were measured with a prototype 3-stage CC. The energy deposited and position of each interaction in each stage were recorded and used to calculate a “cone-of-origin” for each gamma that scattered twice in the CC. A DCA filter was developed which finds the shortest distance from the gamma’s cone-of-origin surface to the location of the gamma source. Themore » DCA filter was applied to the data to determine the initial energy of the gamma and to remove “bad” interactions that only contribute noise to the image. Additionally, a CL filter, which removes gamma events that do not follow the theoretical predictions of the Compton scatter equation, was used to further remove “bad” interactions from the measured data. Then images were reconstructed with raw, unfiltered data, DCA filtered data, and DCA+CL filtered data and the achievable image resolution of each dataset was compared. Results: Spatial resolutions of ∼2 mm, and better than 2 mm, were achievable with the DCA and DCA+CL filtered data, respectively, compared to > 5 mm for the raw, unfiltered data. Conclusion: In many special cases in medical imaging where information about the source position may be known, such as proton radiotherapy range verification, the application of the DCA and CL filters can result in considerable improvements in the achievable spatial resolutions of Compton imaging.« less

Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

PubMed Central

Villa-Parra, Ana Cecilia; Bastos-Filho, Teodiano; López-Delis, Alberto; Frizera-Neto, Anselmo; Krishnan, Sridhar

2017-01-01

This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG) signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC) between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs) based on Canonical Correlation Analysis (CCA) to recognize 40 targets of steady-state visual evoked potential (SSVEP), providing an accuracy (ACC) of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly (p<0.01) improved for most of the subjects (ACC≥74.79%), when compared with other BCIs based on Common Spatial Pattern, Filter Bank-Common Spatial Pattern, and Riemannian Geometry. PMID:29186848

Self-aligned spatial filtering using laser optical tweezers.

PubMed

Birkbeck, Aaron L; Zlatanovic, Sanja; Esener, Sadik C

2006-09-01

We present an optical spatial filtering device that has been integrated into a microfluidic system and whose motion and alignment is controlled using a laser optical tweezer. The lithographically patterned micro-optical spatial filter device filters out higher frequency additive noise components by automatically aligning itself in three dimensions to the focus of the laser beam. This self-alignment capability is achieved through the attachment of a refractive optical element directly over the circular aperture or pinhole of the spatial filter. A discussion of two different spatial filter designs is presented along with experimental results that demonstrate the effectiveness of the self-aligned micro-optic spatial filter.

The Filtered Abel Transform and Its Application in Combustion Diagnostics

NASA Technical Reports Server (NTRS)

Simons, Stephen N. (Technical Monitor); Yuan, Zeng-Guang

2003-01-01

Many non-intrusive combustion diagnosis methods generate line-of-sight projections of a flame field. To reconstruct the spatial field of the measured properties, these projections need to be deconvoluted. When the spatial field is axisymmetric, commonly used deconvolution method include the Abel transforms, the onion peeling method and the two-dimensional Fourier transform method and its derivatives such as the filtered back projection methods. This paper proposes a new approach for performing the Abel transform method is developed, which possesses the exactness of the Abel transform and the flexibility of incorporating various filters in the reconstruction process. The Abel transform is an exact method and the simplest among these commonly used methods. It is evinced in this paper that all the exact reconstruction methods for axisymmetric distributions must be equivalent to the Abel transform because of its uniqueness and exactness. Detailed proof is presented to show that the two dimensional Fourier methods when applied to axisymmetric cases is identical to the Abel transform. Discrepancies among various reconstruction method stem from the different approximations made to perform numerical calculations. An equation relating the spectrum of a set of projection date to that of the corresponding spatial distribution is obtained, which shows that the spectrum of the projection is equal to the Abel transform of the spectrum of the corresponding spatial distribution. From the equation, if either the projection or the distribution is bandwidth limited, the other is also bandwidth limited, and both have the same bandwidth. If the two are not bandwidth limited, the Abel transform has a bias against low wave number components in most practical cases. This explains why the Abel transform and all exact deconvolution methods are sensitive to high wave number noises. The filtered Abel transform is based on the fact that the Abel transform of filtered projection data is equal to an integral transform of the original projection data with the kernel function being the Abel transform of the filtering function. The kernel function is independent of the projection data and can be obtained separately when the filtering function is selected. Users can select the best filtering function for a particular set of experimental data. When the kernal function is obtained, it can be used repeatedly to a number of projection data sets (rovs) from the same experiment. When an entire flame image that contains a large number of projection lines needs to be processed, the new approach significantly reduces computational effort in comparison with the conventional approach in which each projection data set is deconvoluted separately. Computer codes have been developed to perform the filter Abel transform for an entire flame field. Measured soot volume fraction data of a jet diffusion flame are processed as an example.

Destriping of Landsat MSS images by filtering techniques

USGS Publications Warehouse

Pan, Jeng-Jong; Chang, Chein-I

1992-01-01

: The removal of striping noise encountered in the Landsat Multispectral Scanner (MSS) images can be generally done by using frequency filtering techniques. Frequency do~ain filteri~g has, how~ver, se,:era~ prob~ems~ such as storage limitation of data required for fast Fourier transforms, nngmg artl~acts appe~nng at hlgh-mt,enslty.dlscontinuities, and edge effects between adjacent filtered data sets. One way for clrcu~,,:entmg the above difficulties IS, to design a spatial filter to convolve with the images. Because it is known that the,stnpmg a.lways appears at frequencies of 1/6, 1/3, and 1/2 cycles per line, it is possible to design a simple one-dimensIOnal spat~a~ fll,ter to take advantage of this a priori knowledge to cope with the above problems. The desired filter is the type of ~mlte Impuls~ response which can be designed by a linear programming and Remez's exchange algorithm coupled ~lth an adaptIve tec,hmque. In addition, a four-step spatial filtering technique with an appropriate adaptive approach IS also presented which may be particularly useful for geometrically rectified MSS images.

Low Dissipative High Order Shock-Capturing Methods Using Characteristic-Based Filters

NASA Technical Reports Server (NTRS)

Yee, H. C.; Sandham, N. D.; Djomehri, M. J.

1998-01-01

An approach which closely maintains the non-dissipative nature of classical fourth or higher- order spatial differencing away from shock waves and steep gradient regions while being capable of accurately capturing discontinuities, steep gradient and fine scale turbulent structures in a stable and efficient manner is described. The approach is a generalization of the method of Gustafsson and Oisson and the artificial compression method (ACM) of Harten. Spatially non-dissipative fourth or higher-order compact and non-compact spatial differencings are used as the base schemes. Instead of applying a scalar filter as in Gustafsson and Olsson, an ACM like term is used to signal the appropriate amount of second or third-order TVD or ENO types of characteristic based numerical dissipation. This term acts as a characteristic filter to minimize numerical dissipation for the overall scheme. For time-accurate computations, time discretizations with low dissipation are used. Numerical experiments on 2-D vortical flows, vortex-shock interactions and compressible spatially and temporally evolving mixing layers showed that the proposed schemes have the desired property with only a 10% increase in operations count over standard second-order TVD schemes. Aside from the ability to accurately capture shock-turbulence interaction flows, this approach is also capable of accurately preserving vortex convection. Higher accuracy is achieved with fewer grid points when compared to that of standard second-order TVD or ENO schemes. To demonstrate the applicability of these schemes in sustaining turbulence where shock waves are absent, a simulation of 3-D compressible turbulent channel flow in a small domain is conducted.

Low Dissipative High Order Shock-Capturing Methods using Characteristic-Based Filters

NASA Technical Reports Server (NTRS)

Yee, H. C.; Sandham, N. D.; Djomehri, M. J.

1998-01-01

An approach which closely maintains the non-dissipative nature of classical fourth or higher- order spatial differencing away from shock waves and steep gradient regions while being capable of accurately capturing discontinuities, steep gradient and fine scale turbulent structures in a stable and efficient manner is described. The approach is a generalization of the method of Gustafsson and Olsson and the artificial compression method (ACM) of Harten. Spatially non-dissipative fourth or higher-order compact and non-compact spatial differencings are used as the base schemes. Instead of applying a scalar filter as in Gustafsson and Olsson, an ACM like term is used to signal the appropriate amount of second or third-order TVD or ENO types of characteristic based numerical dissipation. This term acts as a characteristic filter to minimize numerical dissipation for the overall scheme. For time-accurate computations, time discretizations with low dissipation are used. Numerical experiments on 2-D vortical flows, vortex-shock interactions and compressible spatially and temporally evolving mixing layers showed that the proposed schemes have the desired property with only a 10% increase in operations count over standard second-order TVD schemes. Aside from the ability to accurately capture shock-turbulence interaction flows, this approach is also capable of accurately preserving vortex convection. Higher accuracy is achieved with fewer grid points when compared to that of standard second-order TVD or ENO schemes. To demonstrate the applicability of these schemes in sustaining turbulence where shock waves are absent, a simulation of 3-D compressible turbulent channel flow in a small domain is conducted.

Detecting single-trial EEG evoked potential using a wavelet domain linear mixed model: application to error potentials classification.

PubMed

Spinnato, J; Roubaud, M-C; Burle, B; Torrésani, B

2015-06-01

The main goal of this work is to develop a model for multisensor signals, such as magnetoencephalography or electroencephalography (EEG) signals that account for inter-trial variability, suitable for corresponding binary classification problems. An important constraint is that the model be simple enough to handle small size and unbalanced datasets, as often encountered in BCI-type experiments. The method involves the linear mixed effects statistical model, wavelet transform, and spatial filtering, and aims at the characterization of localized discriminant features in multisensor signals. After discrete wavelet transform and spatial filtering, a projection onto the relevant wavelet and spatial channels subspaces is used for dimension reduction. The projected signals are then decomposed as the sum of a signal of interest (i.e., discriminant) and background noise, using a very simple Gaussian linear mixed model. Thanks to the simplicity of the model, the corresponding parameter estimation problem is simplified. Robust estimates of class-covariance matrices are obtained from small sample sizes and an effective Bayes plug-in classifier is derived. The approach is applied to the detection of error potentials in multichannel EEG data in a very unbalanced situation (detection of rare events). Classification results prove the relevance of the proposed approach in such a context. The combination of the linear mixed model, wavelet transform and spatial filtering for EEG classification is, to the best of our knowledge, an original approach, which is proven to be effective. This paper improves upon earlier results on similar problems, and the three main ingredients all play an important role.

A wavelet and least square filter based spatial-spectral denoising approach of hyperspectral imagery

NASA Astrophysics Data System (ADS)

Li, Ting; Chen, Xiao-Mei; Chen, Gang; Xue, Bo; Ni, Guo-Qiang

2009-11-01

Noise reduction is a crucial step in hyperspectral imagery pre-processing. Based on sensor characteristics, the noise of hyperspectral imagery represents in both spatial and spectral domain. However, most prevailing denosing techniques process the imagery in only one specific domain, which have not utilized multi-domain nature of hyperspectral imagery. In this paper, a new spatial-spectral noise reduction algorithm is proposed, which is based on wavelet analysis and least squares filtering techniques. First, in the spatial domain, a new stationary wavelet shrinking algorithm with improved threshold function is utilized to adjust the noise level band-by-band. This new algorithm uses BayesShrink for threshold estimation, and amends the traditional soft-threshold function by adding shape tuning parameters. Comparing with soft or hard threshold function, the improved one, which is first-order derivable and has a smooth transitional region between noise and signal, could save more details of image edge and weaken Pseudo-Gibbs. Then, in the spectral domain, cubic Savitzky-Golay filter based on least squares method is used to remove spectral noise and artificial noise that may have been introduced in during the spatial denoising. Appropriately selecting the filter window width according to prior knowledge, this algorithm has effective performance in smoothing the spectral curve. The performance of the new algorithm is experimented on a set of Hyperion imageries acquired in 2007. The result shows that the new spatial-spectral denoising algorithm provides more significant signal-to-noise-ratio improvement than traditional spatial or spectral method, while saves the local spectral absorption features better.

Multiple Spatial Frequencies Pyramid WaveFront Sensing

NASA Astrophysics Data System (ADS)

Ragazzoni, Roberto; Vassallo, Daniele; Dima, Marco; Portaluri, Elisa; Bergomi, Maria; Greggio, Davide; Viotto, Valentina; Gullieuszik, Marco; Biondi, Federico; Carolo, Elena; Chinellato, Simonetta; Farinato, Jacopo; Magrin, Demetrio; Marafatto, Luca

2017-11-01

A modification of the pyramid wavefront sensor is described. In this conceptually new class of devices, the perturbations are split at the level of the focal plane depending upon their spatial frequencies, and then measured separately. The aim of this approach is to increase the accuracy in the determination of some range of spatial frequency perturbations, or a certain classes of modes, disentangling them from the noise associated to the Poissonian fluctuations of the light coming from the perturbations outside of the range of interest or from the background in the pupil planes; the latter case specifically when the pyramid wavefront sensor is used with a large modulation. While the limits and the effectiveness of this approach should be further investigated, a number of variations on the concept are shown, including a generalization of the spatial filtering in the point-diffraction wavefront sensor. The simplest application, a generalization to the pyramid of the well-known spatially filtering in wavefront sensing, is showing promise as a significant limiting magnitude advance. Applications are further speculated in the area of extreme adaptive optics and when serving spectroscopic instrumentation where “light in the bucket” rather than Strehl performance is required.

Improved photo response non-uniformity (PRNU) based source camera identification.

PubMed

Cooper, Alan J

2013-03-10

The concept of using Photo Response Non-Uniformity (PRNU) as a reliable forensic tool to match an image to a source camera is now well established. Traditionally, the PRNU estimation methodologies have centred on a wavelet based de-noising approach. Resultant filtering artefacts in combination with image and JPEG contamination act to reduce the quality of PRNU estimation. In this paper, it is argued that the application calls for a simplified filtering strategy which at its base level may be realised using a combination of adaptive and median filtering applied in the spatial domain. The proposed filtering method is interlinked with a further two stage enhancement strategy where only pixels in the image having high probabilities of significant PRNU bias are retained. This methodology significantly improves the discrimination between matching and non-matching image data sets over that of the common wavelet filtering approach. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

A Unified Fisher's Ratio Learning Method for Spatial Filter Optimization.

PubMed

Li, Xinyang; Guan, Cuntai; Zhang, Haihong; Ang, Kai Keng

To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.

Resolution improvement in positron emission tomography using anatomical Magnetic Resonance Imaging.

PubMed

Chu, Yong; Su, Min-Ying; Mandelkern, Mark; Nalcioglu, Orhan

2006-08-01

An ideal imaging system should provide information with high-sensitivity, high spatial, and temporal resolution. Unfortunately, it is not possible to satisfy all of these desired features in a single modality. In this paper, we discuss methods to improve the spatial resolution in positron emission imaging (PET) using a priori information from Magnetic Resonance Imaging (MRI). Our approach uses an image restoration algorithm based on the maximization of mutual information (MMI), which has found significant success for optimizing multimodal image registration. The MMI criterion is used to estimate the parameters in the Sharpness-Constrained Wiener filter. The generated filter is then applied to restore PET images of a realistic digital brain phantom. The resulting restored images show improved resolution and better signal-to-noise ratio compared to the interpolated PET images. We conclude that a Sharpness-Constrained Wiener filter having parameters optimized from a MMI criterion may be useful for restoring spatial resolution in PET based on a priori information from correlated MRI.

Design of a composite filter realizable on practical spatial light modulators

NASA Technical Reports Server (NTRS)

Rajan, P. K.; Ramakrishnan, Ramachandran

1994-01-01

Hybrid optical correlator systems use two spatial light modulators (SLM's), one at the input plane and the other at the filter plane. Currently available SLM's such as the deformable mirror device (DMD) and liquid crystal television (LCTV) SLM's exhibit arbitrarily constrained operating characteristics. The pattern recognition filters designed with the assumption that the SLM's have ideal operating characteristic may not behave as expected when implemented on the DMD or LCTV SLM's. Therefore it is necessary to incorporate the SLM constraints in the design of the filters. In this report, an iterative method is developed for the design of an unconstrained minimum average correlation energy (MACE) filter. Then using this algorithm a new approach for the design of a SLM constrained distortion invariant filter in the presence of input SLM is developed. Two different optimization algorithms are used to maximize the objective function during filter synthesis, one based on the simplex method and the other based on the Hooke and Jeeves method. Also, the simulated annealing based filter design algorithm proposed by Khan and Rajan is refined and improved. The performance of the filter is evaluated in terms of its recognition/discrimination capabilities using computer simulations and the results are compared with a simulated annealing optimization based MACE filter. The filters are designed for different LCTV SLM's operating characteristics and the correlation responses are compared. The distortion tolerance and the false class image discrimination qualities of the filter are comparable to those of the simulated annealing based filter but the new filter design takes about 1/6 of the computer time taken by the simulated annealing filter design.

Ensemble Kalman filter inference of spatially-varying Manning's n coefficients in the coastal ocean

NASA Astrophysics Data System (ADS)

Siripatana, Adil; Mayo, Talea; Knio, Omar; Dawson, Clint; Maître, Olivier Le; Hoteit, Ibrahim

2018-07-01

Ensemble Kalman (EnKF) filtering is an established framework for large scale state estimation problems. EnKFs can also be used for state-parameter estimation, using the so-called "Joint-EnKF" approach. The idea is simply to augment the state vector with the parameters to be estimated and assign invariant dynamics for the time evolution of the parameters. In this contribution, we investigate the efficiency of the Joint-EnKF for estimating spatially-varying Manning's n coefficients used to define the bottom roughness in the Shallow Water Equations (SWEs) of a coastal ocean model. Observation System Simulation Experiments (OSSEs) are conducted using the ADvanced CIRCulation (ADCIRC) model, which solves a modified form of the Shallow Water Equations. A deterministic EnKF, the Singular Evolutive Interpolated Kalman (SEIK) filter, is used to estimate a vector of Manning's n coefficients defined at the model nodal points by assimilating synthetic water elevation data. It is found that with reasonable ensemble size (O (10)) , the filter's estimate converges to the reference Manning's field. To enhance performance, we have further reduced the dimension of the parameter search space through a Karhunen-Loéve (KL) expansion. We have also iterated on the filter update step to better account for the nonlinearity of the parameter estimation problem. We study the sensitivity of the system to the ensemble size, localization scale, dimension of retained KL modes, and number of iterations. The performance of the proposed framework in term of estimation accuracy suggests that a well-tuned Joint-EnKF provides a promising robust approach to infer spatially varying seabed roughness parameters in the context of coastal ocean modeling.

Assessing Habitat Suitability at Multiple Scales: A Landscape-Level Approach

Treesearch

Kurt H. Riitters; R.V. O' Neill; K.B. Jones

1997-01-01

The distribution and abundance of many plants and animals are influenced by the spatial arrangement of suitable habitats across landscapes. We derived habitat maps from a digital land cover map of the ~178,000 km2 Chesapeake Bay Watershed by using a spatial filtering algorithm. The regional amounts and patterns of habitats were different for...

Towards accurate localization: long- and short-term correlation filters for tracking

NASA Astrophysics Data System (ADS)

Li, Minglangjun; Tian, Chunna

2018-04-01

Visual tracking is a challenging problem, especially using a single model. In this paper, we propose a discriminative correlation filter (DCF) based tracking approach that exploits both the long-term and short-term information of the target, named LSTDCF, to improve the tracking performance. In addition to a long-term filter learned through the whole sequence, a short-term filter is trained using only features extracted from most recent frames. The long-term filter tends to capture more semantics of the target as more frames are used for training. However, since the target may undergo large appearance changes, features extracted around the target in non-recent frames prevent the long-term filter from locating the target in the current frame accurately. In contrast, the short-term filter learns more spatial details of the target from recent frames but gets over-fitting easily. Thus the short-term filter is less robust to handle cluttered background and prone to drift. We take the advantage of both filters and fuse their response maps to make the final estimation. We evaluate our approach on a widely-used benchmark with 100 image sequences and achieve state-of-the-art results.

Spatial filtering velocimetry of objective speckles for measuring out-of-plane motion.

PubMed

Jakobsen, M L; Yura, H T; Hanson, S G

2012-03-20

This paper analyzes the dynamics of objective laser speckles as the distance between the object and the observation plane continuously changes. With the purpose of applying optical spatial filtering velocimetry to the speckle dynamics, in order to measure out-of-plane motion in real time, a rotational symmetric spatial filter is designed. The spatial filter converts the speckle dynamics into a photocurrent with a quasi-sinusoidal response to the out-of-plane motion. The spatial filter is here emulated with a CCD camera, and is tested on speckles arising from a real application. The analysis discusses the selectivity of the spatial filter, the nonlinear response between speckle motion and observation distance, and the influence of the distance-dependent speckle size. Experiments with the emulated filters illustrate performance and potential applications of the technology. © 2012 Optical Society of America

Robust Sensing of Approaching Vehicles Relying on Acoustic Cues

PubMed Central

Mizumachi, Mitsunori; Kaminuma, Atsunobu; Ono, Nobutaka; Ando, Shigeru

2014-01-01

The latest developments in automobile design have allowed them to be equipped with various sensing devices. Multiple sensors such as cameras and radar systems can be simultaneously used for active safety systems in order to overcome blind spots of individual sensors. This paper proposes a novel sensing technique for catching up and tracking an approaching vehicle relying on an acoustic cue. First, it is necessary to extract a robust spatial feature from noisy acoustical observations. In this paper, the spatio-temporal gradient method is employed for the feature extraction. Then, the spatial feature is filtered out through sequential state estimation. A particle filter is employed to cope with a highly non-linear problem. Feasibility of the proposed method has been confirmed with real acoustical observations, which are obtained by microphones outside a cruising vehicle. PMID:24887038

Separation of the global and local components in functional near-infrared spectroscopy signals using principal component spatial filtering

PubMed Central

Zhang, Xian; Noah, Jack Adam; Hirsch, Joy

2016-01-01

Abstract. Global systemic effects not specific to a task can be prominent in functional near-infrared spectroscopy (fNIRS) signals and the separation of task-specific fNIRS signals and global nonspecific effects is challenging due to waveform correlations. We describe a principal component spatial filter algorithm for separation of the global and local effects. The effectiveness of the approach is demonstrated using fNIRS signals acquired during a right finger-thumb tapping task where the response patterns are well established. Both the temporal waveforms and the spatial pattern consistencies between oxyhemoglobin and deoxyhemoglobin signals are significantly improved, consistent with the basic physiological basis of fNIRS signals and the expected pattern of activity associated with the task. PMID:26866047

Symmetric Phase Only Filtering for Improved DPIV Data Processing

NASA Technical Reports Server (NTRS)

Wernet, Mark P.

2006-01-01

The standard approach in Digital Particle Image Velocimetry (DPIV) data processing is to use Fast Fourier Transforms to obtain the cross-correlation of two single exposure subregions, where the location of the cross-correlation peak is representative of the most probable particle displacement across the subregion. This standard DPIV processing technique is analogous to Matched Spatial Filtering, a technique commonly used in optical correlators to perform the crosscorrelation operation. Phase only filtering is a well known variation of Matched Spatial Filtering, which when used to process DPIV image data yields correlation peaks which are narrower and up to an order of magnitude larger than those obtained using traditional DPIV processing. In addition to possessing desirable correlation plane features, phase only filters also provide superior performance in the presence of DC noise in the correlation subregion. When DPIV image subregions contaminated with surface flare light or high background noise levels are processed using phase only filters, the correlation peak pertaining only to the particle displacement is readily detected above any signal stemming from the DC objects. Tedious image masking or background image subtraction are not required. Both theoretical and experimental analyses of the signal-to-noise ratio performance of the filter functions are presented. In addition, a new Symmetric Phase Only Filtering (SPOF) technique, which is a variation on the traditional phase only filtering technique, is described and demonstrated. The SPOF technique exceeds the performance of the traditionally accepted phase only filtering techniques and is easily implemented in standard DPIV FFT based correlation processing with no significant computational performance penalty. An "Automatic" SPOF algorithm is presented which determines when the SPOF is able to provide better signal to noise results than traditional PIV processing. The SPOF based optical correlation processing approach is presented as a new paradigm for more robust cross-correlation processing of low signal-to-noise ratio DPIV image data."

Ballistic Imaging and Scattering Measurements for Diesel Spray Combustion: Optical Development and Phenomenological Studies

DTIC Science & Technology

2016-04-01

polystyrene spheres in a water suspension. The impact of spatial filtering , temporal filtering , and scattering path length on image resolution are...The impact of spatial filtering , temporal filtering , and scattering path length on image resolution are reported. The technique is demonstrated...cell filled with polystyrene spheres in a water suspension. The impact of spatial filtering , temporal filtering , and scattering path length on image

Eigenvector Spatial Filtering Regression Modeling of Ground PM2.5 Concentrations Using Remotely Sensed Data.

PubMed

Zhang, Jingyi; Li, Bin; Chen, Yumin; Chen, Meijie; Fang, Tao; Liu, Yongfeng

2018-06-11

This paper proposes a regression model using the Eigenvector Spatial Filtering (ESF) method to estimate ground PM 2.5 concentrations. Covariates are derived from remotely sensed data including aerosol optical depth, normal differential vegetation index, surface temperature, air pressure, relative humidity, height of planetary boundary layer and digital elevation model. In addition, cultural variables such as factory densities and road densities are also used in the model. With the Yangtze River Delta region as the study area, we constructed ESF-based Regression (ESFR) models at different time scales, using data for the period between December 2015 and November 2016. We found that the ESFR models effectively filtered spatial autocorrelation in the OLS residuals and resulted in increases in the goodness-of-fit metrics as well as reductions in residual standard errors and cross-validation errors, compared to the classic OLS models. The annual ESFR model explained 70% of the variability in PM 2.5 concentrations, 16.7% more than the non-spatial OLS model. With the ESFR models, we performed detail analyses on the spatial and temporal distributions of PM 2.5 concentrations in the study area. The model predictions are lower than ground observations but match the general trend. The experiment shows that ESFR provides a promising approach to PM 2.5 analysis and prediction.

Adaptive Numerical Dissipative Control in High Order Schemes for Multi-D Non-Ideal MHD

NASA Technical Reports Server (NTRS)

Yee, H. C.; Sjoegreen, B.

2004-01-01

The goal is to extend our adaptive numerical dissipation control in high order filter schemes and our new divergence-free methods for ideal MHD to non-ideal MHD that include viscosity and resistivity. The key idea consists of automatic detection of different flow features as distinct sensors to signal the appropriate type and amount of numerical dissipation/filter where needed and leave the rest of the region free of numerical dissipation contamination. These scheme-independent detectors are capable of distinguishing shocks/shears, flame sheets, turbulent fluctuations and spurious high-frequency oscillations. The detection algorithm is based on an artificial compression method (ACM) (for shocks/shears), and redundant multi-resolution wavelets (WAV) (for the above types of flow feature). These filter approaches also provide a natural and efficient way for the minimization of Div(B) numerical error. The filter scheme consists of spatially sixth order or higher non-dissipative spatial difference operators as the base scheme for the inviscid flux derivatives. If necessary, a small amount of high order linear dissipation is used to remove spurious high frequency oscillations. For example, an eighth-order centered linear dissipation (AD8) might be included in conjunction with a spatially sixth-order base scheme. The inviscid difference operator is applied twice for the viscous flux derivatives. After the completion of a full time step of the base scheme step, the solution is adaptively filtered by the product of a 'flow detector' and the 'nonlinear dissipative portion' of a high-resolution shock-capturing scheme. In addition, the scheme independent wavelet flow detector can be used in conjunction with spatially compact, spectral or spectral element type of base schemes. The ACM and wavelet filter schemes using the dissipative portion of a second-order shock-capturing scheme with sixth-order spatial central base scheme for both the inviscid and viscous MHD flux derivatives and a fourth-order Runge-Kutta method are denoted.

Spatial filtering with photonic crystals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maigyte, Lina; Staliunas, Kestutis; Institució Catalana de Recerca i Estudis Avançats

2015-03-15

Photonic crystals are well known for their celebrated photonic band-gaps—the forbidden frequency ranges, for which the light waves cannot propagate through the structure. The frequency (or chromatic) band-gaps of photonic crystals can be utilized for frequency filtering. In analogy to the chromatic band-gaps and the frequency filtering, the angular band-gaps and the angular (spatial) filtering are also possible in photonic crystals. In this article, we review the recent advances of the spatial filtering using the photonic crystals in different propagation regimes and for different geometries. We review the most evident configuration of filtering in Bragg regime (with the back-reflection—i.e., inmore » the configuration with band-gaps) as well as in Laue regime (with forward deflection—i.e., in the configuration without band-gaps). We explore the spatial filtering in crystals with different symmetries, including axisymmetric crystals; we discuss the role of chirping, i.e., the dependence of the longitudinal period along the structure. We also review the experimental techniques to fabricate the photonic crystals and numerical techniques to explore the spatial filtering. Finally, we discuss several implementations of such filters for intracavity spatial filtering.« less

Recursive mass matrix factorization and inversion: An operator approach to open- and closed-chain multibody dynamics

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Kreutz, K.

1988-01-01

This report advances a linear operator approach for analyzing the dynamics of systems of joint-connected rigid bodies.It is established that the mass matrix M for such a system can be factored as M=(I+H phi L)D(I+H phi L) sup T. This yields an immediate inversion M sup -1=(I-H psi L) sup T D sup -1 (I-H psi L), where H and phi are given by known link geometric parameters, and L, psi and D are obtained recursively by a spatial discrete-step Kalman filter and by the corresponding Riccati equation associated with this filter. The factors (I+H phi L) and (I-H psi L) are lower triangular matrices which are inverses of each other, and D is a diagonal matrix. This factorization and inversion of the mass matrix leads to recursive algortihms for forward dynamics based on spatially recursive filtering and smoothing. The primary motivation for advancing the operator approach is to provide a better means to formulate, analyze and understand spatial recursions in multibody dynamics. This is achieved because the linear operator notation allows manipulation of the equations of motion using a very high-level analytical framework (a spatial operator algebra) that is easy to understand and use. Detailed lower-level recursive algorithms can readily be obtained for inspection from the expressions involving spatial operators. The report consists of two main sections. In Part 1, the problem of serial chain manipulators is analyzed and solved. Extensions to a closed-chain system formed by multiple manipulators moving a common task object are contained in Part 2. To retain ease of exposition in the report, only these two types of multibody systems are considered. However, the same methods can be easily applied to arbitrary multibody systems formed by a collection of joint-connected regid bodies.

Virtual experiment of optical spatial filtering in Matlab environment

NASA Astrophysics Data System (ADS)

Ji, Yunjing; Wang, Chunyong; Song, Yang; Lai, Jiancheng; Wang, Qinghua; Qi, Jing; Shen, Zhonghua

2017-08-01

The principle of spatial filtering experiment has been introduced, and the computer simulation platform with graphical user interface (GUI) has been made out in Matlab environment. Using it various filtering processes for different input image or different filtering purpose will be completed accurately, and filtering effect can be observed clearly with adjusting experimental parameters. The physical nature of the optical spatial filtering can be showed vividly, and so experimental teaching effect will be promoted.

Functional strategies drive community assembly of stream fishes along environmental gradients and across spatial scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Troia, Matthew J.; Gido, Keith B.

Trade-offs among functional traits produce multi-trait strategies that shape species interactions with the environment and drive the assembly of local communities from regional species pools. Stream fish communities vary along stream size gradients and among hierarchically structured habitat patches, but little is known about how the dispersion of strategies varies along environmental gradients and across spatial scales. We used null models to quantify the dispersion of reproductive life history, feeding, and locomotion strategies in communities sampled at three spatial scales in a prairie stream network in Kansas, USA. Strategies were generally underdispersed at all spatial scales, corroborating the longstanding notionmore » of abiotic filtering in stream fish communities. We tested for variation in strategy dispersion along a gradient of stream size and between headwater streams draining different ecoregions. Reproductive life history strategies became increasingly underdispersed moving from downstream to upstream, suggesting that abiotic filtering is stronger in headwaters. This pattern was stronger among reaches compared to mesohabitats, supporting the premise that differences in hydrologic regime among reaches filter reproductive life history strategies. Feeding strategies became increasingly underdispersed moving from upstream to downstream, indicating that environmental filters associated with stream size affect the dispersion of feeding and reproductive life history in opposing ways. Weak differences in strategy dispersion were detected between ecoregions, suggesting that different abiotic filters or strategies drive community differences between ecoregions. Lastly, given the pervasiveness of multi-trait strategies in plant and animal communities, we conclude that the assessment of strategy dispersion offers a comprehensive approach for elucidating mechanisms of community assembly.« less

Fast global image smoothing based on weighted least squares.

PubMed

Min, Dongbo; Choi, Sunghwan; Lu, Jiangbo; Ham, Bumsub; Sohn, Kwanghoon; Do, Minh N

2014-12-01

This paper presents an efficient technique for performing a spatially inhomogeneous edge-preserving image smoothing, called fast global smoother. Focusing on sparse Laplacian matrices consisting of a data term and a prior term (typically defined using four or eight neighbors for 2D image), our approach efficiently solves such global objective functions. In particular, we approximate the solution of the memory-and computation-intensive large linear system, defined over a d-dimensional spatial domain, by solving a sequence of 1D subsystems. Our separable implementation enables applying a linear-time tridiagonal matrix algorithm to solve d three-point Laplacian matrices iteratively. Our approach combines the best of two paradigms, i.e., efficient edge-preserving filters and optimization-based smoothing. Our method has a comparable runtime to the fast edge-preserving filters, but its global optimization formulation overcomes many limitations of the local filtering approaches. Our method also achieves high-quality results as the state-of-the-art optimization-based techniques, but runs ∼10-30 times faster. Besides, considering the flexibility in defining an objective function, we further propose generalized fast algorithms that perform Lγ norm smoothing (0 < γ < 2) and support an aggregated (robust) data term for handling imprecise data constraints. We demonstrate the effectiveness and efficiency of our techniques in a range of image processing and computer graphics applications.

Correlation of Spatially Filtered Dynamic Speckles in Distance Measurement Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Semenov, Dmitry V.; Nippolainen, Ervin; Kamshilin, Alexei A.

2008-04-15

In this paper statistical properties of spatially filtered dynamic speckles are considered. This phenomenon was not sufficiently studied yet while spatial filtering is an important instrument for speckles velocity measurements. In case of spatial filtering speckle velocity information is derived from the modulation frequency of filtered light power which is measured by photodetector. Typical photodetector output is represented by a narrow-band random noise signal which includes non-informative intervals. Therefore more or less precious frequency measurement requires averaging. In its turn averaging implies uncorrelated samples. However, conducting research we found that correlation is typical property not only of dynamic speckle patternsmore » but also of spatially filtered speckles. Using spatial filtering the correlation is observed as a response of measurements provided to the same part of the object surface or in case of simultaneously using several adjacent photodetectors. Found correlations can not be explained using just properties of unfiltered dynamic speckles. As we demonstrate the subject of this paper is important not only from pure theoretical point but also from the point of applied speckle metrology. E.g. using single spatial filter and an array of photodetector can greatly improve accuracy of speckle velocity measurements.« less

Morphological operators for enhanced polarimetric image target detection

NASA Astrophysics Data System (ADS)

Romano, João. M.; Rosario, Dalton S.

2015-09-01

We introduce an algorithm based on morphological filters with the Stokes parameters that augments the daytime and nighttime detection of weak-signal manmade objects immersed in a predominant natural background scene. The approach features a tailored sequence of signal-enhancing filters, consisting of core morphological operators (dilation, erosion) and higher level morphological operations (e.g., spatial gradient, opening, closing) to achieve a desired overarching goal. Using representative data from the SPICE database, the results show that the approach was able to automatically and persistently detect with a high confidence level the presence of three mobile military howitzer surrogates (targets) in natural clutter.

A periodic spatio-spectral filter for event-related potentials.

PubMed

Ghaderi, Foad; Kim, Su Kyoung; Kirchner, Elsa Andrea

2016-12-01

With respect to single trial detection of event-related potentials (ERPs), spatial and spectral filters are two of the most commonly used pre-processing techniques for signal enhancement. Spatial filters reduce the dimensionality of the data while suppressing the noise contribution and spectral filters attenuate frequency components that most likely belong to noise subspace. However, the frequency spectrum of ERPs overlap with that of the ongoing electroencephalogram (EEG) and different types of artifacts. Therefore, proper selection of the spectral filter cutoffs is not a trivial task. In this research work, we developed a supervised method to estimate the spatial and finite impulse response (FIR) spectral filters, simultaneously. We evaluated the performance of the method on offline single trial classification of ERPs in datasets recorded during an oddball paradigm. The proposed spatio-spectral filter improved the overall single-trial classification performance by almost 9% on average compared with the case that no spatial filters were used. We also analyzed the effects of different spectral filter lengths and the number of retained channels after spatial filtering. Copyright © 2016. Published by Elsevier Ltd.

Bayesian learning for spatial filtering in an EEG-based brain-computer interface.

PubMed

Zhang, Haihong; Yang, Huijuan; Guan, Cuntai

2013-07-01

Spatial filtering for EEG feature extraction and classification is an important tool in brain-computer interface. However, there is generally no established theory that links spatial filtering directly to Bayes classification error. To address this issue, this paper proposes and studies a Bayesian analysis theory for spatial filtering in relation to Bayes error. Following the maximum entropy principle, we introduce a gamma probability model for describing single-trial EEG power features. We then formulate and analyze the theoretical relationship between Bayes classification error and the so-called Rayleigh quotient, which is a function of spatial filters and basically measures the ratio in power features between two classes. This paper also reports our extensive study that examines the theory and its use in classification, using three publicly available EEG data sets and state-of-the-art spatial filtering techniques and various classifiers. Specifically, we validate the positive relationship between Bayes error and Rayleigh quotient in real EEG power features. Finally, we demonstrate that the Bayes error can be practically reduced by applying a new spatial filter with lower Rayleigh quotient.

Application of a three-lens slit spatial filter in high power lasers

NASA Astrophysics Data System (ADS)

Xiong, Han

2018-07-01

Combined with partial parameters in National Ignition Facility, the conceptual design of off-axial four-pass main laser optical system with a three-lens slit spatial filter has been discussed. Since the three-lens slit spatial filter can decline the focal intensity by about 3 orders of magnitudes than that in NIF system, the cutoff frequency in main amplifier cavity can be reduced from 51 × DL to 39 × DL for better beam quality. The main laser system for single beam line can be shortened from 174.7 m to 155.7 m and the spatial filter in high vacuum becomes 60 m instead of the original 83.5 m. Additionally, the pinhole closure could be avoided since the declining of focal intensity in slit spatial filter and the absence of pinhole aperture in the other (pinhole) spatial filter, which provides new ideas for the future high-power lasers.

The synergy between complex channel-specific FIR filter and spatial filter for single-trial EEG classification.

PubMed

Yu, Ke; Wang, Yue; Shen, Kaiquan; Li, Xiaoping

2013-01-01

The common spatial pattern analysis (CSP), a frequently utilized feature extraction method in brain-computer-interface applications, is believed to be time-invariant and sensitive to noises, mainly due to an inherent shortcoming of purely relying on spatial filtering. Therefore, temporal/spectral filtering which can be very effective to counteract the unfavorable influence of noises is usually used as a supplement. This work integrates the CSP spatial filters with complex channel-specific finite impulse response (FIR) filters in a natural and intuitive manner. Each hybrid spatial-FIR filter is of high-order, data-driven and is unique to its corresponding channel. They are derived by introducing multiple time delays and regularization into conventional CSP. The general framework of the method follows that of CSP but performs better, as proven in single-trial classification tasks like event-related potential detection and motor imagery.

Translation of EEG Spatial Filters from Resting to Motor Imagery Using Independent Component Analysis

PubMed Central

Wang, Yijun; Wang, Yu-Te; Jung, Tzyy-Ping

2012-01-01

Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) often use spatial filters to improve signal-to-noise ratio of task-related EEG activities. To obtain robust spatial filters, large amounts of labeled data, which are often expensive and labor-intensive to obtain, need to be collected in a training procedure before online BCI control. Several studies have recently developed zero-training methods using a session-to-session scenario in order to alleviate this problem. To our knowledge, a state-to-state translation, which applies spatial filters derived from one state to another, has never been reported. This study proposes a state-to-state, zero-training method to construct spatial filters for extracting EEG changes induced by motor imagery. Independent component analysis (ICA) was separately applied to the multi-channel EEG in the resting and the motor imagery states to obtain motor-related spatial filters. The resultant spatial filters were then applied to single-trial EEG to differentiate left- and right-hand imagery movements. On a motor imagery dataset collected from nine subjects, comparable classification accuracies were obtained by using ICA-based spatial filters derived from the two states (motor imagery: 87.0%, resting: 85.9%), which were both significantly higher than the accuracy achieved by using monopolar scalp EEG data (80.4%). The proposed method considerably increases the practicality of BCI systems in real-world environments because it is less sensitive to electrode misalignment across different sessions or days and does not require annotated pilot data to derive spatial filters. PMID:22666377

Spatial operator approach to flexible multibody system dynamics and control

NASA Technical Reports Server (NTRS)

Rodriguez, G.

1991-01-01

The inverse and forward dynamics problems for flexible multibody systems were solved using the techniques of spatially recursive Kalman filtering and smoothing. These algorithms are easily developed using a set of identities associated with mass matrix factorization and inversion. These identities are easily derived using the spatial operator algebra developed by the author. Current work is aimed at computational experiments with the described algorithms and at modelling for control design of limber manipulator systems. It is also aimed at handling and manipulation of flexible objects.

Computational Investigations of Noise Suppression in Subsonic Round Jets

NASA Technical Reports Server (NTRS)

Pruett, C. David

1997-01-01

NASA Grant NAG1-1802, originally submitted in June 1996 as a two-year proposal, was awarded one-year's funding by NASA LaRC for the period 5 Oct., 1996, through 4 Oct., 1997. Because of the inavailability (from IT at NASA ARC) of sufficient supercomputer time in fiscal 1998 to complete the computational goals of the second year of the original proposal (estimated to be at least 400 Cray C-90 CPU hours), those goals have been appropriately amended, and a new proposal has been submitted to LaRC as a follow-on to NAG1-1802. The current report documents the activities and accomplishments on NAG1-1802 during the one-year period from 5 Oct., 1996, through 4 Oct., 1997. NASA Grant NAG1-1802, and its predecessor, NAG1-1772, have been directed toward adapting the numerical tool of Large-Eddy Simulation (LES) to aeroacoustic applications, with particular focus on noise suppression in subsonic round jets. In LES, the filtered Navier-Stokes equations are solved numerically on a relatively coarse computational grid. Residual stresses, generated by scales of motion too small to be resolved on the coarse grid, are modeled. Although most LES incorporate spatial filtering, time-domain filtering affords certain conceptual and computational advantages, particularly for aeroacoustic applications. Consequently, this work has focused on the development of SubGrid-Scale (SGS) models that incorporate time- domain filters. The author is unaware of any previous attempt at purely time-filtered LES; however, Aldama and Dakhoul and Bedford have considered approaches that combine both spatial and temporal filtering. In our view, filtering in both space and time is redundant, because removal of high frequencies effects the removal of small spatial scales and vice versa.

Plant Host Species and Geographic Distance Affect the Structure of Aboveground Fungal Symbiont Communities, and Environmental Filtering Affects Belowground Communities in a Coastal Dune Ecosystem.

PubMed

David, Aaron S; Seabloom, Eric W; May, Georgiana

2016-05-01

Microbial symbionts inhabit tissues of all plants and animals. Their community composition depends largely on two ecological processes: (1) filtering by abiotic conditions and host species determining the environments that symbionts are able to colonize and (2) dispersal-limitation determining the pool of symbionts available to colonize a given host and community spatial structure. In plants, the above- and belowground tissues represent such distinct habitats for symbionts that we expect different effects of filtering and spatial structuring on their symbiont communities. In this study, we characterized above- and belowground communities of fungal endophytes--fungi living asymptomatically within plants--to understand the contributions of filtering and spatial structure to endophyte community composition. We used a culture-based approach to characterize endophytes growing in leaves and roots of three species of coastal beachgrasses in dunes of the USA Pacific Northwest. For leaves, endophyte isolation frequency and OTU richness depended primarily on plant host species. In comparison, for roots, both isolation frequency and OTU richness increased from the nutrient-poor front of the dune to the higher-nutrient backdune. Endophyte community composition in leaves exhibited a distance-decay relationship across the region. In a laboratory assay, faster growth rates and lower spore production were more often associated with leaf- than root-inhabiting endophytes. Overall, our results reveal a greater importance of biotic filtering by host species and dispersal-limitation over regional geographic distances for aboveground leaf endophyte communities and stronger effects of abiotic environmental filtering and locally patchy distributions for belowground root endophyte communities.

Example-based human motion denoising.

PubMed

Lou, Hui; Chai, Jinxiang

2010-01-01

With the proliferation of motion capture data, interest in removing noise and outliers from motion capture data has increased. In this paper, we introduce an efficient human motion denoising technique for the simultaneous removal of noise and outliers from input human motion data. The key idea of our approach is to learn a series of filter bases from precaptured motion data and use them along with robust statistics techniques to filter noisy motion data. Mathematically, we formulate the motion denoising process in a nonlinear optimization framework. The objective function measures the distance between the noisy input and the filtered motion in addition to how well the filtered motion preserves spatial-temporal patterns embedded in captured human motion data. Optimizing the objective function produces an optimal filtered motion that keeps spatial-temporal patterns in captured motion data. We also extend the algorithm to fill in the missing values in input motion data. We demonstrate the effectiveness of our system by experimenting with both real and simulated motion data. We also show the superior performance of our algorithm by comparing it with three baseline algorithms and to those in state-of-art motion capture data processing software such as Vicon Blade.

Periodic component analysis as a spatial filter for SSVEP-based brain-computer interface.

PubMed

Kiran Kumar, G R; Reddy, M Ramasubba

2018-06-08

Traditional Spatial filters used for steady-state visual evoked potential (SSVEP) extraction such as minimum energy combination (MEC) require the estimation of the background electroencephalogram (EEG) noise components. Even though this leads to improved performance in low signal to noise ratio (SNR) conditions, it makes such algorithms slow compared to the standard detection methods like canonical correlation analysis (CCA) due to the additional computational cost. In this paper, Periodic component analysis (πCA) is presented as an alternative spatial filtering approach to extract the SSVEP component effectively without involving extensive modelling of the noise. The πCA can separate out components corresponding to a given frequency of interest from the background electroencephalogram (EEG) by capturing the temporal information and does not generalize SSVEP based on rigid templates. Data from ten test subjects were used to evaluate the proposed method and the results demonstrate that the periodic component analysis acts as a reliable spatial filter for SSVEP extraction. Statistical tests were performed to validate the results. The experimental results show that πCA provides significant improvement in accuracy compared to standard CCA and MEC in low SNR conditions. The results demonstrate that πCA provides better detection accuracy compared to CCA and on par with that of MEC at a lower computational cost. Hence πCA is a reliable and efficient alternative detection algorithm for SSVEP based brain-computer interface (BCI). Copyright © 2018. Published by Elsevier B.V.

Spatial filtering velocimeter for vehicle navigation with extended measurement range

NASA Astrophysics Data System (ADS)

He, Xin; Zhou, Jian; Nie, Xiaoming; Long, Xingwu

2015-05-01

The idea of using spatial filtering velocimeter is proposed to provide accurate velocity information for vehicle autonomous navigation system. The presented spatial filtering velocimeter is based on a CMOS linear image sensor. The limited frame rate restricts high speed measurement of the vehicle. To extend measurement range of the velocimeter, a method of frequency shifting is put forward. Theoretical analysis shows that the frequency of output signal can be reduced and the measurement range can be doubled by this method when the shifting direction is set the same with that of image velocity. The approach of fast Fourier transform (FFT) is employed to obtain the power spectra of the spatially filtered signals. Because of limited frequency resolution of FFT, a frequency spectrum correction algorithm, called energy centrobaric correction, is used to improve the frequency resolution. The correction accuracy energy centrobaric correction is analyzed. Experiments are carried out to measure the moving surface of a conveyor belt. The experimental results show that the maximum measurable velocity is about 800deg/s without frequency shifting, 1600deg/s with frequency shifting, when the frame rate of the image is about 8117 Hz. Therefore, the measurement range is doubled by the method of frequency shifting. Furthermore, experiments were carried out to measure the vehicle velocity simultaneously using both the designed SFV and a laser Doppler velocimeter (LDV). The measurement results of the presented SFV are coincident with that of the LDV, but with bigger fluctuation. Therefore, it has the potential of application to vehicular autonomous navigation.

Common mode error in Antarctic GPS coordinate time series on its effect on bedrock-uplift estimates

NASA Astrophysics Data System (ADS)

Liu, Bin; King, Matt; Dai, Wujiao

2018-05-01

Spatially-correlated common mode error always exists in regional, or-larger, GPS networks. We applied independent component analysis (ICA) to GPS vertical coordinate time series in Antarctica from 2010 to 2014 and made a comparison with the principal component analysis (PCA). Using PCA/ICA, the time series can be decomposed into a set of temporal components and their spatial responses. We assume the components with common spatial responses are common mode error (CME). An average reduction of ˜40% about the RMS values was achieved in both PCA and ICA filtering. However, the common mode components obtained from the two approaches have different spatial and temporal features. ICA time series present interesting correlations with modeled atmospheric and non-tidal ocean loading displacements. A white noise (WN) plus power law noise (PL) model was adopted in the GPS velocity estimation using maximum likelihood estimation (MLE) analysis, with ˜55% reduction of the velocity uncertainties after filtering using ICA. Meanwhile, spatiotemporal filtering reduces the amplitude of PL and periodic terms in the GPS time series. Finally, we compare the GPS uplift velocities, after correction for elastic effects, with recent models of glacial isostatic adjustment (GIA). The agreements of the GPS observed velocities and four GIA models are generally improved after the spatiotemporal filtering, with a mean reduction of ˜0.9 mm/yr of the WRMS values, possibly allowing for more confident separation of various GIA model predictions.

JPEG2000-coded image error concealment exploiting convex sets projections.

PubMed

Atzori, Luigi; Ginesu, Giaime; Raccis, Alessio

2005-04-01

Transmission errors in JPEG2000 can be grouped into three main classes, depending on the affected area: LL, high frequencies at the lower decomposition levels, and high frequencies at the higher decomposition levels. The first type of errors are the most annoying but can be concealed exploiting the signal spatial correlation like in a number of techniques proposed in the past; the second are less annoying but more difficult to address; the latter are often imperceptible. In this paper, we address the problem of concealing the second class or errors when high bit-planes are damaged by proposing a new approach based on the theory of projections onto convex sets. Accordingly, the error effects are masked by iteratively applying two procedures: low-pass (LP) filtering in the spatial domain and restoration of the uncorrupted wavelet coefficients in the transform domain. It has been observed that a uniform LP filtering brought to some undesired side effects that negatively compensated the advantages. This problem has been overcome by applying an adaptive solution, which exploits an edge map to choose the optimal filter mask size. Simulation results demonstrated the efficiency of the proposed approach.

Ultrasound sounding in air by fast-moving receiver

NASA Astrophysics Data System (ADS)

Sukhanov, D.; Erzakova, N.

2018-05-01

A method of ultrasound imaging in the air for a fast receiver. The case, when the speed of movement of the receiver can not be neglected with respect to the speed of sound. In this case, the Doppler effect is significant, making it difficult for matched filtering of the backscattered signal. The proposed method does not use a continuous repetitive noise-sounding signal. generalized approach applies spatial matched filtering in the time domain to recover the ultrasonic tomographic images.

Spatial filters for high-peak-power multistage laser amplifiers.

PubMed

Potemkin, A K; Barmashova, T V; Kirsanov, A V; Martyanov, M A; Khazanov, E A; Shaykin, A A

2007-07-10

We describe spatial filters used in a Nd:glass laser with an output pulse energy up to 300 J and a pulse duration of 1 ns. This laser is designed for pumping of a chirped-pulse optical parametric amplifier. We present data required to choose the shape and diameter of a spatial filter lens, taking into account aberrations caused by spherical surfaces. Calculation of the optimal pinhole diameter is presented. Design features of the spatial filters and the procedure of their alignment are discussed in detail.

Split-spectrum processing technique for SNR enhancement of ultrasonic guided wave.

PubMed

Pedram, Seyed Kamran; Fateri, Sina; Gan, Lu; Haig, Alex; Thornicroft, Keith

2018-02-01

Ultrasonic guided wave (UGW) systems are broadly used in several branches of industry where the structural integrity is of concern. In those systems, signal interpretation can often be challenging due to the multi-modal and dispersive propagation of UGWs. This results in degradation of the signals in terms of signal-to-noise ratio (SNR) and spatial resolution. This paper employs the split-spectrum processing (SSP) technique in order to enhance the SNR and spatial resolution of UGW signals using the optimized filter bank parameters in real time scenario for pipe inspection. SSP technique has already been developed for other applications such as conventional ultrasonic testing for SNR enhancement. In this work, an investigation is provided to clarify the sensitivity of SSP performance to the filter bank parameter values for UGWs such as processing bandwidth, filter bandwidth, filter separation and a number of filters. As a result, the optimum values are estimated to significantly improve the SNR and spatial resolution of UGWs. The proposed method is synthetically and experimentally compared with conventional approaches employing different SSP recombination algorithms. The Polarity Thresholding (PT) and PT with Minimization (PTM) algorithms were found to be the best recombination algorithms. They substantially improved the SNR up to 36.9dB and 38.9dB respectively. The outcome of the work presented in this paper paves the way to enhance the reliability of UGW inspections. Copyright © 2017 Elsevier B.V. All rights reserved.

Detection of Movement Related Cortical Potentials from EEG Using Constrained ICA for Brain-Computer Interface Applications.

PubMed

Karimi, Fatemeh; Kofman, Jonathan; Mrachacz-Kersting, Natalie; Farina, Dario; Jiang, Ning

2017-01-01

The movement related cortical potential (MRCP), a slow cortical potential from the scalp electroencephalogram (EEG), has been used in real-time brain-computer-interface (BCI) systems designed for neurorehabilitation. Detecting MPCPs in real time with high accuracy and low latency is essential in these applications. In this study, we propose a new MRCP detection method based on constrained independent component analysis (cICA). The method was tested for MRCP detection during executed and imagined ankle dorsiflexion of 24 healthy participants, and compared with four commonly used spatial filters for MRCP detection in an offline experiment. The effect of cICA and the compared spatial filters on the morphology of the extracted MRCP was evaluated by two indices quantifying the signal-to-noise ratio and variability of the extracted MRCP. The performance of the filters for detection was then directly compared for accuracy and latency. The latency obtained with cICA (-34 ± 29 ms motor execution (ME) and 28 ± 16 ms for motor imagery (MI) dataset) was significantly smaller than with all other spatial filters. Moreover, cICA resulted in greater true positive rates (87.11 ± 11.73 for ME and 86.66 ± 6.96 for MI dataset) and lower false positive rates (20.69 ± 13.68 for ME and 19.31 ± 12.60 for MI dataset) compared to the other methods. These results confirm the superiority of cICA in MRCP detection with respect to previously proposed EEG filtering approaches.

Detection of movement intention from single-trial movement-related cortical potentials

NASA Astrophysics Data System (ADS)

Niazi, Imran Khan; Jiang, Ning; Tiberghien, Olivier; Feldbæk Nielsen, Jørgen; Dremstrup, Kim; Farina, Dario

2011-10-01

Detection of movement intention from neural signals combined with assistive technologies may be used for effective neurofeedback in rehabilitation. In order to promote plasticity, a causal relation between intended actions (detected for example from the EEG) and the corresponding feedback should be established. This requires reliable detection of motor intentions. In this study, we propose a method to detect movements from EEG with limited latency. In a self-paced asynchronous BCI paradigm, the initial negative phase of the movement-related cortical potentials (MRCPs), extracted from multi-channel scalp EEG was used to detect motor execution/imagination in healthy subjects and stroke patients. For MRCP detection, it was demonstrated that a new optimized spatial filtering technique led to better accuracy than a large Laplacian spatial filter and common spatial pattern. With the optimized spatial filter, the true positive rate (TPR) for detection of movement execution in healthy subjects (n = 15) was 82.5 ± 7.8%, with latency of -66.6 ± 121 ms. Although TPR decreased with motor imagination in healthy subject (n = 10, 64.5 ± 5.33%) and with attempted movements in stroke patients (n = 5, 55.01 ± 12.01%), the results are promising for the application of this approach to provide patient-driven real-time neurofeedback.

Parallel exploitation of a spatial-spectral classification approach for hyperspectral images on RVC-CAL

NASA Astrophysics Data System (ADS)

Lazcano, R.; Madroñal, D.; Fabelo, H.; Ortega, S.; Salvador, R.; Callicó, G. M.; Juárez, E.; Sanz, C.

2017-10-01

Hyperspectral Imaging (HI) assembles high resolution spectral information from hundreds of narrow bands across the electromagnetic spectrum, thus generating 3D data cubes in which each pixel gathers the spectral information of the reflectance of every spatial pixel. As a result, each image is composed of large volumes of data, which turns its processing into a challenge, as performance requirements have been continuously tightened. For instance, new HI applications demand real-time responses. Hence, parallel processing becomes a necessity to achieve this requirement, so the intrinsic parallelism of the algorithms must be exploited. In this paper, a spatial-spectral classification approach has been implemented using a dataflow language known as RVCCAL. This language represents a system as a set of functional units, and its main advantage is that it simplifies the parallelization process by mapping the different blocks over different processing units. The spatial-spectral classification approach aims at refining the classification results previously obtained by using a K-Nearest Neighbors (KNN) filtering process, in which both the pixel spectral value and the spatial coordinates are considered. To do so, KNN needs two inputs: a one-band representation of the hyperspectral image and the classification results provided by a pixel-wise classifier. Thus, spatial-spectral classification algorithm is divided into three different stages: a Principal Component Analysis (PCA) algorithm for computing the one-band representation of the image, a Support Vector Machine (SVM) classifier, and the KNN-based filtering algorithm. The parallelization of these algorithms shows promising results in terms of computational time, as the mapping of them over different cores presents a speedup of 2.69x when using 3 cores. Consequently, experimental results demonstrate that real-time processing of hyperspectral images is achievable.

Quantum image median filtering in the spatial domain

NASA Astrophysics Data System (ADS)

Li, Panchi; Liu, Xiande; Xiao, Hong

2018-03-01

Spatial filtering is one principal tool used in image processing for a broad spectrum of applications. Median filtering has become a prominent representation of spatial filtering because its performance in noise reduction is excellent. Although filtering of quantum images in the frequency domain has been described in the literature, and there is a one-to-one correspondence between linear spatial filters and filters in the frequency domain, median filtering is a nonlinear process that cannot be achieved in the frequency domain. We therefore investigated the spatial filtering of quantum image, focusing on the design method of the quantum median filter and applications in image de-noising. To this end, first, we presented the quantum circuits for three basic modules (i.e., Cycle Shift, Comparator, and Swap), and then, we design two composite modules (i.e., Sort and Median Calculation). We next constructed a complete quantum circuit that implements the median filtering task and present the results of several simulation experiments on some grayscale images with different noise patterns. Although experimental results show that the proposed scheme has almost the same noise suppression capacity as its classical counterpart, the complexity analysis shows that the proposed scheme can reduce the computational complexity of the classical median filter from the exponential function of image size n to the second-order polynomial function of image size n, so that the classical method can be speeded up.

Spatial optical crosstalk in CMOS image sensors integrated with plasmonic color filters.

PubMed

Yu, Yan; Chen, Qin; Wen, Long; Hu, Xin; Zhang, Hui-Fang

2015-08-24

Imaging resolution of complementary metal oxide semiconductor (CMOS) image sensor (CIS) keeps increasing to approximately 7k × 4k. As a result, the pixel size shrinks down to sub-2μm, which greatly increases the spatial optical crosstalk. Recently, plasmonic color filter was proposed as an alternative to conventional colorant pigmented ones. However, there is little work on its size effect and the spatial optical crosstalk in a model of CIS. By numerical simulation, we investigate the size effect of nanocross array plasmonic color filters and analyze the spatial optical crosstalk of each pixel in a Bayer array of a CIS with a pixel size of 1μm. It is found that the small pixel size deteriorates the filtering performance of nanocross color filters and induces substantial spatial color crosstalk. By integrating the plasmonic filters in the low Metal layer in standard CMOS process, the crosstalk reduces significantly, which is compatible to pigmented filters in a state-of-the-art backside illumination CIS.

A high-power spatial filter for Thomson scattering stray light reduction

NASA Astrophysics Data System (ADS)

Levesque, J. P.; Litzner, K. D.; Mauel, M. E.; Maurer, D. A.; Navratil, G. A.; Pedersen, T. S.

2011-03-01

The Thomson scattering diagnostic on the High Beta Tokamak-Extended Pulse (HBT-EP) is routinely used to measure electron temperature and density during plasma discharges. Avalanche photodiodes in a five-channel interference filter polychromator measure scattered light from a 6 ns, 800 mJ, 1064 nm Nd:YAG laser pulse. A low cost, high-power spatial filter was designed, tested, and added to the laser beamline in order to reduce stray laser light to levels which are acceptable for accurate Rayleigh calibration. A detailed analysis of the spatial filter design and performance is given. The spatial filter can be easily implemented in an existing Thomson scattering system without the need to disturb the vacuum chamber or significantly change the beamline. Although apertures in the spatial filter suffer substantial damage from the focused beam, with proper design they can last long enough to permit absolute calibration.

Efficiency analysis of color image filtering

NASA Astrophysics Data System (ADS)

Fevralev, Dmitriy V.; Ponomarenko, Nikolay N.; Lukin, Vladimir V.; Abramov, Sergey K.; Egiazarian, Karen O.; Astola, Jaakko T.

2011-12-01

This article addresses under which conditions filtering can visibly improve the image quality. The key points are the following. First, we analyze filtering efficiency for 25 test images, from the color image database TID2008. This database allows assessing filter efficiency for images corrupted by different noise types for several levels of noise variance. Second, the limit of filtering efficiency is determined for independent and identically distributed (i.i.d.) additive noise and compared to the output mean square error of state-of-the-art filters. Third, component-wise and vector denoising is studied, where the latter approach is demonstrated to be more efficient. Fourth, using of modern visual quality metrics, we determine that for which levels of i.i.d. and spatially correlated noise the noise in original images or residual noise and distortions because of filtering in output images are practically invisible. We also demonstrate that it is possible to roughly estimate whether or not the visual quality can clearly be improved by filtering.

Minimum Energy-Variance Filters for the detection of compact sources in crowded astronomical images

NASA Astrophysics Data System (ADS)

Herranz, D.; Sanz, J. L.; López-Caniego, M.; González-Nuevo, J.

2006-10-01

In this paper we address the common problem of the detection and identification of compact sources, such as stars or far galaxies, in Astronomical images. The common approach, that consist in applying a matched filter to the data in order to remove noise and to search for intensity peaks above a certain detection threshold, does not work well when the sources to be detected appear in large number over small regions of the sky due to the effect of source overlapping and interferences among the filtered profiles of the sources. A new class of filter that balances noise removal with signal spatial concentration is introduced, then it is applied to simulated astronomical images of the sky at 857 GHz. We show that with the new filter it is possible to improve the ratio between true detections and false alarms with respect to the matched filter. For low detection thresholds, the improvement is ~ 40%.

Towards Zero Training for Brain-Computer Interfacing

PubMed Central

Krauledat, Matthias; Tangermann, Michael; Blankertz, Benjamin; Müller, Klaus-Robert

2008-01-01

Electroencephalogram (EEG) signals are highly subject-specific and vary considerably even between recording sessions of the same user within the same experimental paradigm. This challenges a stable operation of Brain-Computer Interface (BCI) systems. The classical approach is to train users by neurofeedback to produce fixed stereotypical patterns of brain activity. In the machine learning approach, a widely adapted method for dealing with those variances is to record a so called calibration measurement on the beginning of each session in order to optimize spatial filters and classifiers specifically for each subject and each day. This adaptation of the system to the individual brain signature of each user relieves from the need of extensive user training. In this paper we suggest a new method that overcomes the requirement of these time-consuming calibration recordings for long-term BCI users. The method takes advantage of knowledge collected in previous sessions: By a novel technique, prototypical spatial filters are determined which have better generalization properties compared to single-session filters. In particular, they can be used in follow-up sessions without the need to recalibrate the system. This way the calibration periods can be dramatically shortened or even completely omitted for these ‘experienced’ BCI users. The feasibility of our novel approach is demonstrated with a series of online BCI experiments. Although performed without any calibration measurement at all, no loss of classification performance was observed. PMID:18698427

A Wearable Channel Selection-Based Brain-Computer Interface for Motor Imagery Detection.

PubMed

Lo, Chi-Chun; Chien, Tsung-Yi; Chen, Yu-Chun; Tsai, Shang-Ho; Fang, Wai-Chi; Lin, Bor-Shyh

2016-02-06

Motor imagery-based brain-computer interface (BCI) is a communication interface between an external machine and the brain. Many kinds of spatial filters are used in BCIs to enhance the electroencephalography (EEG) features related to motor imagery. The approach of channel selection, developed to reserve meaningful EEG channels, is also an important technique for the development of BCIs. However, current BCI systems require a conventional EEG machine and EEG electrodes with conductive gel to acquire multi-channel EEG signals and then transmit these EEG signals to the back-end computer to perform the approach of channel selection. This reduces the convenience of use in daily life and increases the limitations of BCI applications. In order to improve the above issues, a novel wearable channel selection-based brain-computer interface is proposed. Here, retractable comb-shaped active dry electrodes are designed to measure the EEG signals on a hairy site, without conductive gel. By the design of analog CAR spatial filters and the firmware of EEG acquisition module, the function of spatial filters could be performed without any calculation, and channel selection could be performed in the front-end device to improve the practicability of detecting motor imagery in the wearable EEG device directly or in commercial mobile phones or tablets, which may have relatively low system specifications. Finally, the performance of the proposed BCI is investigated, and the experimental results show that the proposed system is a good wearable BCI system prototype.

Experimental evidence of the spatial coherence moiré and the filtering of classes of radiator pairs.

PubMed

Castaneda, Roman; Usuga-Castaneda, Mario; Herrera-Ramírez, Jorge

2007-08-01

Evidence of the physical existence of the spatial coherence moiré is obtained by confronting numerical results with experimental results of spatially partial interference. Although it was performed for two particular cases, the results reveal a general behavior of the optical fields in any state of spatial coherence. Moreover, the study of the spatial coherence moiré deals with a new type of filtering, named filtering of classes of radiator pairs, which allows changing the power spectrum at the observation plane by modulating the complex degree of spatial coherence, without altering the power distribution at the aperture plane or introducing conventional spatial filters. This new procedure can optimize some technological applications of actual interest, as the beam shaping for instance.

Remote sensing fusion based on guided image filtering

NASA Astrophysics Data System (ADS)

Zhao, Wenfei; Dai, Qinling; Wang, Leiguang

2015-12-01

In this paper, we propose a novel remote sensing fusion approach based on guided image filtering. The fused images can well preserve the spectral features of the original multispectral (MS) images, meanwhile, enhance the spatial details information. Four quality assessment indexes are also introduced to evaluate the fusion effect when compared with other fusion methods. Experiments carried out on Gaofen-2, QuickBird, WorldView-2 and Landsat-8 images. And the results show an excellent performance of the proposed method.

Identifying differences in brain activities and an accurate detection of autism spectrum disorder using resting state functional-magnetic resonance imaging : A spatial filtering approach.

PubMed

Subbaraju, Vigneshwaran; Suresh, Mahanand Belathur; Sundaram, Suresh; Narasimhan, Sundararajan

2017-01-01

This paper presents a new approach for detecting major differences in brain activities between Autism Spectrum Disorder (ASD) patients and neurotypical subjects using the resting state fMRI. Further the method also extracts discriminative features for an accurate diagnosis of ASD. The proposed approach determines a spatial filter that projects the covariance matrices of the Blood Oxygen Level Dependent (BOLD) time-series signals from both the ASD patients and neurotypical subjects in orthogonal directions such that they are highly separable. The inverse of this filter also provides a spatial pattern map within the brain that highlights those regions responsible for the distinguishable activities between the ASD patients and neurotypical subjects. For a better classification, highly discriminative log-variance features providing the maximum separation between the two classes are extracted from the projected BOLD time-series data. A detailed study has been carried out using the publicly available data from the Autism Brain Imaging Data Exchange (ABIDE) consortium for the different gender and age-groups. The study results indicate that for all the above categories, the regional differences in resting state activities are more commonly found in the right hemisphere compared to the left hemisphere of the brain. Among males, a clear shift in activities to the prefrontal cortex is observed for ASD patients while other parts of the brain show diminished activities compared to neurotypical subjects. Among females, such a clear shift is not evident; however, several regions, especially in the posterior and medial portions of the brain show diminished activities due to ASD. Finally, the classification performance obtained using the log-variance features is found to be better when compared to earlier studies in the literature. Copyright © 2016 Elsevier B.V. All rights reserved.

Real-time computer treatment of THz passive device images with the high image quality

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Trofimov, Vladislav V.

2012-06-01

We demonstrate real-time computer code improving significantly the quality of images captured by the passive THz imaging system. The code is not only designed for a THz passive device: it can be applied to any kind of such devices and active THz imaging systems as well. We applied our code for computer processing of images captured by four passive THz imaging devices manufactured by different companies. It should be stressed that computer processing of images produced by different companies requires using the different spatial filters usually. The performance of current version of the computer code is greater than one image per second for a THz image having more than 5000 pixels and 24 bit number representation. Processing of THz single image produces about 20 images simultaneously corresponding to various spatial filters. The computer code allows increasing the number of pixels for processed images without noticeable reduction of image quality. The performance of the computer code can be increased many times using parallel algorithms for processing the image. We develop original spatial filters which allow one to see objects with sizes less than 2 cm. The imagery is produced by passive THz imaging devices which captured the images of objects hidden under opaque clothes. For images with high noise we develop an approach which results in suppression of the noise after using the computer processing and we obtain the good quality image. With the aim of illustrating the efficiency of the developed approach we demonstrate the detection of the liquid explosive, ordinary explosive, knife, pistol, metal plate, CD, ceramics, chocolate and other objects hidden under opaque clothes. The results demonstrate the high efficiency of our approach for the detection of hidden objects and they are a very promising solution for the security problem.

Least Median of Squares Filtering of Locally Optimal Point Matches for Compressible Flow Image Registration

PubMed Central

Castillo, Edward; Castillo, Richard; White, Benjamin; Rojo, Javier; Guerrero, Thomas

2012-01-01

Compressible flow based image registration operates under the assumption that the mass of the imaged material is conserved from one image to the next. Depending on how the mass conservation assumption is modeled, the performance of existing compressible flow methods is limited by factors such as image quality, noise, large magnitude voxel displacements, and computational requirements. The Least Median of Squares Filtered Compressible Flow (LFC) method introduced here is based on a localized, nonlinear least squares, compressible flow model that describes the displacement of a single voxel that lends itself to a simple grid search (block matching) optimization strategy. Spatially inaccurate grid search point matches, corresponding to erroneous local minimizers of the nonlinear compressible flow model, are removed by a novel filtering approach based on least median of squares fitting and the forward search outlier detection method. The spatial accuracy of the method is measured using ten thoracic CT image sets and large samples of expert determined landmarks (available at www.dir-lab.com). The LFC method produces an average error within the intra-observer error on eight of the ten cases, indicating that the method is capable of achieving a high spatial accuracy for thoracic CT registration. PMID:22797602

Separation of simultaneous sources using a structural-oriented median filter in the flattened dimension

NASA Astrophysics Data System (ADS)

Gan, Shuwei; Wang, Shoudong; Chen, Yangkang; Chen, Xiaohong; Xiang, Kui

2016-01-01

Simultaneous-source shooting can help tremendously shorten the acquisition period and improve the quality of seismic data for better subsalt seismic imaging, but at the expense of introducing strong interference (blending noise) to the acquired seismic data. We propose to use a structural-oriented median filter to attenuate the blending noise along the structural direction of seismic profiles. The principle of the proposed approach is to first flatten the seismic record in local spatial windows and then to apply a traditional median filter (MF) to the third flattened dimension. The key component of the proposed approach is the estimation of the local slope, which can be calculated by first scanning the NMO velocity and then transferring the velocity to the local slope. Both synthetic and field data examples show that the proposed approach can successfully separate the simultaneous-source data into individual sources. We provide an open-source toy example to better demonstratethe proposed methodology.

Neural networks for data compression and invariant image recognition

NASA Technical Reports Server (NTRS)

Gardner, Sheldon

1989-01-01

An approach to invariant image recognition (I2R), based upon a model of biological vision in the mammalian visual system (MVS), is described. The complete I2R model incorporates several biologically inspired features: exponential mapping of retinal images, Gabor spatial filtering, and a neural network associative memory. In the I2R model, exponentially mapped retinal images are filtered by a hierarchical set of Gabor spatial filters (GSF) which provide compression of the information contained within a pixel-based image. A neural network associative memory (AM) is used to process the GSF coded images. We describe a 1-D shape function method for coding of scale and rotationally invariant shape information. This method reduces image shape information to a periodic waveform suitable for coding as an input vector to a neural network AM. The shape function method is suitable for near term applications on conventional computing architectures equipped with VLSI FFT chips to provide a rapid image search capability.

Digital processing of radiographic images

NASA Technical Reports Server (NTRS)

Bond, A. D.; Ramapriyan, H. K.

1973-01-01

Some techniques are presented and the software documentation for the digital enhancement of radiographs. Both image handling and image processing operations are considered. The image handling operations dealt with are: (1) conversion of format of data from packed to unpacked and vice versa; (2) automatic extraction of image data arrays; (3) transposition and 90 deg rotations of large data arrays; (4) translation of data arrays for registration; and (5) reduction of the dimensions of data arrays by integral factors. Both the frequency and the spatial domain approaches are presented for the design and implementation of the image processing operation. It is shown that spatial domain recursive implementation of filters is much faster than nonrecursive implementations using fast fourier transforms (FFT) for the cases of interest in this work. The recursive implementation of a class of matched filters for enhancing image signal to noise ratio is described. Test patterns are used to illustrate the filtering operations. The application of the techniques to radiographic images of metallic structures is demonstrated through several examples.

Development of high damage threshold laser-machined apodizers and gain filters for laser applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rambo, Patrick; Schwarz, Jens; Kimmel, Mark

We have developed high damage threshold filters to modify the spatial profile of a high energy laser beam. The filters are formed by laser ablation of a transmissive window. The ablation sites constitute scattering centers which can be filtered in a subsequent spatial filter. Finally, by creating the filters in dielectric materials, we see an increased laser-induced damage threshold from previous filters created using ‘metal on glass’ lithography.

Development of high damage threshold laser-machined apodizers and gain filters for laser applications

DOE PAGES

Rambo, Patrick; Schwarz, Jens; Kimmel, Mark; ...

2016-09-27

We have developed high damage threshold filters to modify the spatial profile of a high energy laser beam. The filters are formed by laser ablation of a transmissive window. The ablation sites constitute scattering centers which can be filtered in a subsequent spatial filter. Finally, by creating the filters in dielectric materials, we see an increased laser-induced damage threshold from previous filters created using ‘metal on glass’ lithography.

Short spatial filters with spherical lenses for high-power pulsed lasers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burdonov, K F; Soloviev, A A; Shaikin, A A

We report possible employment of short spatial filters based on spherical lenses in a pulsed laser source (neodymium glass, 300 J, 1 ns). The influence of the spherical aberration on the quality of output radiation and coefficient of conversion to the second harmonics is studied. The ultra-short aberration spatial filter of length 1.9 m with an aperture of 122 mm is experimentally tested. A considerable shortening of multi-cascade pump lasers for modern petawatt laser systems is demonstrated by the employment of short spatial filters without expensive aspherical optics. (elements of laser systems)

Using the spatial filtering process to evaluate the nonbreeding range of Rusty Blackbird Euphagus carolinus

Treesearch

Paul Hamel; Esra Ozdenrol

2008-01-01

During the nonbreeding period, Rusty Blackbird (Euphagus carolinus) occurs predominantly in forested wetland habitats in the southeastern U.S. We used spatial filtering of Christmas Bird Count data to identify areas within the nonbreeding range where the species occurs at higher than expected probability. Spatial filtering is an epidemiological modeling process...

Evaluating Benefits of LID Practices at Multiple Spatial Scales Using SUSTAIN

EPA Science Inventory

Low impact development (LID) is a storm water management approach that essentially mimics the way nature works: infiltrate, filter, store, evaporate, and detain runoff close to its source. LID practices are distributed in nature, and they work on decentralized micro-scales and m...

Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

PubMed

Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

2014-05-01

In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

Spatial filter with volume gratings for high-peak-power multistage laser amplifiers

NASA Astrophysics Data System (ADS)

Tan, Yi-zhou; Yang, Yi-sheng; Zheng, Guang-wei; Shen, Ben-jian; Pan, Heng-yue; Liu, Li

2010-08-01

The regular spatial filters comprised of lens and pinhole are essential component in high power laser systems, such as lasers for inertial confinement fusion, nonlinear optical technology and directed-energy weapon. On the other hand the pinhole is treated as a bottleneck of high power laser due to harmful plasma created by the focusing beam. In this paper we present a spatial filter based on angular selectivity of Bragg diffraction grating to avoid the harmful focusing effect in the traditional pinhole filter. A spatial filter consisted of volume phase gratings in two-pass amplifier cavity were reported. Two-dimensional filter was proposed by using single Pi-phase-shifted Bragg grating, numerical simulation results shown that its angular spectrum bandwidth can be less than 160urad. The angular selectivity of photo-thermorefractive glass and RUGATE film filters, construction stability, thermal stability and the effects of misalignments of gratings on the diffraction efficiencies under high-pulse-energy laser operating condition are discussed.

The role of low-spatial frequencies in lexical decision and masked priming.

PubMed

Boden, C; Giaschi, D

2009-04-01

Spatial frequency filtering was used to test the hypotheses that low-spatial frequency information in printed text can: (1) lead to a rapid lexical decision or (2) facilitate word recognition. Adult proficient readers made lexical decisions in unprimed and masked repetition priming experiments with unfiltered, low-pass, high-pass and notch filtered letter strings. In the unprimed experiments, a filtered target was presented for 105 or 400 ms followed by a pattern mask. Sensitivity (d') was lowest for the low-pass filtered targets at both durations with a bias towards a 'non-word' response. Sensitivity was higher in the high-pass and notch filter conditions. In the priming experiments, a forward mask was followed by a filtered prime then an unfiltered target. Primed words, but not non-words, were identified faster than unprimed words in both the low-pass and high-pass filtered conditions. These results do not support a unique role for low-spatial frequency information in either facilitating or making rapid lexical decisions.

Crack Imaging and Quantification in Aluminum Plates with Guided Wave Wavenumber Analysis Methods

NASA Technical Reports Server (NTRS)

Yu, Lingyu; Tian, Zhenhua; Leckey, Cara A. C.

2015-01-01

Guided wavefield analysis methods for detection and quantification of crack damage in an aluminum plate are presented in this paper. New wavenumber components created by abrupt wave changes at the structural discontinuity are identified in the frequency-wavenumber spectra. It is shown that the new wavenumbers can be used to detect and characterize the crack dimensions. Two imaging based approaches, filter reconstructed imaging and spatial wavenumber imaging, are used to demonstrate how the cracks can be evaluated with wavenumber analysis. The filter reconstructed imaging is shown to be a rapid method to map the plate and any existing damage, but with less precision in estimating crack dimensions; while the spatial wavenumber imaging provides an intensity image of spatial wavenumber values with enhanced resolution of crack dimensions. These techniques are applied to simulated wavefield data, and the simulation based studies show that spatial wavenumber imaging method is able to distinguish cracks of different severities. Laboratory experimental validation is performed for a single crack case to confirm the methods' capabilities for imaging cracks in plates.

Extracting spatial information from large aperture exposures of diffuse sources

NASA Technical Reports Server (NTRS)

Clarke, J. T.; Moos, H. W.

1981-01-01

The spatial properties of large aperture exposures of diffuse emission can be used both to investigate spatial variations in the emission and to filter out camera noise in exposures of weak emission sources. Spatial imaging can be accomplished both parallel and perpendicular to dispersion with a resolution of 5-6 arc sec, and a narrow median filter running perpendicular to dispersion across a diffuse image selectively filters out point source features, such as reseaux marks and fast particle hits. Spatial information derived from observations of solar system objects is presented.

CHAMP - Camera, Handlens, and Microscope Probe

NASA Technical Reports Server (NTRS)

Mungas, G. S.; Beegle, L. W.; Boynton, J.; Sepulveda, C. A.; Balzer, M. A.; Sobel, H. R.; Fisher, T. A.; Deans, M.; Lee, P.

2005-01-01

CHAMP (Camera, Handlens And Microscope Probe) is a novel field microscope capable of color imaging with continuously variable spatial resolution from infinity imaging down to diffraction-limited microscopy (3 micron/pixel). As an arm-mounted imager, CHAMP supports stereo-imaging with variable baselines, can continuously image targets at an increasing magnification during an arm approach, can provide precision range-finding estimates to targets, and can accommodate microscopic imaging of rough surfaces through a image filtering process called z-stacking. Currently designed with a filter wheel with 4 different filters, so that color and black and white images can be obtained over the entire Field-of-View, future designs will increase the number of filter positions to include 8 different filters. Finally, CHAMP incorporates controlled white and UV illumination so that images can be obtained regardless of sun position, and any potential fluorescent species can be identified so the most astrobiologically interesting samples can be identified.

Preliminary design of the spatial filters used in the multipass amplification system of TIL

NASA Astrophysics Data System (ADS)

Zhu, Qihua; Zhang, Xiao Min; Jing, Feng

1998-12-01

The spatial filters are used in Technique Integration Line, which has a multi-pass amplifier, not only to suppress parasitic high spatial frequency modes but also to provide places for inserting a light isolator and injecting the seed beam, and to relay image while the beam passes through the amplifiers several times. To fulfill these functions, the parameters of the spatial filters are optimized by calculations and analyzes with the consideration of avoiding the plasma blow-off effect and components demanding by ghost beam focus. The 'ghost beams' are calculated by ray tracing. A software was developed to evaluate the tolerance of the spatial filters and their components, and to align the whole system on computer simultaneously.

Investigating MAI's Precision: Single Interferogram and Time Series Filtering

NASA Astrophysics Data System (ADS)

Bechor Ben Dov, N.; Herring, T.

2010-12-01

Multiple aperture InSAR (MAI) is a technique to obtain along-track displacements from InSAR phase data. Because InSAR measurements are insensitive to along-track displacements, it is only possible to retrieve them using none-interferometric approaches, either pixel-offset tracking or using data from different orbital configurations and assuming continuity/ displacement model. These approaches are limited by precision and data acquisition conflicts, respectively. MAI is promising in this respect as its precision is better than the former and its data is available whether additional acquisitions are there or not. Here we study the MAI noise and develop a filter to reduce it. We test the filtering with empirical noise and simulated signal data. Below we describe the filtered results single interferogram precision, and a Kalman filter approach for MAI time series. We use 14 interferograms taken over the larger Los Angeles/San Gabrial Mountains area in CA. The interferograms include a variety of decorrelation sources, both terrain-related (topographic variations, vegetation and agriculture), and imaging-related (spatial and temporal baselines of 200-500m and 1-12 months, respectively). Most of the pixels are in the low to average coherence range (below 0.7). The data were collected by ESA and made available by the WInSAR consortium. We assume the data contain “zero” along-track signal (less then the theoretical 4 cm for our coherence range), and use the images as 14 dependent realizations of the MAI noise. We find a wide distribution of phase values σ = 2-3 radians (wrapped). We superimpose a signal on our MAI noise interferograms using along-track displacement (-88 - 143 cm) calculated for the 1812 Wrightwood earthquake. To analyze single MAI interferograms, we design an iterative quantile-based filter and test it on the noise+signal MAI interferograms. The residuals reveal the following MAI noise characteristics: (1) a constant noise term, up to 90 cm (2) a displacement gradient term, up to 0.75cm/km (3) a coherence dependent root residuals sum of squares (RRSS), down to 5 cm at 0.8 coherence In the figure we present two measures of the MAI rmse. Prior to phase gradient correction the RRSS follows the circled line. With the correction, the RRSS follows the solid line. We next evaluate MAI's precision given a time series. We use a Kalman Filter to estimate the spatially and temporally correlated components of the MAI data. We reference the displacements to a given area in the interferograms, weight the data with coherence, and model the reminder terms of the spatially correlated noise as a quadratic phase gradient across the image. The results (not displayed) again vary with coherence. MAI single interferogram precision

Classifying EEG for Brain-Computer Interface: Learning Optimal Filters for Dynamical System Features

PubMed Central

Song, Le; Epps, Julien

2007-01-01

Classification of multichannel EEG recordings during motor imagination has been exploited successfully for brain-computer interfaces (BCI). In this paper, we consider EEG signals as the outputs of a networked dynamical system (the cortex), and exploit synchronization features from the dynamical system for classification. Herein, we also propose a new framework for learning optimal filters automatically from the data, by employing a Fisher ratio criterion. Experimental evaluations comparing the proposed dynamical system features with the CSP and the AR features reveal their competitive performance during classification. Results also show the benefits of employing the spatial and the temporal filters optimized using the proposed learning approach. PMID:18364986

Characterization Of Improved Binary Phase-Only Filters In A Real-Time Coherent Optical Correlation System

NASA Astrophysics Data System (ADS)

Flannery, D.; Keller, P.; Cartwright, S.; Loomis, J.

1987-06-01

Attractive correlation system performance potential is possible using magneto-optic spatial light modulators (SLM) to implement binary phase-only reference filters at high rates, provided the correlation performance of such reduced-information-content filters is adequate for the application. In the case studied here, the desired filter impulse response is a rectangular shape, which cannot be achieved with the usual binary phase-only filter formulation. The correlation application problem is described and techniques for synthesizing improved filter impulse response are considered. A compromise solution involves the cascading of a fixed amplitude-only weighting mask with the binary phase-only SLM. Based on simulations presented, this approach provides improved impulse responses and good correlation performance, while retaining the critical feature of real-time variations of the size, shape, and orientation of the rectangle by electronic programming of the phase pattern in the SLM. Simulations indicate that, for at least one very challenging input scene clutter situation, these filters provide higher correlation signal-to-noise than does "ideal" correlation, i.e. using a perfect rectangle filter response.

Fusing Observations and Model Results for Creation of Enhanced Ozone Spatial Fields: Comparison of Three Techniques

EPA Science Inventory

This paper presents three simple techniques for fusing observations and numerical model predictions. The techniques rely on model/observation bias being considered either as error free, or containing some uncertainty, the latter mitigated with a Kalman filter approach or a spati...

Spectral analysis and filtering techniques in digital spatial data processing

USGS Publications Warehouse

Pan, Jeng-Jong

1989-01-01

A filter toolbox has been developed at the EROS Data Center, US Geological Survey, for retrieving or removing specified frequency information from two-dimensional digital spatial data. This filter toolbox provides capabilities to compute the power spectrum of a given data and to design various filters in the frequency domain. Three types of filters are available in the toolbox: point filter, line filter, and area filter. Both the point and line filters employ Gaussian-type notch filters, and the area filter includes the capabilities to perform high-pass, band-pass, low-pass, and wedge filtering techniques. These filters are applied for analyzing satellite multispectral scanner data, airborne visible and infrared imaging spectrometer (AVIRIS) data, gravity data, and the digital elevation models (DEM) data. -from Author

Spatial filters for high average power lasers

DOEpatents

Erlandson, Alvin C

2012-11-27

A spatial filter includes a first filter element and a second filter element overlapping with the first filter element. The first filter element includes a first pair of cylindrical lenses separated by a first distance. Each of the first pair of cylindrical lenses has a first focal length. The first filter element also includes a first slit filter positioned between the first pair of cylindrical lenses. The second filter element includes a second pair of cylindrical lenses separated by a second distance. Each of the second pair of cylindrical lenses has a second focal length. The second filter element also includes a second slit filter positioned between the second pair of cylindrical lenses.

Spatial filters for high power lasers

DOEpatents

Erlandson, Alvin Charles; Bayramian, Andrew James

2014-12-02

A spatial filter includes a first filter element and a second filter element overlapping with the first filter element. The first filter element includes a first pair of cylindrical lenses separated by a first distance. Each of the first pair of cylindrical lenses has a first focal length. The first filter element also includes a first longitudinal slit filter positioned between the first pair of cylindrical lenses. The second filter element includes a second pair of cylindrical lenses separated by a second distance. Each of the second pair of cylindrical lenses has a second focal length. The second filter element also includes a second longitudinal slit filter positioned between the second pair of cylindrical lenses.

Regularized Filters for L1-Norm-Based Common Spatial Patterns.

PubMed

Wang, Haixian; Li, Xiaomeng

2016-02-01

The l1 -norm-based common spatial patterns (CSP-L1) approach is a recently developed technique for optimizing spatial filters in the field of electroencephalogram (EEG)-based brain computer interfaces. The l1 -norm-based expression of dispersion in CSP-L1 alleviates the negative impact of outliers. In this paper, we further improve the robustness of CSP-L1 by taking into account noise which does not necessarily have as large a deviation as with outliers. The noise modelling is formulated by using the waveform length of the EEG time course. With the noise modelling, we then regularize the objective function of CSP-L1, in which the l1-norm is used in two folds: one is the dispersion and the other is the waveform length. An iterative algorithm is designed to resolve the optimization problem of the regularized objective function. A toy illustration and the experiments of classification on real EEG data sets show the effectiveness of the proposed method.

Optimal design of a bank of spatio-temporal filters for EEG signal classification.

PubMed

Higashi, Hiroshi; Tanaka, Toshihisa

2011-01-01

The spatial weights for electrodes called common spatial pattern (CSP) are known to be effective in EEG signal classification for motor imagery based brain computer interfaces (MI-BCI). To achieve accurate classification in CSP, the frequency filter should be properly designed. To this end, several methods for designing the filter have been proposed. However, the existing methods cannot consider plural brain activities described with different frequency bands and different spatial patterns such as activities of mu and beta rhythms. In order to efficiently extract these brain activities, we propose a method to design plural filters and spatial weights which extract desired brain activity. The proposed method designs finite impulse response (FIR) filters and the associated spatial weights by optimization of an objective function which is a natural extension of CSP. Moreover, we show by a classification experiment that the bank of FIR filters which are designed by introducing an orthogonality into the objective function can extract good discriminative features. Moreover, the experiment result suggests that the proposed method can automatically detect and extract brain activities related to motor imagery.

Efficient Lane Boundary Detection with Spatial-Temporal Knowledge Filtering

PubMed Central

Nan, Zhixiong; Wei, Ping; Xu, Linhai; Zheng, Nanning

2016-01-01

Lane boundary detection technology has progressed rapidly over the past few decades. However, many challenges that often lead to lane detection unavailability remain to be solved. In this paper, we propose a spatial-temporal knowledge filtering model to detect lane boundaries in videos. To address the challenges of structure variation, large noise and complex illumination, this model incorporates prior spatial-temporal knowledge with lane appearance features to jointly identify lane boundaries. The model first extracts line segments in video frames. Two novel filters—the Crossing Point Filter (CPF) and the Structure Triangle Filter (STF)—are proposed to filter out the noisy line segments. The two filters introduce spatial structure constraints and temporal location constraints into lane detection, which represent the spatial-temporal knowledge about lanes. A straight line or curve model determined by a state machine is used to fit the line segments to finally output the lane boundaries. We collected a challenging realistic traffic scene dataset. The experimental results on this dataset and other standard dataset demonstrate the strength of our method. The proposed method has been successfully applied to our autonomous experimental vehicle. PMID:27529248

Two-wavelength spatial-heterodyne holography

DOEpatents

Hanson, Gregory R.; Bingham, Philip R.; Simpson, John T.; Karnowski, Thomas P.; Voelkl, Edgar

2007-12-25

Systems and methods are described for obtaining two-wavelength differential-phase holograms. A method includes determining a difference between a filtered analyzed recorded first spatially heterodyne hologram phase and a filtered analyzed recorded second spatially-heterodyned hologram phase.

Noise reduction and functional maps image quality improvement in dynamic CT perfusion using a new k-means clustering guided bilateral filter (KMGB).

PubMed

Pisana, Francesco; Henzler, Thomas; Schönberg, Stefan; Klotz, Ernst; Schmidt, Bernhard; Kachelrieß, Marc

2017-07-01

Dynamic CT perfusion (CTP) consists in repeated acquisitions of the same volume in different time steps, slightly before, during and slightly afterwards the injection of contrast media. Important functional information can be derived for each voxel, which reflect the local hemodynamic properties and hence the metabolism of the tissue. Different approaches are being investigated to exploit data redundancy and prior knowledge for noise reduction of such datasets, ranging from iterative reconstruction schemes to high dimensional filters. We propose a new spatial bilateral filter which makes use of the k-means clustering algorithm and of an optimal calculated guiding image. We named the proposed filter as k-means clustering guided bilateral filter (KMGB). In this study, the KMGB filter is compared with the partial temporal non-local means filter (PATEN), with the time-intensity profile similarity (TIPS) filter, and with a new version derived from it, by introducing the guiding image (GB-TIPS). All the filters were tested on a digital in-house developed brain CTP phantom, were noise was added to simulate 80 kV and 200 mAs (default scanning parameters), 100 mAs and 30 mAs. Moreover, the filters performances were tested on 7 noisy clinical datasets with different pathologies in different body regions. The original contribution of our work is two-fold: first we propose an efficient algorithm to calculate a guiding image to improve the results of the TIPS filter, secondly we propose the introduction of the k-means clustering step and demonstrate how this can potentially replace the TIPS part of the filter obtaining better results at lower computational efforts. As expected, in the GB-TIPS, the introduction of the guiding image limits the over-smoothing of the TIPS filter, improving spatial resolution by more than 50%. Furthermore, replacing the time-intensity profile similarity calculation with a fuzzy k-means clustering strategy (KMGB) allows to control the edge preserving features of the filter, resulting in improved spatial resolution and CNR both for CT images and for functional maps. In the phantom study, the PATEN filter showed overall the poorest results, while the other filters showed comparable performances in terms of perfusion values preservation, with the KMGB filter having overall the best image quality. In conclusion, the KMGB filter leads to superior results for CT images and functional maps quality improvement, in significantly shorter computational times compared to the other filters. Our results suggest that the KMGB filter might be a more robust solution for halved-dose CTP datasets. For all the filters investigated, some artifacts start to appear on the BF maps if one sixth of the dose is simulated, suggesting that no one of the filters investigated in this study might be optimal for such a drastic dose reduction scenario. © 2017 American Association of Physicists in Medicine.

Low-pass filtered continuum streambed and bedload sediment mass balance laws for an alluvial, gravel-bed stream

NASA Astrophysics Data System (ADS)

DeTemple, B.; Wilcock, P.

2011-12-01

In an alluvial, gravel-bed stream governed by a plane-bed bedload transport regime, the physicochemical properties, size distribution, and granular architecture of the sediment grains that constitute the streambed surface influence many hydrodynamic, geomorphic, chemical, and ecological processes. Consequently, the abilities to accurately characterize the morphology and model the morphodynamics of the streambed surface and its interaction with the bedload above and subsurface below are necessary for a more complete understanding of how sediment, flow, organisms, and biogeochemistry interact. We report on our progress in the bottom-up development of low-pass filtered continuum streambed and bedload sediment mass balance laws for an alluvial, gravel-bed stream. These balance laws are assembled in a four stage process. First, the stream sediment-water system is conceptually abstracted as a nested, multi-phase, multi-species, structured continuum. Second, the granular surface of an aggregate of sediment grains is mathematically defined. Third, an integral approach to mass balance, founded in the continuum theory of multiphase flow, is used to formulate primordial, differential, instantaneous, local, continuum, mass balance laws applicable at any material point within a gravel-bed stream. Fourth, area averaging and time-after-area averaging, employing planform, low-pass filtering expressed as correlation or convolution integrals and based on the spatial and temporal filtering techniques found in the fields of multiphase flow, porous media flow, and large eddy simulation of turbulent fluid flow, are applied to smooth the primordial equations while maximizing stratigraphic resolution and preserving the definitions of relevant morphodynamic surfaces. Our approach unifies, corrects, contextualizes, and generalizes prior efforts at developing stream sediment continuity equations, including the top-down derivations of the surface layer (or "active layer") approach of Hirano [1971a,b] and probabilistic approach of Parker et al. [2000], as well as the bottom-up, low-pass filtered continuum approach of Coleman & Nikora [2009] which employed volume and volume-after-time averaging. It accommodates partial transport (e.g., Wilcock & McArdell [1997], Wilcock [1997a,b]). Additionally, it provides: (1) precise definitions of the geometry and kinematics of sediment in a gravel-bed stream required to collect and analyze the high resolution spatial and temporal datasets that are becoming ever more present in both laboratory and field investigations, (2) a mathematical framework for the use of tracer grains in gravel-bed streams, including the fate of streambed-emplaced tracers as well as the dispersion of tracers in the bedload, (3) spatial and temporal averaging uncompromised by the Reynolds rules necessary to assess the nature of scale separation, and (4) a kinematic foundation for hybrid Langrangian-Eulerian models of sediment morphodynamics.

Going Deeper With Contextual CNN for Hyperspectral Image Classification.

PubMed

Lee, Hyungtae; Kwon, Heesung

2017-10-01

In this paper, we describe a novel deep convolutional neural network (CNN) that is deeper and wider than other existing deep networks for hyperspectral image classification. Unlike current state-of-the-art approaches in CNN-based hyperspectral image classification, the proposed network, called contextual deep CNN, can optimally explore local contextual interactions by jointly exploiting local spatio-spectral relationships of neighboring individual pixel vectors. The joint exploitation of the spatio-spectral information is achieved by a multi-scale convolutional filter bank used as an initial component of the proposed CNN pipeline. The initial spatial and spectral feature maps obtained from the multi-scale filter bank are then combined together to form a joint spatio-spectral feature map. The joint feature map representing rich spectral and spatial properties of the hyperspectral image is then fed through a fully convolutional network that eventually predicts the corresponding label of each pixel vector. The proposed approach is tested on three benchmark data sets: the Indian Pines data set, the Salinas data set, and the University of Pavia data set. Performance comparison shows enhanced classification performance of the proposed approach over the current state-of-the-art on the three data sets.

Dem Reconstruction Using Light Field and Bidirectional Reflectance Function from Multi-View High Resolution Spatial Images

NASA Astrophysics Data System (ADS)

de Vieilleville, F.; Ristorcelli, T.; Delvit, J.-M.

2016-06-01

This paper presents a method for dense DSM reconstruction from high resolution, mono sensor, passive imagery, spatial panchromatic image sequence. The interest of our approach is four-fold. Firstly, we extend the core of light field approaches using an explicit BRDF model from the Image Synthesis community which is more realistic than the Lambertian model. The chosen model is the Cook-Torrance BRDF which enables us to model rough surfaces with specular effects using specific material parameters. Secondly, we extend light field approaches for non-pinhole sensors and non-rectilinear motion by using a proper geometric transformation on the image sequence. Thirdly, we produce a 3D volume cost embodying all the tested possible heights and filter it using simple methods such as Volume Cost Filtering or variational optimal methods. We have tested our method on a Pleiades image sequence on various locations with dense urban buildings and report encouraging results with respect to classic multi-label methods such as MIC-MAC, or more recent pipelines such as S2P. Last but not least, our method also produces maps of material parameters on the estimated points, allowing us to simplify building classification or road extraction.

Prefocused objective-pinhole unit for beam expanding and spatial filtering.

PubMed

Antes, G P

1973-03-01

A beam-expanding and spatial-filtering device, the prefocused objective-pinhole unit (POP unit), is presented. The design is primarily aimed at greater simplicity in handling and construction than the commercially available lens-pinhole spatial filters (LPSF), for once the pinhole is fixed in the correct position with respect to the objective, the alignment of the whole unit can be made an easy matter.

Time-lapse analysis of methane quantity in Mary Lee group of coal seams using filter-based multiple-point geostatistical simulation

USGS Publications Warehouse

Karacan, C. Özgen; Olea, Ricardo A.

2013-01-01

The systematic approach presented in this paper is the first time in literature that history matching, TIs of GIPs and filter simulations are used for degasification performance evaluation and for assessing GIP for mining safety. Results from this study showed that using production history matching of coalbed methane wells to determine time-lapsed reservoir data could be used to compute spatial GIP and representative GIP TIs generated through Voronoi decomposition. Furthermore, performing filter simulations using point-wise data and TIs could be used to predict methane quantity in coal seams subjected to degasification. During the course of the study, it was shown that the material balance of gas produced by wellbores and the GIP reductions in coal seams predicted using filter simulations compared very well, showing the success of filter simulations for continuous variables in this case study. Quantitative results from filter simulations of GIP within the studied area briefly showed that GIP was reduced from an initial ∼73 Bcf (median) to ∼46 Bcf (2011), representing a 37 % decrease and varying spatially through degasification. It is forecasted that there will be an additional ∼2 Bcf reduction in methane quantity between 2011 and 2015. This study and presented results showed that the applied methodology and utilized techniques can be used to map GIP and its change within coal seams after degasification, which can further be used for ventilation design for methane control in coal mines.

Optical filter highlighting spectral features part II: quantitative measurements of cosmetic foundation and assessment of their spatial distributions under realistic facial conditions.

PubMed

Nishino, Ken; Nakamura, Mutsuko; Matsumoto, Masayuki; Tanno, Osamu; Nakauchi, Shigeki

2011-03-28

We previously proposed a filter that could detect cosmetic foundations with high discrimination accuracy [Opt. Express 19, 6020 (2011)]. This study extends the filter's functionality to the quantification of the amount of foundation and applies the filter for the assessment of spatial distributions of foundation under realistic facial conditions. Human faces that are applied with quantitatively controlled amounts of cosmetic foundations were measured using the filter. A calibration curve between pixel values of the image and the amount of foundation was created. The optical filter was applied to visualize spatial foundation distributions under realistic facial conditions, which clearly indicated areas on the face where foundation remained even after cleansing. Results confirm that the proposed filter could visualize and nondestructively inspect the foundation distributions.

Fish tracking by combining motion based segmentation and particle filtering

NASA Astrophysics Data System (ADS)

Bichot, E.; Mascarilla, L.; Courtellemont, P.

2006-01-01

In this paper, we suggest a new importance sampling scheme to improve a particle filtering based tracking process. This scheme relies on exploitation of motion segmentation. More precisely, we propagate hypotheses from particle filtering to blobs of similar motion to target. Hence, search is driven toward regions of interest in the state space and prediction is more accurate. We also propose to exploit segmentation to update target model. Once the moving target has been identified, a representative model is learnt from its spatial support. We refer to this model in the correction step of the tracking process. The importance sampling scheme and the strategy to update target model improve the performance of particle filtering in complex situations of occlusions compared to a simple Bootstrap approach as shown by our experiments on real fish tank sequences.

Least squares restoration of multichannel images

NASA Technical Reports Server (NTRS)

Galatsanos, Nikolas P.; Katsaggelos, Aggelos K.; Chin, Roland T.; Hillery, Allen D.

1991-01-01

Multichannel restoration using both within- and between-channel deterministic information is considered. A multichannel image is a set of image planes that exhibit cross-plane similarity. Existing optimal restoration filters for single-plane images yield suboptimal results when applied to multichannel images, since between-channel information is not utilized. Multichannel least squares restoration filters are developed using the set theoretic and the constrained optimization approaches. A geometric interpretation of the estimates of both filters is given. Color images (three-channel imagery with red, green, and blue components) are considered. Constraints that capture the within- and between-channel properties of color images are developed. Issues associated with the computation of the two estimates are addressed. A spatially adaptive, multichannel least squares filter that utilizes local within- and between-channel image properties is proposed. Experiments using color images are described.

Evaluation of spatial filtering on the accuracy of wheat area estimate

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Moreira, M. A.; Chen, S. C.; Delima, A. M.

1982-01-01

A 3 x 3 pixel spatial filter for postclassification was used for wheat classification to evaluate the effects of this procedure on the accuracy of area estimation using LANDSAT digital data obtained from a single pass. Quantitative analyses were carried out in five test sites (approx 40 sq km each) and t tests showed that filtering with threshold values significantly decreased errors of commission and omission. In area estimation filtering improved the overestimate of 4.5% to 2.7% and the root-mean-square error decreased from 126.18 ha to 107.02 ha. Extrapolating the same procedure of automatic classification using spatial filtering for postclassification to the whole study area, the accuracy in area estimate was improved from the overestimate of 10.9% to 9.7%. It is concluded that when single pass LANDSAT data is used for crop identification and area estimation the postclassification procedure using a spatial filter provides a more accurate area estimate by reducing classification errors.

Blending of phased array data

NASA Astrophysics Data System (ADS)

Duijster, Arno; van Groenestijn, Gert-Jan; van Neer, Paul; Blacquière, Gerrit; Volker, Arno

2018-04-01

The use of phased arrays is growing in the non-destructive testing industry and the trend is towards large 2D arrays, but due to limitations, it is currently not possible to record the signals from all elements, resulting in aliased data. In the past, we have presented a data interpolation scheme `beyond spatial aliasing' to overcome this aliasing. In this paper, we present a different approach: blending and deblending of data. On the hardware side, groups of receivers are blended (grouped) in only a few transmit/recording channels. This allows for transmission and recording with all elements, in a shorter acquisition time and with less channels. On the data processing side, this blended data is deblended (separated) by transforming it to a different domain and applying an iterative filtering and thresholding. Two different filtering methods are compared: f-k filtering and wavefield extrapolation filtering. The deblending and filtering methods are demonstrated on simulated experimental data. The wavefield extrapolation filtering proves to outperform f-k filtering. The wavefield extrapolation method can deal with groups of up to 24 receivers, in a phased array of 48 × 48 elements.

Unsupervised classification of operator workload from brain signals

NASA Astrophysics Data System (ADS)

Schultze-Kraft, Matthias; Dähne, Sven; Gugler, Manfred; Curio, Gabriel; Blankertz, Benjamin

2016-06-01

Objective. In this study we aimed for the classification of operator workload as it is expected in many real-life workplace environments. We explored brain-signal based workload predictors that differ with respect to the level of label information required for training, including entirely unsupervised approaches. Approach. Subjects executed a task on a touch screen that required continuous effort of visual and motor processing with alternating difficulty. We first employed classical approaches for workload state classification that operate on the sensor space of EEG and compared those to the performance of three state-of-the-art spatial filtering methods: common spatial patterns (CSPs) analysis, which requires binary label information; source power co-modulation (SPoC) analysis, which uses the subjects’ error rate as a target function; and canonical SPoC (cSPoC) analysis, which solely makes use of cross-frequency power correlations induced by different states of workload and thus represents an unsupervised approach. Finally, we investigated the effects of fusing brain signals and peripheral physiological measures (PPMs) and examined the added value for improving classification performance. Main results. Mean classification accuracies of 94%, 92% and 82% were achieved with CSP, SPoC, cSPoC, respectively. These methods outperformed the approaches that did not use spatial filtering and they extracted physiologically plausible components. The performance of the unsupervised cSPoC is significantly increased by augmenting it with PPM features. Significance. Our analyses ensured that the signal sources used for classification were of cortical origin and not contaminated with artifacts. Our findings show that workload states can be successfully differentiated from brain signals, even when less and less information from the experimental paradigm is used, thus paving the way for real-world applications in which label information may be noisy or entirely unavailable.

A pipeline of spatio-temporal filtering for predicting the laterality of self-initiated fine movements from single trial readiness potentials

NASA Astrophysics Data System (ADS)

Abou Zeid, Elias; Rezazadeh Sereshkeh, Alborz; Chau, Tom

2016-12-01

Objective. In recent years, the readiness potential (RP), a type of pre-movement neural activity, has been investigated for asynchronous electroencephalogram (EEG)-based brain-computer interfaces (BCIs). Since the RP is attenuated for involuntary movements, a BCI driven by RP alone could facilitate intentional control amid a plethora of unintentional movements. Previous studies have attempted single trial classification of RP via spatial and temporal filtering methods, or by combining the RP with event-related desynchronization. However, RP feature extraction remains challenging due to the slow non-oscillatory nature of the potential, its variability among participants and the inherent noise in EEG signals. Here, we propose a participant-specific, individually optimized pipeline of spatio-temporal filtering (PSTF) to improve RP feature extraction for laterality prediction. Approach. PSTF applies band-pass filtering on RP signals, followed by Fisher criterion spatial filtering to maximize class separation, and finally temporal window averaging for feature dimension reduction. Optimal parameters are simultaneously found by cross-validation for each participant. Using EEG data from 14 participants performing self-initiated left or right key presses as well as two benchmark BCI datasets, we compared the performance of PSTF to two popular methods: common spatial subspace decomposition, and adaptive spatio-temporal filtering. Main results. On the BCI benchmark data sets, PSTF performed comparably to both existing methods. With the key press EEG data, PSTF extracted more discriminative features, thereby leading to more accurate (74.99% average accuracy) predictions of RP laterality than that achievable with existing methods. Significance. Naturalistic and volitional interaction with the world is an important capacity that is lost with traditional system-paced BCIs. We demonstrated a significant improvement in fine movement laterality prediction from RP features alone. Our work supports further study of RP-based BCI for intuitive asynchronous control of the environment, such as augmentative communication or wheelchair navigation.

Improved spatial regression analysis of diffusion tensor imaging for lesion detection during longitudinal progression of multiple sclerosis in individual subjects

NASA Astrophysics Data System (ADS)

Liu, Bilan; Qiu, Xing; Zhu, Tong; Tian, Wei; Hu, Rui; Ekholm, Sven; Schifitto, Giovanni; Zhong, Jianhui

2016-03-01

Subject-specific longitudinal DTI study is vital for investigation of pathological changes of lesions and disease evolution. Spatial Regression Analysis of Diffusion tensor imaging (SPREAD) is a non-parametric permutation-based statistical framework that combines spatial regression and resampling techniques to achieve effective detection of localized longitudinal diffusion changes within the whole brain at individual level without a priori hypotheses. However, boundary blurring and dislocation limit its sensitivity, especially towards detecting lesions of irregular shapes. In the present study, we propose an improved SPREAD (dubbed improved SPREAD, or iSPREAD) method by incorporating a three-dimensional (3D) nonlinear anisotropic diffusion filtering method, which provides edge-preserving image smoothing through a nonlinear scale space approach. The statistical inference based on iSPREAD was evaluated and compared with the original SPREAD method using both simulated and in vivo human brain data. Results demonstrated that the sensitivity and accuracy of the SPREAD method has been improved substantially by adapting nonlinear anisotropic filtering. iSPREAD identifies subject-specific longitudinal changes in the brain with improved sensitivity, accuracy, and enhanced statistical power, especially when the spatial correlation is heterogeneous among neighboring image pixels in DTI.

Two-microphone spatial filtering provides speech reception benefits for cochlear implant users in difficult acoustic environments

PubMed Central

Goldsworthy, Raymond L.; Delhorne, Lorraine A.; Desloge, Joseph G.; Braida, Louis D.

2014-01-01

This article introduces and provides an assessment of a spatial-filtering algorithm based on two closely-spaced (∼1 cm) microphones in a behind-the-ear shell. The evaluated spatial-filtering algorithm used fast (∼10 ms) temporal-spectral analysis to determine the location of incoming sounds and to enhance sounds arriving from straight ahead of the listener. Speech reception thresholds (SRTs) were measured for eight cochlear implant (CI) users using consonant and vowel materials under three processing conditions: An omni-directional response, a dipole-directional response, and the spatial-filtering algorithm. The background noise condition used three simultaneous time-reversed speech signals as interferers located at 90°, 180°, and 270°. Results indicated that the spatial-filtering algorithm can provide speech reception benefits of 5.8 to 10.7 dB SRT compared to an omni-directional response in a reverberant room with multiple noise sources. Given the observed SRT benefits, coupled with an efficient design, the proposed algorithm is promising as a CI noise-reduction solution. PMID:25096120

Image enhancement filters significantly improve reading performance for low vision observers

NASA Technical Reports Server (NTRS)

Lawton, T. B.

1992-01-01

As people age, so do their photoreceptors; many photoreceptors in central vision stop functioning when a person reaches their late sixties or early seventies. Low vision observers with losses in central vision, those with age-related maculopathies, were studied. Low vision observers no longer see high spatial frequencies, being unable to resolve fine edge detail. We developed image enhancement filters to compensate for the low vision observer's losses in contrast sensitivity to intermediate and high spatial frequencies. The filters work by boosting the amplitude of the less visible intermediate spatial frequencies. The lower spatial frequencies. These image enhancement filters not only reduce the magnification needed for reading by up to 70 percent, but they also increase the observer's reading speed by 2-4 times. A summary of this research is presented.

Deferred slanted-edge analysis: a unified approach to spatial frequency response measurement on distorted images and color filter array subsets.

PubMed

van den Bergh, F

2018-03-01

The slanted-edge method of spatial frequency response (SFR) measurement is usually applied to grayscale images under the assumption that any distortion of the expected straight edge is negligible. By decoupling the edge orientation and position estimation step from the edge spread function construction step, it is shown in this paper that the slanted-edge method can be extended to allow it to be applied to images suffering from significant geometric distortion, such as produced by equiangular fisheye lenses. This same decoupling also allows the slanted-edge method to be applied directly to Bayer-mosaicked images so that the SFR of the color filter array subsets can be measured directly without the unwanted influence of demosaicking artifacts. Numerical simulation results are presented to demonstrate the efficacy of the proposed deferred slanted-edge method in relation to existing methods.

Next generation miniature simultaneous multi-hyperspectral imaging systems

NASA Astrophysics Data System (ADS)

Hinnrichs, Michele; Gupta, Neelam

2014-03-01

The concept for a hyperspectral imaging system using a Fabry-Perot tunable filter (FPTF) array that is fabricated using "miniature optical electrical mechanical system" (MOEMS) technology. [1] Using an array of FPTF as an approach to hyperspectral imaging relaxes wavelength tuning requirements considerably because of the reduced portion of the spectrum that is covered by each element in the array. In this paper, Pacific Advanced Technology and ARL present the results of a concept design and performed analysis of a MOEMS based tunable Fabry-Perot array (FPTF) to perform simultaneous multispectral and hyperspectral imaging with relatively high spatial resolution. The concept design was developed with support of an Army SBIR Phase I program The Fabry-Perot tunable MOEMS filter array was combined with a miniature optics array and a focal plane array of 1024 x 1024 pixels to produce 16 colors every frame of the camera. Each color image has a spatial resolution of 256 x 256 pixels with an IFOV of 1.7 mrads and FOV of 25 degrees. The spectral images are collected simultaneously allowing high resolution spectral-spatial-temporal information in each frame of the camera, thus enabling the implementation of spectral-temporal-spatial algorithms in real-time to provide high sensitivity for the detection of weak signals in a high clutter background environment with low sensitivity to camera motion. The challenge in the design was the independent actuation of each Fabry Perot element in the array allowing for individual tuning. An additional challenge was the need to maximize the fill factor to improve the spatial coverage with minimal dead space. This paper will only address the concept design and analysis of the Fabry-Perot tunable filter array. A previous paper presented at SPIE DSS in 2012 explained the design of the optical array.

Object motion analysis study

NASA Technical Reports Server (NTRS)

1974-01-01

The use of optical data processing (ODP) techniques for motion analysis in two-dimensional imagery was studied. The basic feasibility of this approach was demonstrated, but inconsistent performance of the photoplastic used for recording spatial filters prevented totally automatic operation. Promising solutions to the problems encountered are discussed, and it is concluded that ODP techniques could be quite useful for motion analysis.

High resolution quantitative phase imaging of live cells with constrained optimization approach

NASA Astrophysics Data System (ADS)

Pandiyan, Vimal Prabhu; Khare, Kedar; John, Renu

2016-03-01

Quantitative phase imaging (QPI) aims at studying weakly scattering and absorbing biological specimens with subwavelength accuracy without any external staining mechanisms. Use of a reference beam at an angle is one of the necessary criteria for recording of high resolution holograms in most of the interferometric methods used for quantitative phase imaging. The spatial separation of the dc and twin images is decided by the reference beam angle and Fourier-filtered reconstructed image will have a very poor resolution if hologram is recorded below a minimum reference angle condition. However, it is always inconvenient to have a large reference beam angle while performing high resolution microscopy of live cells and biological specimens with nanometric features. In this paper, we treat reconstruction of digital holographic microscopy images as a constrained optimization problem with smoothness constraint in order to recover only complex object field in hologram plane even with overlapping dc and twin image terms. We solve this optimization problem by gradient descent approach iteratively and the smoothness constraint is implemented by spatial averaging with appropriate size. This approach will give excellent high resolution image recovery compared to Fourier filtering while keeping a very small reference angle. We demonstrate this approach on digital holographic microscopy of live cells by recovering the quantitative phase of live cells from a hologram recorded with nearly zero reference angle.

Effects of Spatial and Non-Spatial Multi-Modal Cues on Orienting of Visual-Spatial Attention in an Augmented Environment

DTIC Science & Technology

2007-11-01

information into awareness. Broadbent’s (1958) " Filter " model of attention (see Figure 1) maps the flow of information from the senses through a number of...benefits of an attentional cueing paradigm can be explained within these models . For example, the selective filter is augmented by the information...capacity filter ’, while Wickens’ model represents this with a limited amount of ’attentional resources’ available to perception, decision making

Two-Microphone Spatial Filtering Improves Speech Reception for Cochlear-Implant Users in Reverberant Conditions With Multiple Noise Sources

PubMed Central

2014-01-01

This study evaluates a spatial-filtering algorithm as a method to improve speech reception for cochlear-implant (CI) users in reverberant environments with multiple noise sources. The algorithm was designed to filter sounds using phase differences between two microphones situated 1 cm apart in a behind-the-ear hearing-aid capsule. Speech reception thresholds (SRTs) were measured using a Coordinate Response Measure for six CI users in 27 listening conditions including each combination of reverberation level (T60 = 0, 270, and 540 ms), number of noise sources (1, 4, and 11), and signal-processing algorithm (omnidirectional response, dipole-directional response, and spatial-filtering algorithm). Noise sources were time-reversed speech segments randomly drawn from the Institute of Electrical and Electronics Engineers sentence recordings. Target speech and noise sources were processed using a room simulation method allowing precise control over reverberation times and sound-source locations. The spatial-filtering algorithm was found to provide improvements in SRTs on the order of 6.5 to 11.0 dB across listening conditions compared with the omnidirectional response. This result indicates that such phase-based spatial filtering can improve speech reception for CI users even in highly reverberant conditions with multiple noise sources. PMID:25330772

A combination of spatial and recursive temporal filtering for noise reduction when using region of interest (ROI) fluoroscopy for patient dose reduction in image guided vascular interventions with significant anatomical motion

NASA Astrophysics Data System (ADS)

Setlur Nagesh, S. V.; Khobragade, P.; Ionita, C.; Bednarek, D. R.; Rudin, S.

2015-03-01

Because x-ray based image-guided vascular interventions are minimally invasive they are currently the most preferred method of treating disorders such as stroke, arterial stenosis, and aneurysms; however, the x-ray exposure to the patient during long image-guided interventional procedures could cause harmful effects such as cancer in the long run and even tissue damage in the short term. ROI fluoroscopy reduces patient dose by differentially attenuating the incident x-rays outside the region-of-interest. To reduce the noise in the dose-reduced regions previously recursive temporal filtering was successfully demonstrated for neurovascular interventions. However, in cardiac interventions, anatomical motion is significant and excessive recursive filtering could cause blur. In this work the effects of three noise-reduction schemes, including recursive temporal filtering, spatial mean filtering, and a combination of spatial and recursive temporal filtering, were investigated in a simulated ROI dose-reduced cardiac intervention. First a model to simulate the aortic arch and its movement was built. A coronary stent was used to simulate a bioprosthetic valve used in TAVR procedures and was deployed under dose-reduced ROI fluoroscopy during the simulated heart motion. The images were then retrospectively processed for noise reduction in the periphery, using recursive temporal filtering, spatial filtering and a combination of both. Quantitative metrics for all three noise reduction schemes are calculated and are presented as results. From these it can be concluded that with significant anatomical motion, a combination of spatial and recursive temporal filtering scheme is best suited for reducing the excess quantum noise in the periphery. This new noise-reduction technique in combination with ROI fluoroscopy has the potential for substantial patient-dose savings in cardiac interventions.

Recursive inverse kinematics for robot arms via Kalman filtering and Bryson-Frazier smoothing

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Scheid, R. E., Jr.

1987-01-01

This paper applies linear filtering and smoothing theory to solve recursively the inverse kinematics problem for serial multilink manipulators. This problem is to find a set of joint angles that achieve a prescribed tip position and/or orientation. A widely applicable numerical search solution is presented. The approach finds the minimum of a generalized distance between the desired and the actual manipulator tip position and/or orientation. Both a first-order steepest-descent gradient search and a second-order Newton-Raphson search are developed. The optimal relaxation factor required for the steepest descent method is computed recursively using an outward/inward procedure similar to those used typically for recursive inverse dynamics calculations. The second-order search requires evaluation of a gradient and an approximate Hessian. A Gauss-Markov approach is used to approximate the Hessian matrix in terms of products of first-order derivatives. This matrix is inverted recursively using a two-stage process of inward Kalman filtering followed by outward smoothing. This two-stage process is analogous to that recently developed by the author to solve by means of spatial filtering and smoothing the forward dynamics problem for serial manipulators.

Enhancement of flow measurements using fluid-dynamic constraints

NASA Astrophysics Data System (ADS)

Egger, H.; Seitz, T.; Tropea, C.

2017-09-01

Novel experimental modalities acquire spatially resolved velocity measurements for steady state and transient flows which are of interest for engineering and biological applications. One of the drawbacks of such high resolution velocity data is their susceptibility to measurement errors. In this paper, we propose a novel filtering strategy that allows enhancement of the noisy measurements to obtain reconstruction of smooth divergence free velocity and corresponding pressure fields which together approximately comply to a prescribed flow model. The main step in our approach consists of the appropriate use of the velocity measurements in the design of a linearized flow model which can be shown to be well-posed and consistent with the true velocity and pressure fields up to measurement and modeling errors. The reconstruction procedure is then formulated as an optimal control problem for this linearized flow model. The resulting filter has analyzable smoothing and approximation properties. We briefly discuss the discretization of the approach by finite element methods and comment on the efficient solution by iterative methods. The capability of the proposed filter to significantly reduce data noise is demonstrated by numerical tests including the application to experimental data. In addition, we compare with other methods like smoothing and solenoidal filtering.

Unsupervised classification of operator workload from brain signals.

PubMed

Schultze-Kraft, Matthias; Dähne, Sven; Gugler, Manfred; Curio, Gabriel; Blankertz, Benjamin

2016-06-01

In this study we aimed for the classification of operator workload as it is expected in many real-life workplace environments. We explored brain-signal based workload predictors that differ with respect to the level of label information required for training, including entirely unsupervised approaches. Subjects executed a task on a touch screen that required continuous effort of visual and motor processing with alternating difficulty. We first employed classical approaches for workload state classification that operate on the sensor space of EEG and compared those to the performance of three state-of-the-art spatial filtering methods: common spatial patterns (CSPs) analysis, which requires binary label information; source power co-modulation (SPoC) analysis, which uses the subjects' error rate as a target function; and canonical SPoC (cSPoC) analysis, which solely makes use of cross-frequency power correlations induced by different states of workload and thus represents an unsupervised approach. Finally, we investigated the effects of fusing brain signals and peripheral physiological measures (PPMs) and examined the added value for improving classification performance. Mean classification accuracies of 94%, 92% and 82% were achieved with CSP, SPoC, cSPoC, respectively. These methods outperformed the approaches that did not use spatial filtering and they extracted physiologically plausible components. The performance of the unsupervised cSPoC is significantly increased by augmenting it with PPM features. Our analyses ensured that the signal sources used for classification were of cortical origin and not contaminated with artifacts. Our findings show that workload states can be successfully differentiated from brain signals, even when less and less information from the experimental paradigm is used, thus paving the way for real-world applications in which label information may be noisy or entirely unavailable.

The Spatial Vision Tree: A Generic Pattern Recognition Engine- Scientific Foundations, Design Principles, and Preliminary Tree Design

NASA Technical Reports Server (NTRS)

Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

2010-01-01

New foundational ideas are used to define a novel approach to generic visual pattern recognition. These ideas proceed from the starting point of the intrinsic equivalence of noise reduction and pattern recognition when noise reduction is taken to its theoretical limit of explicit matched filtering. This led us to think of the logical extension of sparse coding using basis function transforms for both de-noising and pattern recognition to the full pattern specificity of a lexicon of matched filter pattern templates. A key hypothesis is that such a lexicon can be constructed and is, in fact, a generic visual alphabet of spatial vision. Hence it provides a tractable solution for the design of a generic pattern recognition engine. Here we present the key scientific ideas, the basic design principles which emerge from these ideas, and a preliminary design of the Spatial Vision Tree (SVT). The latter is based upon a cryptographic approach whereby we measure a large aggregate estimate of the frequency of occurrence (FOO) for each pattern. These distributions are employed together with Hamming distance criteria to design a two-tier tree. Then using information theory, these same FOO distributions are used to define a precise method for pattern representation. Finally the experimental performance of the preliminary SVT on computer generated test images and complex natural images is assessed.

Reducing multi-sensor data to a single time course that reveals experimental effects

PubMed Central

2013-01-01

Background Multi-sensor technologies such as EEG, MEG, and ECoG result in high-dimensional data sets. Given the high temporal resolution of such techniques, scientific questions very often focus on the time-course of an experimental effect. In many studies, researchers focus on a single sensor or the average over a subset of sensors covering a “region of interest” (ROI). However, single-sensor or ROI analyses ignore the fact that the spatial focus of activity is constantly changing, and fail to make full use of the information distributed over the sensor array. Methods We describe a technique that exploits the optimality and simplicity of matched spatial filters in order to reduce experimental effects in multivariate time series data to a single time course. Each (multi-sensor) time sample of each trial is replaced with its projection onto a spatial filter that is matched to an observed experimental effect, estimated from the remaining trials (Effect-Matched Spatial filtering, or EMS filtering). The resulting set of time courses (one per trial) can be used to reveal the temporal evolution of an experimental effect, which distinguishes this approach from techniques that reveal the temporal evolution of an anatomical source or region of interest. Results We illustrate the technique with data from a dual-task experiment and use it to track the temporal evolution of brain activity during the psychological refractory period. We demonstrate its effectiveness in separating the means of two experimental conditions, and in significantly improving the signal-to-noise ratio at the single-trial level. It is fast to compute and results in readily-interpretable time courses and topographies. The technique can be applied to any data-analysis question that can be posed independently at each sensor, and we provide one example, using linear regression, that highlights the versatility of the technique. Conclusion The approach described here combines established techniques in a way that strikes a balance between power, simplicity, speed of processing, and interpretability. We have used it to provide a direct view of parallel and serial processes in the human brain that previously could only be measured indirectly. An implementation of the technique in MatLab is freely available via the internet. PMID:24125590

Investigation on filter method for smoothing spiral phase plate

NASA Astrophysics Data System (ADS)

Zhang, Yuanhang; Wen, Shenglin; Luo, Zijian; Tang, Caixue; Yan, Hao; Yang, Chunlin; Liu, Mincai; Zhang, Qinghua; Wang, Jian

2018-03-01

Spiral phase plate (SPP) for generating vortex hollow beams has high efficiency in various applications. However, it is difficult to obtain an ideal spiral phase plate because of its continuous-varying helical phase and discontinued phase step. This paper describes the demonstration of continuous spiral phase plate using filter methods. The numerical simulations indicate that different filter method including spatial domain filter, frequency domain filter has unique impact on surface topography of SPP and optical vortex characteristics. The experimental results reveal that the spatial Gaussian filter method for smoothing SPP is suitable for Computer Controlled Optical Surfacing (CCOS) technique and obtains good optical properties.

The spatial resolution of a rotating gamma camera tomographic facility.

PubMed

Webb, S; Flower, M A; Ott, R J; Leach, M O; Inamdar, R

1983-12-01

An important feature determining the spatial resolution in transverse sections reconstructed by convolution and back-projection is the frequency filter corresponding to the convolution kernel. Equations have been derived giving the theoretical spatial resolution, for a perfect detector and noise-free data, using four filter functions. Experiments have shown that physical constraints will always limit the resolution that can be achieved with a given system. The experiments indicate that the region of the frequency spectrum between KN/2 and KN where KN is the Nyquist frequency does not contribute significantly to resolution. In order to investigate the physical effect of these filter functions, the spatial resolution of reconstructed images obtained with a GE 400T rotating gamma camera has been measured. The results obtained serve as an aid to choosing appropriate reconstruction filters for use with a rotating gamma camera system.

Laser tweezer actuated microphotonic array devices for high resolution imaging and analysis in chip-based biosystems

NASA Astrophysics Data System (ADS)

Birkbeck, Aaron L.

A new technology is developed that functionally integrates arrays of lasers and micro-optics into microfluidic systems for the purpose of imaging, analyzing, and manipulating objects and biological cells. In general, the devices and technologies emerging from this area either lack functionality through the reliance on mechanical systems or provide a serial-based, time consuming approach. As compared to the current state of art, our all-optical design methodology has several distinguishing features, such as parallelism, high efficiency, low power, auto-alignment, and high yield fabrication methods, which all contribute to minimizing the cost of the integration process. The potential use of vertical cavity surface emitting lasers (VCSELs) for the creation of two-dimensional arrays of laser optical tweezers that perform independently controlled, parallel capture, and transport of large numbers of individual objects and biological cells is investigated. One of the primary biological applications for which VCSEL array sourced laser optical tweezers are considered is the formation of engineered tissues through the manipulation and spatial arrangement of different types of cells in a co-culture. Creating devices that combine laser optical tweezers with select micro-optical components permits optical imaging and analysis functions to take place inside the microfluidic channel. One such device is a micro-optical spatial filter whose motion and alignment is controlled using a laser optical tweezer. Unlike conventional spatial filter systems, our device utilizes a refractive optical element that is directly incorporated onto the lithographically patterned spatial filter. This allows the micro-optical spatial filter to automatically align itself in three-dimensions to the focal point of the microscope objective, where it then filters out the higher frequency additive noise components present in the laser beam. As a means of performing high resolution imaging in the microfluidic channel, we developed a novel technique that integrates the capacity of a laser tweezer to optically trap and manipulate objects in three-dimensions with the resolution-enhanced imaging capabilities of a solid immersion lens (SIL). In our design, the SIL is a free-floating device whose imaging beam, motion control and alignment is provided by a laser optical tweezer, which allows the microfluidic SIL to image in areas that are inaccessible to traditional solid immersion microscopes.

Denoising Algorithm for CFA Image Sensors Considering Inter-Channel Correlation.

PubMed

Lee, Min Seok; Park, Sang Wook; Kang, Moon Gi

2017-05-28

In this paper, a spatio-spectral-temporal filter considering an inter-channel correlation is proposed for the denoising of a color filter array (CFA) sequence acquired by CCD/CMOS image sensors. Owing to the alternating under-sampled grid of the CFA pattern, the inter-channel correlation must be considered in the direct denoising process. The proposed filter is applied in the spatial, spectral, and temporal domain, considering the spatio-tempo-spectral correlation. First, nonlocal means (NLM) spatial filtering with patch-based difference (PBD) refinement is performed by considering both the intra-channel correlation and inter-channel correlation to overcome the spatial resolution degradation occurring with the alternating under-sampled pattern. Second, a motion-compensated temporal filter that employs inter-channel correlated motion estimation and compensation is proposed to remove the noise in the temporal domain. Then, a motion adaptive detection value controls the ratio of the spatial filter and the temporal filter. The denoised CFA sequence can thus be obtained without motion artifacts. Experimental results for both simulated and real CFA sequences are presented with visual and numerical comparisons to several state-of-the-art denoising methods combined with a demosaicing method. Experimental results confirmed that the proposed frameworks outperformed the other techniques in terms of the objective criteria and subjective visual perception in CFA sequences.

Median Filter Noise Reduction of Image and Backpropagation Neural Network Model for Cervical Cancer Classification

NASA Astrophysics Data System (ADS)

Wutsqa, D. U.; Marwah, M.

2017-06-01

In this paper, we consider spatial operation median filter to reduce the noise in the cervical images yielded by colposcopy tool. The backpropagation neural network (BPNN) model is applied to the colposcopy images to classify cervical cancer. The classification process requires an image extraction by using a gray level co-occurrence matrix (GLCM) method to obtain image features that are used as inputs of BPNN model. The advantage of noise reduction is evaluated by comparing the performances of BPNN models with and without spatial operation median filter. The experimental result shows that the spatial operation median filter can improve the accuracy of the BPNN model for cervical cancer classification.

Optimizing spatial patterns with sparse filter bands for motor-imagery based brain-computer interface.

PubMed

Zhang, Yu; Zhou, Guoxu; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

2015-11-30

Common spatial pattern (CSP) has been most popularly applied to motor-imagery (MI) feature extraction for classification in brain-computer interface (BCI) application. Successful application of CSP depends on the filter band selection to a large degree. However, the most proper band is typically subject-specific and can hardly be determined manually. This study proposes a sparse filter band common spatial pattern (SFBCSP) for optimizing the spatial patterns. SFBCSP estimates CSP features on multiple signals that are filtered from raw EEG data at a set of overlapping bands. The filter bands that result in significant CSP features are then selected in a supervised way by exploiting sparse regression. A support vector machine (SVM) is implemented on the selected features for MI classification. Two public EEG datasets (BCI Competition III dataset IVa and BCI Competition IV IIb) are used to validate the proposed SFBCSP method. Experimental results demonstrate that SFBCSP help improve the classification performance of MI. The optimized spatial patterns by SFBCSP give overall better MI classification accuracy in comparison with several competing methods. The proposed SFBCSP is a potential method for improving the performance of MI-based BCI. Copyright © 2015 Elsevier B.V. All rights reserved.

Application of the Radon-FCL approach to seismic random noise suppression and signal preservation

NASA Astrophysics Data System (ADS)

Meng, Fanlei; Li, Yue; Liu, Yanping; Tian, Yanan; Wu, Ning

2016-08-01

The fractal conservation law (FCL) is a linear partial differential equation that is modified by an anti-diffusive term of lower order. The analysis indicated that this algorithm could eliminate high frequencies and preserve or amplify low/medium-frequencies. Thus, this method is quite suitable for the simultaneous noise suppression and enhancement or preservation of seismic signals. However, the conventional FCL filters seismic data only along the time direction, thereby ignoring the spatial coherence between neighbouring traces, which leads to the loss of directional information. Therefore, we consider the development of the conventional FCL into the time-space domain and propose a Radon-FCL approach. We applied a Radon transform to implement the FCL method in this article; performing FCL filtering in the Radon domain achieves a higher level of noise attenuation. Using this method, seismic reflection events can be recovered with the sacrifice of fewer frequency components while effectively attenuating more random noise than conventional FCL filtering. Experiments using both synthetic and common shot point data demonstrate the advantages of the Radon-FCL approach versus the conventional FCL method with regard to both random noise attenuation and seismic signal preservation.

Effects of spatial frequency content on classification of face gender and expression.

PubMed

Aguado, Luis; Serrano-Pedraza, Ignacio; Rodríguez, Sonia; Román, Francisco J

2010-11-01

The role of different spatial frequency bands on face gender and expression categorization was studied in three experiments. Accuracy and reaction time were measured for unfiltered, low-pass (cut-off frequency of 1 cycle/deg) and high-pass (cutoff frequency of 3 cycles/deg) filtered faces. Filtered and unfiltered faces were equated in root-mean-squared contrast. For low-pass filtered faces reaction times were higher than unfiltered and high-pass filtered faces in both categorization tasks. In the expression task, these results were obtained with expressive faces presented in isolation (Experiment 1) and also with neutral-expressive dynamic sequences where each expressive face was preceded by a briefly presented neutral version of the same face (Experiment 2). For high-pass filtered faces different effects were observed on gender and expression categorization. While both speed and accuracy of gender categorization were reduced comparing to unfiltered faces, the efficiency of expression classification remained similar. Finally, we found no differences between expressive and non expressive faces in the effects of spatial frequency filtering on gender categorization (Experiment 3). These results show a common role of information from the high spatial frequency band in the categorization of face gender and expression.

Assessing mass change trends in GRACE models

NASA Astrophysics Data System (ADS)

Siemes, C.; Liu, X.; Ditmar, P.; Revtova, E.; Slobbe, C.; Klees, R.; Zhao, Q.

2009-04-01

The DEOS Mass Transport model, release 1 (DMT-1), has been recently presented to the scientific community. The model is based on GRACE data and consists of sets of spherical harmonic coefficients to degree 120, which are estimated once per month. Currently, the DMT-1 model covers the time span from Feb. 2003 to Dec. 2006. The high spatial resolution of the model could be achieved by applying a statistically optimal Wiener-type filter, which is superior to standard filtering techniques. The optimal Wiener-type filter is a regularization-type filter which makes full use of the variance/covariance matrices of the sets of spherical harmonic coefficients. It can be shown that applying this filter is equivalent to introducing an additional set of observations: Each set of spherical harmonic coefficients is assumed to be zero. The variance/covariance matrix of this information is chosen according to the signal contained within the sets of spherical harmonic coefficients, expressed in terms of equivalent water layer thickness in the spatial domain, with respect to its variations in time. It will be demonstrated that DMT-1 provides a much better localization and more realistic amplitudes than alternative filtered models. In particular, we will consider a lower maximum degree of the spherical harmonic expansion (e.g. 70), as well as standard filters like an isotropic Gaussian filter. For the sake of a fair comparison, we will use the same GRACE observations as well as the same method for the inversion of the observations to obtain the alternative filtered models. For the inversion method, we will choose the three-point range combination approach. Thus, we will compare four different models: (1) GRACE solution with maximum degree 120, filtered by optimal Wiener-type filter (the DMT-1 model) (2) GRACE solution with maximum degree 120, filtered by standard filter (3) GRACE solution with maximum degree 70, filtered by optimal Wiener-type filter (4) GRACE solution with maximum degree 70, filtered by standard filter Within the comparison, we will focus on the amplitude of long-term mass change signals with respect to spatial resolution. The challenge for the recovery of such signals from GRACE based solutions results from the fact that the solutions must be filtered and that filtering of always smoothes not only noise, but also to some extend signal. Since the observation density is much higher near the poles than at the equator, which is due to the orbits of the GRACE satellites, we expect that the magnitude of estimated mass change signals in polar areas is less underestimated than in equatorial areas. For this reason will investigate trends at locations in equatorial areas as well as trends at locations in polar areas. In particular, we will investigate Lake Victoria, Lake Malawi and Lake Tanganyika, which are all located in Eastern Africa, near to the equator. Furthermore, we will show trends of two locations at the South-East coast of Greenland, Abbot Ice-Shelf and Marie-Byrd-Land in Antarctica For validation, we use water level variations in Lake Victoria (69000 km2), Lake Malawi (29000 km2) and Lake Tanganyika (33000 km2) as ground truth. The water level, which is measured by satellite radar altimetry, decreases at a rate of approximately 47 cm in Lake Victoria, 42 cm in Lake Malawi and 30 cm in Lake Tanganyika over the period from Feb. 2003 to Dec. 2006. Because all three lakes are located in tropical and subtropical clime, the mass change signal will consist of large seasonal variations in addition to the trend component we are interested in. However, also the amplitude of estimated seasonal variations can be used as an indicator of the quality of the models within the comparison. Since the lakes' areas are at the edge of the spatial resolution GRACE data can provide, they are a good example of the advantages of high-resolution mass change models like DMT-1.

The Variability of the Horizontal Circulation in the Troposphere and Stratosphere: A Comparison

NASA Technical Reports Server (NTRS)

Perlwitz, Judith; Graf, Hans-F.; Hansem, James E. (Technical Monitor)

2001-01-01

The variability of the horizontal circulation in the stratosphere and troposphere of the Northern Hemisphere (NH) is compared by using various approaches. Spatial degrees of freedom (dof) on different time scales were derived. Modes of variability were computed in geopotential height fields at the tropospheric and stratospheric pressure levels by applying multivariate statistical approaches. Features of the spatial and temporal variability of the winterly zonal wind were studied with the help of recurrence and persistence analyses. The geopotential height and zonally-averaged zonal wind at the 50-, 500- and 1000-hPa level are used to investigate the behavior of the horizontal circulation in the lower stratosphere, mid-troposphere and at the near surface level, respectively. It is illustrated that the features of the variability of the horizontal circulation are very similar in the mid-troposphere and at the near surface level. Due to the filtering of tropospheric disturbances by the stratospheric and upper tropospheric zonal mean flow, the variability of the stratospheric circulation exhibits less spatial complexity than the circulation at tropospheric pressure levels. There exist enormous differences in the number of degrees of freedom (or free variability modes) between both atmospheric layers. Results of the analyses clearly show that the concept of a zonally symmetric AO with a simple structure in the troposphere similar to the one in the stratosphere is not valid. It is concluded that the spatially filtered climate change signal can be detected earlier in the stratosphere than in the mid-troposphere or at the near surface level.

Optical ranked-order filtering using threshold decomposition

DOEpatents

Allebach, Jan P.; Ochoa, Ellen; Sweeney, Donald W.

1990-01-01

A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed.

Stretchable Dry Electrodes with Concentric Ring Geometry for Enhancing Spatial Resolution in Electrophysiology.

PubMed

Wang, Kaiping; Parekh, Udit; Pailla, Tejaswy; Garudadri, Harinath; Gilja, Vikash; Ng, Tse Nga

2017-10-01

The multichannel concentric-ring electrodes are stencil printed on stretchable elastomers modified to improve adhesion to skin and minimize motion artifacts for electrophysiological recordings of electroencephalography, electromyography, and electrocardiography. These dry electrodes with a poly(3,4-ethylenedioxythiophene) polystyrene sulfonate interface layer are optimized to show lower noise level than that of commercial gel disc electrodes. The concentric ring geometry enables Laplacian filtering to pinpoint the bioelectric potential source with spatial resolution determined by the ring distance. This work shows a new fabrication approach to integrate and create designs that enhance spatial resolution for high-quality electrophysiology monitoring devices. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Performance of Low Dissipative High Order Shock-Capturing Schemes for Shock-Turbulence Interactions

NASA Technical Reports Server (NTRS)

Sandham, N. D.; Yee, H. C.

1998-01-01

Accurate and efficient direct numerical simulation of turbulence in the presence of shock waves represents a significant challenge for numerical methods. The objective of this paper is to evaluate the performance of high order compact and non-compact central spatial differencing employing total variation diminishing (TVD) shock-capturing dissipations as characteristic based filters for two model problems combining shock wave and shear layer phenomena. A vortex pairing model evaluates the ability of the schemes to cope with shear layer instability and eddy shock waves, while a shock wave impingement on a spatially-evolving mixing layer model studies the accuracy of computation of vortices passing through a sequence of shock and expansion waves. A drastic increase in accuracy is observed if a suitable artificial compression formulation is applied to the TVD dissipations. With this modification to the filter step the fourth-order non-compact scheme shows improved results in comparison to second-order methods, while retaining the good shock resolution of the basic TVD scheme. For this characteristic based filter approach, however, the benefits of compact schemes or schemes with higher than fourth order are not sufficient to justify the higher complexity near the boundary and/or the additional computational cost.

Evaluation of rosette infrasonic noise-reducing spatial filters.

PubMed

Hedlin, Michael A H; Alcoverro, Benoit; D'Spain, Gerald

2003-10-01

This paper presents results from recent tests of rosette infrasonic noise-reducing spatial filters at the Pinon Flat Observatory in southern California. Data from 18- and 70-m aperture rosette filters and a reference port are used to gauge the reduction in atmospheric wind-generated noise levels provided by the filters and to examine the effect of these spatial filters on spatially coherent acoustic signals in the 0.02- to 10-Hz band. At wind speeds up to 5.5 m/s, the 18-m rosette filter reduces wind noise levels above 0.2 Hz by 15 to 20 dB. Under the same conditions, the 70-m rosette filter provides noise reduction of up to 15 to 20 dB between 0.02 and 0.7 Hz. Standing wave resonance inside the 70-m filter degrades the reception of acoustic signals above 0.7 Hz. The fundamental mode of the resonance, 15 dB above background, is centered at 2.65-Hz and the first odd harmonic is observed at 7.95 Hz in data from the large filter. Analytical simulations accurately reproduce the noise reduction and resonance observed in the 70-m filter at all wind speeds above 1.25 m/s. Resonance theory indicates that internal reflections that give rise to the resonance observed in the passband are occurring at the summing manifolds, and not at the inlets. Rosette filters are designed for acoustic arrivals with infinite phase velocity. The plane-wave response of the 70-m rosette filter has a strong dependence on frequency above 3.5 Hz at grazing angles of less than 15 degrees from the horizontal. At grazing angles, complete cancellation of the signal occurs at 5 Hz. Theoretical predictions of the phase and amplitude response of 18- and 70-m rosette filters, that take into account internal resonance and time delays between the inlets, compare favorably with observations derived from a cross-spectral analysis of signals from the explosion of a large bolide.

Approximate deconvolution model for the simulation of turbulent gas-solid flows: An a priori analysis

NASA Astrophysics Data System (ADS)

Schneiderbauer, Simon; Saeedipour, Mahdi

2018-02-01

Highly resolved two-fluid model (TFM) simulations of gas-solid flows in vertical periodic channels have been performed to study closures for the filtered drag force and the Reynolds-stress-like contribution stemming from the convective terms. An approximate deconvolution model (ADM) for the large-eddy simulation of turbulent gas-solid suspensions is detailed and subsequently used to reconstruct those unresolved contributions in an a priori manner. With such an approach, an approximation of the unfiltered solution is obtained by repeated filtering allowing the determination of the unclosed terms of the filtered equations directly. A priori filtering shows that predictions of the ADM model yield fairly good agreement with the fine grid TFM simulations for various filter sizes and different particle sizes. In particular, strong positive correlation (ρ > 0.98) is observed at intermediate filter sizes for all sub-grid terms. Additionally, our study reveals that the ADM results moderately depend on the choice of the filters, such as box and Gaussian filter, as well as the deconvolution order. The a priori test finally reveals that ADM is superior compared to isotropic functional closures proposed recently [S. Schneiderbauer, "A spatially-averaged two-fluid model for dense large-scale gas-solid flows," AIChE J. 63, 3544-3562 (2017)].

Towards real-time non contact spatial resolved oxygenation monitoring using a multi spectral filter array camera in various light conditions

NASA Astrophysics Data System (ADS)

Bauer, Jacob R.; van Beekum, Karlijn; Klaessens, John; Noordmans, Herke Jan; Boer, Christa; Hardeberg, Jon Y.; Verdaasdonk, Rudolf M.

2018-02-01

Non contact spatial resolved oxygenation measurements remain an open challenge in the biomedical field and non contact patient monitoring. Although point measurements are the clinical standard till this day, regional differences in the oxygenation will improve the quality and safety of care. Recent developments in spectral imaging resulted in spectral filter array cameras (SFA). These provide the means to acquire spatial spectral videos in real-time and allow a spatial approach to spectroscopy. In this study, the performance of a 25 channel near infrared SFA camera was studied to obtain spatial oxygenation maps of hands during an occlusion of the left upper arm in 7 healthy volunteers. For comparison a clinical oxygenation monitoring system, INVOS, was used as a reference. In case of the NIRS SFA camera, oxygenation curves were derived from 2-3 wavelength bands with a custom made fast analysis software using a basic algorithm. Dynamic oxygenation changes were determined with the NIR SFA camera and INVOS system at different regional locations of the occluded versus non-occluded hands and showed to be in good agreement. To increase the signal to noise ratio, algorithm and image acquisition were optimised. The measurement were robust to different illumination conditions with NIR light sources. This study shows that imaging of relative oxygenation changes over larger body areas is potentially possible in real time.

The modulation transfer function and signal-to-noise ratio of different digital filters: a technical approach.

PubMed

Brüllmann, D D; d'Hoedt, B

2011-05-01

The aim of this study was to illustrate the influence of digital filters on the signal-to-noise ratio (SNR) and modulation transfer function (MTF) of digital images. The article will address image pre-processing that may be beneficial for the production of clinically useful digital radiographs with lower radiation dose. Three filters, an arithmetic mean filter, a median filter and a Gaussian filter (standard deviation (SD) = 0.4), with kernel sizes of 3 × 3 pixels and 5 × 5 pixels were tested. Synthetic images with exactly increasing amounts of Gaussian noise were created to gather linear regression of SNR before and after application of digital filters. Artificial stripe patterns with defined amounts of line pairs per millimetre were used to calculate MTF before and after the application of the digital filters. The Gaussian filter with a 5 × 5 kernel size caused the highest noise suppression (SNR increased from 2.22, measured in the synthetic image, to 11.31 in the filtered image). The smallest noise reduction was found with the 3 × 3 median filter. The application of the median filters resulted in no changes in MTF at the different resolutions but did result in the deletion of smaller structures. The 5 × 5 Gaussian filter and the 5 × 5 arithmetic mean filter showed the strongest changes of MTF. The application of digital filters can improve the SNR of a digital sensor; however, MTF can be adversely affected. As such, imaging systems should not be judged solely on their quoted spatial resolutions because pre-processing may influence image quality.

Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matenine, Dmitri, E-mail: dmitri.matenine.1@ulaval.ca; Mascolo-Fortin, Julia, E-mail: julia.mascolo-fortin.1@ulaval.ca; Goussard, Yves, E-mail: yves.goussard@polymtl.ca

Purpose: The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. Methods: This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numericalmore » simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. Results: The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. Conclusions: The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.« less

Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT.

PubMed

Matenine, Dmitri; Mascolo-Fortin, Julia; Goussard, Yves; Després, Philippe

2015-11-01

The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.

Detection of small surface defects using DCT based enhancement approach in machine vision systems

NASA Astrophysics Data System (ADS)

He, Fuqiang; Wang, Wen; Chen, Zichen

2005-12-01

Utilizing DCT based enhancement approach, an improved small defect detection algorithm for real-time leather surface inspection was developed. A two-stage decomposition procedure was proposed to extract an odd-odd frequency matrix after a digital image has been transformed to DCT domain. Then, the reverse cumulative sum algorithm was proposed to detect the transition points of the gentle curves plotted from the odd-odd frequency matrix. The best radius of the cutting sector was computed in terms of the transition points and the high-pass filtering operation was implemented. The filtered image was then inversed and transformed back to the spatial domain. Finally, the restored image was segmented by an entropy method and some defect features are calculated. Experimental results show the proposed small defect detection method can reach the small defect detection rate by 94%.

Effect of different thickness of material filter on Tc-99m spectra and performance parameters of gamma camera

NASA Astrophysics Data System (ADS)

Nazifah, A.; Norhanna, S.; Shah, S. I.; Zakaria, A.

2014-11-01

This study aimed to investigate the effects of material filter technique on Tc-99m spectra and performance parameters of Philip ADAC forte dual head gamma camera. Thickness of material filter was selected on the basis of percentage attenuation of various gamma ray energies by different thicknesses of zinc material. A cylindrical source tank of NEMA single photon emission computed tomography (SPECT) Triple Line Source Phantom filled with water and Tc-99m radionuclide injected was used for spectra, uniformity and sensitivity measurements. Vinyl plastic tube was used as a line source for spatial resolution. Images for uniformity were reconstructed by filtered back projection method. Butterworth filter of order 5 and cut off frequency 0.35 cycles/cm was selected. Chang's attenuation correction method was applied by selecting 0.13/cm linear attenuation coefficient. Count rate was decreased with material filter from the compton region of Tc-99m energy spectrum, also from the photopeak region. Spatial resolution was improved. However, uniformity of tomographic image was equivocal, and system volume sensitivity was reduced by material filter. Material filter improved system's spatial resolution. Therefore, the technique may be used for phantom studies to improve the image quality.

The use of the Kalman filter in the automated segmentation of EIT lung images.

PubMed

Zifan, A; Liatsis, P; Chapman, B E

2013-06-01

In this paper, we present a new pipeline for the fast and accurate segmentation of impedance images of the lungs using electrical impedance tomography (EIT). EIT is an emerging, promising, non-invasive imaging modality that produces real-time, low spatial but high temporal resolution images of impedance inside a body. Recovering impedance itself constitutes a nonlinear ill-posed inverse problem, therefore the problem is usually linearized, which produces impedance-change images, rather than static impedance ones. Such images are highly blurry and fuzzy along object boundaries. We provide a mathematical reasoning behind the high suitability of the Kalman filter when it comes to segmenting and tracking conductivity changes in EIT lung images. Next, we use a two-fold approach to tackle the segmentation problem. First, we construct a global lung shape to restrict the search region of the Kalman filter. Next, we proceed with augmenting the Kalman filter by incorporating an adaptive foreground detection system to provide the boundary contours for the Kalman filter to carry out the tracking of the conductivity changes as the lungs undergo deformation in a respiratory cycle. The proposed method has been validated by using performance statistics such as misclassified area, and false positive rate, and compared to previous approaches. The results show that the proposed automated method can be a fast and reliable segmentation tool for EIT imaging.

Parameter estimation for stiff deterministic dynamical systems via ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Arnold, Andrea; Calvetti, Daniela; Somersalo, Erkki

2014-10-01

A commonly encountered problem in numerous areas of applications is to estimate the unknown coefficients of a dynamical system from direct or indirect observations at discrete times of some of the components of the state vector. A related problem is to estimate unobserved components of the state. An egregious example of such a problem is provided by metabolic models, in which the numerous model parameters and the concentrations of the metabolites in tissue are to be estimated from concentration data in the blood. A popular method for addressing similar questions in stochastic and turbulent dynamics is the ensemble Kalman filter (EnKF), a particle-based filtering method that generalizes classical Kalman filtering. In this work, we adapt the EnKF algorithm for deterministic systems in which the numerical approximation error is interpreted as a stochastic drift with variance based on classical error estimates of numerical integrators. This approach, which is particularly suitable for stiff systems where the stiffness may depend on the parameters, allows us to effectively exploit the parallel nature of particle methods. Moreover, we demonstrate how spatial prior information about the state vector, which helps the stability of the computed solution, can be incorporated into the filter. The viability of the approach is shown by computed examples, including a metabolic system modeling an ischemic episode in skeletal muscle, with a high number of unknown parameters.

Estimation and correction of different flavors of surface observation biases in ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Lorente-Plazas, Raquel; Hacker, Josua P.; Collins, Nancy; Lee, Jared A.

2017-04-01

The impact of assimilating surface observations has been shown in several publications, for improving weather prediction inside of the boundary layer as well as the flow aloft. However, the assimilation of surface observations is often far from optimal due to the presence of both model and observation biases. The sources of these biases can be diverse: an instrumental offset, errors associated to the comparison of point-based observations and grid-cell average, etc. To overcome this challenge, a method was developed using the ensemble Kalman filter. The approach consists on representing each observation bias as a parameter. These bias parameters are added to the forward operator and they extend the state vector. As opposed to the observation bias estimation approaches most common in operational systems (e.g. for satellite radiances), the state vector and parameters are simultaneously updated by applying the Kalman filter equations to the augmented state. The method to estimate and correct the observation bias is evaluated using observing system simulation experiments (OSSEs) with the Weather Research and Forecasting (WRF) model. OSSEs are constructed for the conventional observation network including radiosondes, aircraft observations, atmospheric motion vectors, and surface observations. Three different kinds of biases are added to 2-meter temperature for synthetic METARs. From the simplest to more sophisticated, imposed biases are: (1) a spatially invariant bias, (2) a spatially varying bias proportional to topographic height differences between the model and the observations, and (3) bias that is proportional to the temperature. The target region characterized by complex terrain is the western U.S. on a domain with 30-km grid spacing. Observations are assimilated every 3 hours using an 80-member ensemble during September 2012. Results demonstrate that the approach is able to estimate and correct the bias when it is spatially invariant (experiment 1). More complex bias structure in experiments (2) and (3) are more difficult to estimate, but still possible. Estimated the parameter in experiments with unbiased observations results in spatial and temporal parameter variability about zero, and establishes a threshold on the accuracy of the parameter in further experiments. When the observations are biased, the mean parameter value is close to the true bias, but temporal and spatial variability in the parameter estimates is similar to the parameters used when estimating a zero bias in the observations. The distributions are related to other errors in the forecasts, indicating that the parameters are absorbing some of the forecast error from other sources. In this presentation we elucidate the reasons for the resulting parameter estimates, and their variability.

Adaptive Laplacian filtering for sensorimotor rhythm-based brain-computer interfaces.

PubMed

Lu, Jun; McFarland, Dennis J; Wolpaw, Jonathan R

2013-02-01

Sensorimotor rhythms (SMRs) are 8-30 Hz oscillations in the electroencephalogram (EEG) recorded from the scalp over sensorimotor cortex that change with movement and/or movement imagery. Many brain-computer interface (BCI) studies have shown that people can learn to control SMR amplitudes and can use that control to move cursors and other objects in one, two or three dimensions. At the same time, if SMR-based BCIs are to be useful for people with neuromuscular disabilities, their accuracy and reliability must be improved substantially. These BCIs often use spatial filtering methods such as common average reference (CAR), Laplacian (LAP) filter or common spatial pattern (CSP) filter to enhance the signal-to-noise ratio of EEG. Here, we test the hypothesis that a new filter design, called an 'adaptive Laplacian (ALAP) filter', can provide better performance for SMR-based BCIs. An ALAP filter employs a Gaussian kernel to construct a smooth spatial gradient of channel weights and then simultaneously seeks the optimal kernel radius of this spatial filter and the regularization parameter of linear ridge regression. This optimization is based on minimizing the leave-one-out cross-validation error through a gradient descent method and is computationally feasible. Using a variety of kinds of BCI data from a total of 22 individuals, we compare the performances of ALAP filter to CAR, small LAP, large LAP and CSP filters. With a large number of channels and limited data, ALAP performs significantly better than CSP, CAR, small LAP and large LAP both in classification accuracy and in mean-squared error. Using fewer channels restricted to motor areas, ALAP is still superior to CAR, small LAP and large LAP, but equally matched to CSP. Thus, ALAP may help to improve the accuracy and robustness of SMR-based BCIs.

Pixelated filters for spatial imaging

NASA Astrophysics Data System (ADS)

Mathieu, Karine; Lequime, Michel; Lumeau, Julien; Abel-Tiberini, Laetitia; Savin De Larclause, Isabelle; Berthon, Jacques

2015-10-01

Small satellites are often used by spatial agencies to meet scientific spatial mission requirements. Their payloads are composed of various instruments collecting an increasing amount of data, as well as respecting the growing constraints relative to volume and mass; So small-sized integrated camera have taken a favored place among these instruments. To ensure scene specific color information sensing, pixelated filters seem to be more attractive than filter wheels. The work presented here, in collaboration with Institut Fresnel, deals with the manufacturing of this kind of component, based on thin film technologies and photolithography processes. CCD detectors with a pixel pitch about 30 μm were considered. In the configuration where the matrix filters are positioned the closest to the detector, the matrix filters are composed of 2x2 macro pixels (e.g. 4 filters). These 4 filters have a bandwidth about 40 nm and are respectively centered at 550, 700, 770 and 840 nm with a specific rejection rate defined on the visible spectral range [500 - 900 nm]. After an intense design step, 4 thin-film structures have been elaborated with a maximum thickness of 5 μm. A run of tests has allowed us to choose the optimal micro-structuration parameters. The 100x100 matrix filters prototypes have been successfully manufactured with lift-off and ion assisted deposition processes. High spatial and spectral characterization, with a dedicated metrology bench, showed that initial specifications and simulations were globally met. These excellent performances knock down the technological barriers for high-end integrated specific multi spectral imaging.

Accurate mask-based spatially regularized correlation filter for visual tracking

NASA Astrophysics Data System (ADS)

Gu, Xiaodong; Xu, Xinping

2017-01-01

Recently, discriminative correlation filter (DCF)-based trackers have achieved extremely successful results in many competitions and benchmarks. These methods utilize a periodic assumption of the training samples to efficiently learn a classifier. However, this assumption will produce unwanted boundary effects, which severely degrade the tracking performance. Correlation filters with limited boundaries and spatially regularized DCFs were proposed to reduce boundary effects. However, their methods used the fixed mask or predesigned weights function, respectively, which was unsuitable for large appearance variation. We propose an accurate mask-based spatially regularized correlation filter for visual tracking. Our augmented objective can reduce the boundary effect even in large appearance variation. In our algorithm, the masking matrix is converted into the regularized function that acts on the correlation filter in frequency domain, which makes the algorithm fast convergence. Our online tracking algorithm performs favorably against state-of-the-art trackers on OTB-2015 Benchmark in terms of efficiency, accuracy, and robustness.

Gas refractometry based on an all-fiber spatial optical filter.

PubMed

Silva, Susana; Coelho, L; André, R M; Frazão, O

2012-08-15

A spatial optical filter based on splice misalignment between optical fibers with different diameters is proposed for gas refractometry. The sensing head is formed by a 2 mm long optical fiber with 50 μm diameter that is spliced with a strong misalignment between two single-mode fibers (SMF28) and interrogated in transmission. The misalignment causes a Fabry-Perot behavior along the reduced-size fiber and depending on the lead-out SMF28 position, it is possible to obtain different spectral responses, namely, bandpass or band-rejection filters. It is shown that the spatial filter device is highly sensitive to refractive index changes on a nitrogen environment by means of the gas pressure variation. A maximum sensitivity of -1390 nm/RIU for the bandpass filter was achieved. Both devices have shown similar temperature responses with an average sensitivity of 25.7 pm/°C.

Scale-by-scale contributions to Lagrangian particle acceleration

NASA Astrophysics Data System (ADS)

Lalescu, Cristian C.; Wilczek, Michael

2017-11-01

Fluctuations on a wide range of scales in both space and time are characteristic of turbulence. Lagrangian particles, advected by the flow, probe these fluctuations along their trajectories. In an effort to isolate the influence of the different scales on Lagrangian statistics, we employ direct numerical simulations (DNS) combined with a filtering approach. Specifically, we study the acceleration statistics of tracers advected in filtered fields to characterize the smallest temporal scales of the flow. Emphasis is put on the acceleration variance as a function of filter scale, along with the scaling properties of the relevant terms of the Navier-Stokes equations. We furthermore discuss scaling ranges for higher-order moments of the tracer acceleration, as well as the influence of the choice of filter on the results. Starting from the Lagrangian tracer acceleration as the short time limit of the Lagrangian velocity increment, we also quantify the influence of filtering on Lagrangian intermittency. Our work complements existing experimental results on intermittency and accelerations of finite-sized, neutrally-buoyant particles: for the passive tracers used in our DNS, feedback effects are neglected such that the spatial averaging effect is cleanly isolated.

Optical ranked-order filtering using threshold decomposition

DOEpatents

Allebach, J.P.; Ochoa, E.; Sweeney, D.W.

1987-10-09

A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed. 3 figs.

Highly efficient spatial data filtering in parallel using the opensource library CPPPO

NASA Astrophysics Data System (ADS)

Municchi, Federico; Goniva, Christoph; Radl, Stefan

2016-10-01

CPPPO is a compilation of parallel data processing routines developed with the aim to create a library for "scale bridging" (i.e. connecting different scales by mean of closure models) in a multi-scale approach. CPPPO features a number of parallel filtering algorithms designed for use with structured and unstructured Eulerian meshes, as well as Lagrangian data sets. In addition, data can be processed on the fly, allowing the collection of relevant statistics without saving individual snapshots of the simulation state. Our library is provided with an interface to the widely-used CFD solver OpenFOAM®, and can be easily connected to any other software package via interface modules. Also, we introduce a novel, extremely efficient approach to parallel data filtering, and show that our algorithms scale super-linearly on multi-core clusters. Furthermore, we provide a guideline for choosing the optimal Eulerian cell selection algorithm depending on the number of CPU cores used. Finally, we demonstrate the accuracy and the parallel scalability of CPPPO in a showcase focusing on heat and mass transfer from a dense bed of particles.

Optical implementation of the synthetic discriminant function

NASA Astrophysics Data System (ADS)

Butler, S.; Riggins, J.

1984-10-01

Much attention is focused on the use of coherent optical pattern recognition (OPR) using matched spatial filters for robotics and intelligent systems. The OPR problem consists of three aspects -- information input, information processing, and information output. This paper discusses the information processing aspect which consists of choosing a filter to provide robust correlation with high efficiency. The filter should ideally be invariant to image shift, rotation and scale, provide a reasonable signal-to-noise (S/N) ratio and allow high throughput efficiency. The physical implementation of a spatial matched filter involves many choices. These include the use of conventional holograms or computer-generated holograms (CGH) and utilizing absorption or phase materials. Conventional holograms inherently modify the reference image by non-uniform emphasis of spatial frequencies. Proper use of film nonlinearity provides improved filter performance by emphasizing frequency ranges crucial to target discrimination. In the case of a CGH, the emphasis of the reference magnitude and phase can be controlled independently of the continuous tone or binary writing processes. This paper describes computer simulation and optical implementation of a geometrical shape and a Synthetic Discriminant Function (SDF) matched filter. The authors chose the binary Allebach-Keegan (AK) CGH algorithm to produce actual filters. The performances of these filters were measured to verify the simulation results. This paper provides a brief summary of the matched filter theory, the SDF, CGH algorithms, Phase-Only-Filtering, simulation procedures, and results.

Determination of tailored filter sets to create rayfiles including spatial and angular resolved spectral information.

PubMed

Rotscholl, Ingo; Trampert, Klaus; Krüger, Udo; Perner, Martin; Schmidt, Franz; Neumann, Cornelius

2015-11-16

To simulate and optimize optical designs regarding perceived color and homogeneity in commercial ray tracing software, realistic light source models are needed. Spectral rayfiles provide angular and spatial varying spectral information. We propose a spectral reconstruction method with a minimum of time consuming goniophotometric near field measurements with optical filters for the purpose of creating spectral rayfiles. Our discussion focuses on the selection of the ideal optical filter combination for any arbitrary spectrum out of a given filter set by considering measurement uncertainties with Monte Carlo simulations. We minimize the simulation time by a preselection of all filter combinations, which bases on factorial design.

Spatial mode filters realized with multimode interference couplers

NASA Astrophysics Data System (ADS)

Leuthold, J.; Hess, R.; Eckner, J.; Besse, P. A.; Melchior, H.

1996-06-01

Spatial mode filters based on multimode interference couplers (MMI's) that offer the possibility of splitting off antisymmetric from symmetric modes are presented, and realizations of these filters in InGaAsP / InP are demonstrated. Measured suppression of the antisymmetric first-order modes at the output for the symmetric mode is better than 18 dB. Such MMI's are useful for monolithically integrating mode filters with all-optical devices, which are controlled through an antisymmetric first-order mode. The filtering out of optical control signals is necessary for cascading all-optical devices. Another application is the improvement of on-off ratios in optical switches.

Environmental filtering structures tree functional traits combination and lineages across space in tropical tree assemblages.

PubMed

Asefa, Mengesha; Cao, Min; Zhang, Guocheng; Ci, Xiuqin; Li, Jie; Yang, Jie

2017-03-09

Environmental filtering consistently shapes the functional and phylogenetic structure of species across space within diverse forests. However, poor descriptions of community functional and lineage distributions across space hamper the accurate understanding of coexistence mechanisms. We combined environmental variables and geographic space to explore how traits and lineages are filtered by environmental factors using extended RLQ and fourth-corner analyses across different spatial scales. The dispersion patterns of traits and lineages were also examined in a 20-ha tropical rainforest dynamics plot in southwest China. We found that environmental filtering was detected across all spatial scales except the largest scale (100 × 100 m). Generally, the associations between functional traits and environmental variables were more or less consistent across spatial scales. Species with high resource acquisition-related traits were associated with the resource-rich part of the plot across the different spatial scales, whereas resource-conserving functional traits were distributed in limited-resource environments. Furthermore, we found phylogenetic and functional clustering at all spatial scales. Similar functional strategies were also detected among distantly related species, suggesting that phylogenetic distance is not necessarily a proxy for functional distance. In summary, environmental filtering considerably structured the trait and lineage assemblages in this species-rich tropical rainforest.

Kalman filter approach for uncertainty quantification in time-resolved laser-induced incandescence.

PubMed

Hadwin, Paul J; Sipkens, Timothy A; Thomson, Kevin A; Liu, Fengshan; Daun, Kyle J

2018-03-01

Time-resolved laser-induced incandescence (TiRe-LII) data can be used to infer spatially and temporally resolved volume fractions and primary particle size distributions of soot-laden aerosols, but these estimates are corrupted by measurement noise as well as uncertainties in the spectroscopic and heat transfer submodels used to interpret the data. Estimates of the temperature, concentration, and size distribution of soot primary particles within a sample aerosol are typically made by nonlinear regression of modeled spectral incandescence decay, or effective temperature decay, to experimental data. In this work, we employ nonstationary Bayesian estimation techniques to infer aerosol properties from simulated and experimental LII signals, specifically the extended Kalman filter and Schmidt-Kalman filter. These techniques exploit the time-varying nature of both the measurements and the models, and they reveal how uncertainty in the estimates computed from TiRe-LII data evolves over time. Both techniques perform better when compared with standard deterministic estimates; however, we demonstrate that the Schmidt-Kalman filter produces more realistic uncertainty estimates.

Spatiotemporal source tuning filter bank for multiclass EEG based brain computer interfaces.

PubMed

Acharya, Soumyadipta; Mollazadeh, Moshen; Murari, Kartikeya; Thakor, Nitish

2006-01-01

Non invasive brain-computer interfaces (BCI) allow people to communicate by modulating features of their electroencephalogram (EEG). Spatiotemporal filtering has a vital role in multi-class, EEG based BCI. In this study, we used a novel combination of principle component analysis, independent component analysis and dipole source localization to design a spatiotemporal multiple source tuning (SPAMSORT) filter bank, each channel of which was tuned to the activity of an underlying dipole source. Changes in the event-related spectral perturbation (ERSP) were measured and used to train a linear support vector machine to classify between four classes of motor imagery tasks (left hand, right hand, foot and tongue) for one subject. ERSP values were significantly (p<0.01) different across tasks and better (p<0.01) than conventional spatial filtering methods (large Laplacian and common average reference). Classification resulted in an average accuracy of 82.5%. This approach could lead to promising BCI applications such as control of a prosthesis with multiple degrees of freedom.

Visual Processing of Object Velocity and Acceleration

DTIC Science & Technology

1991-12-13

more recently, Dr. Grzywacz’s applications of filtering models to the psychophysics of speed discrimination; 3) the McKee-Welch studies on the...population of spatio-temporally oriented filters to encode velocity. Dr. Grzywacz has attempted to reconcile his model with a variety of psychophysical...by many authors.23 In these models , the image is tectors have different sizes and spatial positions, but they all spatially and temporally filtered

Silicon oxide nanoparticles doped PQ-PMMA for volume holographic imaging filters.

PubMed

Luo, Yuan; Russo, Juan M; Kostuk, Raymond K; Barbastathis, George

2010-04-15

Holographic imaging filters are required to have high Bragg selectivity, namely, narrow angular and spectral bandwidth, to obtain spatial-spectral information within a three-dimensional object. In this Letter, we present the design of holographic imaging filters formed using silicon oxide nanoparticles (nano-SiO(2)) in phenanthrenquinone-poly(methyl methacrylate) (PQ-PMMA) polymer recording material. This combination offers greater Bragg selectivity and increases the diffraction efficiency of holographic filters. The holographic filters with optimized ratio of nano-SiO(2) in PQ-PMMA can significantly improve the performance of Bragg selectivity and diffraction efficiency by 53% and 16%, respectively. We present experimental results and data analysis demonstrating this technique in use for holographic spatial-spectral imaging filters.

Modelling the dependence of contrast sensitivity on grating area and spatial frequency.

PubMed

Rovamo, J; Luntinen, O; Näsänen, R

1993-12-01

We modelled the human foveal visual system in a detection task as a simple image processor comprising (i) low-pass filtering due to the optical transfer function of the eye, (ii) high-pass filtering of neural origin, (iii) addition of internal neural noise, and (iv) detection by a local matched filter. Its detection efficiency for gratings was constant up to a critical area but then decreased with increasing area. To test the model we measured Michelson contrast sensitivity as a function of grating area at spatial frequencies of 0.125-32 c/deg for simple vertical and circular cosine gratings. In circular gratings luminance was sinusoidally modulated as a function of the radius of the grating field. In agreement with the model, contrast sensitivity at all spatial frequencies increased in proportion to the square-root of grating area at small areas. When grating area exceeded critical area, the increase saturated and contrast sensitivity became independent of area at large grating areas. Spatial integration thus obeyed Piper's law at small grating areas. The critical area of spatial integration, marking the cessation of Piper's law, was constant in solid degrees at low spatial frequencies but inversely proportional to spatial frequency squared at medium and high spatial frequencies. At low spatial frequencies the maximum contrast sensitivity obtainable by spatial integration increased in proportion to spatial frequency but at high spatial frequencies it decreased in proportion to the cube of the increasing spatial frequency. The increase was due to high-pass filtering of neural origin (lateral inhibition) and the decrease was mainly due to the optical transfer function of the eye. Our model explained 95% of the total variance of the contrast sensitivity data.

Experiments with explicit filtering for LES using a finite-difference method

NASA Technical Reports Server (NTRS)

Lund, T. S.; Kaltenbach, H. J.

1995-01-01

The equations for large-eddy simulation (LES) are derived formally by applying a spatial filter to the Navier-Stokes equations. The filter width as well as the details of the filter shape are free parameters in LES, and these can be used both to control the effective resolution of the simulation and to establish the relative importance of different portions of the resolved spectrum. An analogous, but less well justified, approach to filtering is more or less universally used in conjunction with LES using finite-difference methods. In this approach, the finite support provided by the computational mesh as well as the wavenumber-dependent truncation errors associated with the finite-difference operators are assumed to define the filter operation. This approach has the advantage that it is also 'automatic' in the sense that no explicit filtering: operations need to be performed. While it is certainly convenient to avoid the explicit filtering operation, there are some practical considerations associated with finite-difference methods that favor the use of an explicit filter. Foremost among these considerations is the issue of truncation error. All finite-difference approximations have an associated truncation error that increases with increasing wavenumber. These errors can be quite severe for the smallest resolved scales, and these errors will interfere with the dynamics of the small eddies if no corrective action is taken. Years of experience at CTR with a second-order finite-difference scheme for high Reynolds number LES has repeatedly indicated that truncation errors must be minimized in order to obtain acceptable simulation results. While the potential advantages of explicit filtering are rather clear, there is a significant cost associated with its implementation. In particular, explicit filtering reduces the effective resolution of the simulation compared with that afforded by the mesh. The resolution requirements for LES are usually set by the need to capture most of the energy-containing eddies, and if explicit filtering is used, the mesh must be enlarged so that these motions are passed by the filter. Given the high cost of explicit filtering, the following interesting question arises. Since the mesh must be expanded in order to perform the explicit filter, might it be better to take advantage of the increased resolution and simply perform an unfiltered simulation on the larger mesh? The cost of the two approaches is roughly the same, but the philosophy is rather different. In the filtered simulation, resolution is sacrificed in order to minimize the various forms of numerical error. In the unfiltered simulation, the errors are left intact, but they are concentrated at very small scales that could be dynamically unimportant from a LES perspective. Very little is known about this tradeoff and the objective of this work is to study this relationship in high Reynolds number channel flow simulations using a second-order finite-difference method.

Segmentation-assisted detection of dirt impairments in archived film sequences.

PubMed

Ren, Jinchang; Vlachos, Theodore

2007-04-01

In this correspondence, a novel segmentation-assisted method for film-dirt detection is proposed. We exploit the fact that film dirt manifests in the spatial domain as a cluster of connected pixels whose intensity differs substantially from that of its neighborhood, and we employ a segmentation-based approach to identify this type of structure. A key feature of our approach is the computation of a measure of confidence attached to detected dirt regions, which can be utilized for performance fine tuning. Another important feature of our algorithm is the avoidance of the computational complexity associated with motion estimation. Our experimental framework benefits from the availability of manually derived as well as objective ground-truth data obtained using infrared scanning. Our results demonstrate that the proposed method compares favorably with standard spatial, temporal, and multistage median-filtering approaches and provides efficient and robust detection for a wide variety of test materials.

Perception of differences in naturalistic dynamic scenes, and a V1-based model.

PubMed

To, Michelle P S; Gilchrist, Iain D; Tolhurst, David J

2015-01-16

We investigate whether a computational model of V1 can predict how observers rate perceptual differences between paired movie clips of natural scenes. Observers viewed 198 pairs of movies clips, rating how different the two clips appeared to them on a magnitude scale. Sixty-six of the movie pairs were naturalistic and those remaining were low-pass or high-pass spatially filtered versions of those originals. We examined three ways of comparing a movie pair. The Spatial Model compared corresponding frames between each movie pairwise, combining those differences using Minkowski summation. The Temporal Model compared successive frames within each movie, summed those differences for each movie, and then compared the overall differences between the paired movies. The Ordered-Temporal Model combined elements from both models, and yielded the single strongest predictions of observers' ratings. We modeled naturalistic sustained and transient impulse functions and compared frames directly with no temporal filtering. Overall, modeling naturalistic temporal filtering improved the models' performance; in particular, the predictions of the ratings for low-pass spatially filtered movies were much improved by employing a transient impulse function. The correlations between model predictions and observers' ratings rose from 0.507 without temporal filtering to 0.759 (p = 0.01%) when realistic impulses were included. The sustained impulse function and the Spatial Model carried more weight in ratings for normal and high-pass movies, whereas the transient impulse function with the Ordered-Temporal Model was most important for spatially low-pass movies. This is consistent with models in which high spatial frequency channels with sustained responses primarily code for spatial details in movies, while low spatial frequency channels with transient responses code for dynamic events. © 2015 ARVO.

Key issues in decomposing fMRI during naturalistic and continuous music experience with independent component analysis.

PubMed

Cong, Fengyu; Puoliväli, Tuomas; Alluri, Vinoo; Sipola, Tuomo; Burunat, Iballa; Toiviainen, Petri; Nandi, Asoke K; Brattico, Elvira; Ristaniemi, Tapani

2014-02-15

Independent component analysis (ICA) has been often used to decompose fMRI data mostly for the resting-state, block and event-related designs due to its outstanding advantage. For fMRI data during free-listening experiences, only a few exploratory studies applied ICA. For processing the fMRI data elicited by 512-s modern tango, a FFT based band-pass filter was used to further pre-process the fMRI data to remove sources of no interest and noise. Then, a fast model order selection method was applied to estimate the number of sources. Next, both individual ICA and group ICA were performed. Subsequently, ICA components whose temporal courses were significantly correlated with musical features were selected. Finally, for individual ICA, common components across majority of participants were found by diffusion map and spectral clustering. The extracted spatial maps (by the new ICA approach) common across most participants evidenced slightly right-lateralized activity within and surrounding the auditory cortices. Meanwhile, they were found associated with the musical features. Compared with the conventional ICA approach, more participants were found to have the common spatial maps extracted by the new ICA approach. Conventional model order selection methods underestimated the true number of sources in the conventionally pre-processed fMRI data for the individual ICA. Pre-processing the fMRI data by using a reasonable band-pass digital filter can greatly benefit the following model order selection and ICA with fMRI data by naturalistic paradigms. Diffusion map and spectral clustering are straightforward tools to find common ICA spatial maps. Copyright © 2013 Elsevier B.V. All rights reserved.

Laser-induced breakdown spectroscopy (LIBS) analysis of calcium ions dissolved in water using filter paper substrates: an ideal internal standard for precision improvement.

PubMed

Choi, Daewoong; Gong, Yongdeuk; Nam, Sang-Ho; Han, Song-Hee; Yoo, Jonghyun; Lee, Yonghoon

2014-01-01

We report an approach for selecting an internal standard to improve the precision of laser-induced breakdown spectroscopy (LIBS) analysis for determining calcium (Ca) concentration in water. The dissolved Ca(2+) ions were pre-concentrated on filter paper by evaporating water. The filter paper was dried and analyzed using LIBS. By adding strontium chloride to sample solutions and using a Sr II line at 407.771 nm for the intensity normalization of Ca II lines at 393.366 or 396.847 nm, the analysis precision could be significantly improved. The Ca II and Sr II line intensities were mapped across the filter paper, and they showed a strong positive shot-to-shot correlation with the same spatial distribution on the filter paper surface. We applied this analysis approach for the measurement of Ca(2+) in tap, bottled, and ground water samples. The Ca(2+) concentrations determined using LIBS are in good agreement with those obtained from flame atomic absorption spectrometry. Finally, we suggest a homologous relation of the strongest emission lines of period 4 and 5 elements in groups IA and IIA based on their similar electronic structures. Our results indicate that the LIBS can be effectively applied for liquid analysis at the sub-parts per million level with high precision using a simple drying of liquid solutions on filter paper and the use of the correct internal standard elements with the similar valence electronic structure with respect to the analytes of interest.

Expert system constant false alarm rate processor

NASA Astrophysics Data System (ADS)

Baldygo, William J., Jr.; Wicks, Michael C.

1993-10-01

The requirements for high detection probability and low false alarm probability in modern wide area surveillance radars are rarely met due to spatial variations in clutter characteristics. Many filtering and CFAR detection algorithms have been developed to effectively deal with these variations; however, any single algorithm is likely to exhibit excessive false alarms and intolerably low detection probabilities in a dynamically changing environment. A great deal of research has led to advances in the state of the art in Artificial Intelligence (AI) and numerous areas have been identified for application to radar signal processing. The approach suggested here, discussed in a patent application submitted by the authors, is to intelligently select the filtering and CFAR detection algorithms being executed at any given time, based upon the observed characteristics of the interference environment. This approach requires sensing the environment, employing the most suitable algorithms, and applying an appropriate multiple algorithm fusion scheme or consensus algorithm to produce a global detection decision.

A circular median filter approach for resolving directional ambiguities in wind fields retrieved from spaceborne scatterometer data

NASA Technical Reports Server (NTRS)

Schultz, Howard

1990-01-01

The retrieval algorithm for spaceborne scatterometry proposed by Schultz (1985) is extended. A circular median filter (CMF) method is presented, which operates on wind directions independently of wind speed, removing any implicit wind speed dependence. A cell weighting scheme is included in the algorithm, permitting greater weights to be assigned to more reliable data. The mathematical properties of the ambiguous solutions to the wind retrieval problem are reviewed. The CMF algorithm is tested on twelve simulated data sets. The effects of spatially correlated likelihood assignment errors on the performance of the CMF algorithm are examined. Also, consideration is given to a wind field smoothing technique that uses a CMF.

Sampling Versus Filtering in Large-Eddy Simulations

NASA Technical Reports Server (NTRS)

Debliquy, O.; Knaepen, B.; Carati, D.; Wray, A. A.

2004-01-01

A LES formalism in which the filter operator is replaced by a sampling operator is proposed. The unknown quantities that appear in the LES equations originate only from inadequate resolution (Discretization errors). The resulting viewpoint seems to make a link between finite difference approaches and finite element methods. Sampling operators are shown to commute with nonlinearities and to be purely projective. Moreover, their use allows an unambiguous definition of the LES numerical grid. The price to pay is that sampling never commutes with spatial derivatives and the commutation errors must be modeled. It is shown that models for the discretization errors may be treated using the dynamic procedure. Preliminary results, using the Smagorinsky model, are very encouraging.

Kalman filter techniques for accelerated Cartesian dynamic cardiac imaging.

PubMed

Feng, Xue; Salerno, Michael; Kramer, Christopher M; Meyer, Craig H

2013-05-01

In dynamic MRI, spatial and temporal parallel imaging can be exploited to reduce scan time. Real-time reconstruction enables immediate visualization during the scan. Commonly used view-sharing techniques suffer from limited temporal resolution, and many of the more advanced reconstruction methods are either retrospective, time-consuming, or both. A Kalman filter model capable of real-time reconstruction can be used to increase the spatial and temporal resolution in dynamic MRI reconstruction. The original study describing the use of the Kalman filter in dynamic MRI was limited to non-Cartesian trajectories because of a limitation intrinsic to the dynamic model used in that study. Here the limitation is overcome, and the model is applied to the more commonly used Cartesian trajectory with fast reconstruction. Furthermore, a combination of the Kalman filter model with Cartesian parallel imaging is presented to further increase the spatial and temporal resolution and signal-to-noise ratio. Simulations and experiments were conducted to demonstrate that the Kalman filter model can increase the temporal resolution of the image series compared with view-sharing techniques and decrease the spatial aliasing compared with TGRAPPA. The method requires relatively little computation, and thus is suitable for real-time reconstruction. Copyright © 2012 Wiley Periodicals, Inc.

Kalman Filter Techniques for Accelerated Cartesian Dynamic Cardiac Imaging

PubMed Central

Feng, Xue; Salerno, Michael; Kramer, Christopher M.; Meyer, Craig H.

2012-01-01

In dynamic MRI, spatial and temporal parallel imaging can be exploited to reduce scan time. Real-time reconstruction enables immediate visualization during the scan. Commonly used view-sharing techniques suffer from limited temporal resolution, and many of the more advanced reconstruction methods are either retrospective, time-consuming, or both. A Kalman filter model capable of real-time reconstruction can be used to increase the spatial and temporal resolution in dynamic MRI reconstruction. The original study describing the use of the Kalman filter in dynamic MRI was limited to non-Cartesian trajectories, because of a limitation intrinsic to the dynamic model used in that study. Here the limitation is overcome and the model is applied to the more commonly used Cartesian trajectory with fast reconstruction. Furthermore, a combination of the Kalman filter model with Cartesian parallel imaging is presented to further increase the spatial and temporal resolution and SNR. Simulations and experiments were conducted to demonstrate that the Kalman filter model can increase the temporal resolution of the image series compared with view sharing techniques and decrease the spatial aliasing compared with TGRAPPA. The method requires relatively little computation, and thus is suitable for real-time reconstruction. PMID:22926804

Spatio-temporal filtering for determination of common mode error in regional GNSS networks

NASA Astrophysics Data System (ADS)

Bogusz, Janusz; Gruszczynski, Maciej; Figurski, Mariusz; Klos, Anna

2015-04-01

The spatial correlation between different stations for individual components in the regional GNSS networks seems to be significant. The mismodelling in satellite orbits, the Earth orientation parameters (EOP), largescale atmospheric effects or satellite antenna phase centre corrections can all cause the regionally correlated errors. This kind of GPS time series errors are referred to as common mode errors (CMEs). They are usually estimated with the regional spatial filtering, such as the "stacking". In this paper, we show the stacking approach for the set of ASG-EUPOS permanent stations, assuming that spatial distribution of the CME is uniform over the whole region of Poland (more than 600 km extent). The ASG-EUPOS is a multifunctional precise positioning system based on the reference network designed for Poland. We used a 5- year span time series (2008-2012) of daily solutions in the ITRF2008 from Bernese 5.0 processed by the Military University of Technology EPN Local Analysis Centre (MUT LAC). At the beginning of our analyses concerning spatial dependencies, the correlation coefficients between each pair of the stations in the GNSS network were calculated. This analysis shows that spatio-temporal behaviour of the GPS-derived time series is not purely random, but there is the evident uniform spatial response. In order to quantify the influence of filtering using CME, the norms L1 and L2 were determined. The values of these norms were calculated for the North, East and Up components twice: before performing the filtration and after stacking. The observed reduction of the L1 and L2 norms was up to 30% depending on the dimension of the network. However, the question how to define an optimal size of CME-analysed subnetwork remains unanswered in this research, due to the fact that our network is not extended enough.

Tunable orbital angular momentum mode filter based on optical geometric transformation.

PubMed

Huang, Hao; Ren, Yongxiong; Xie, Guodong; Yan, Yan; Yue, Yang; Ahmed, Nisar; Lavery, Martin P J; Padgett, Miles J; Dolinar, Sam; Tur, Moshe; Willner, Alan E

2014-03-15

We present a tunable mode filter for spatially multiplexed laser beams carrying orbital angular momentum (OAM). The filter comprises an optical geometric transformation-based OAM mode sorter and a spatial light modulator (SLM). The programmable SLM can selectively control the passing/blocking of each input OAM beam. We experimentally demonstrate tunable filtering of one or multiple OAM modes from four multiplexed input OAM modes with vortex charge of ℓ=-9, -4, +4, and +9. The measured output power suppression ratio of the propagated modes to the blocked modes exceeds 14.5 dB.

Demosaicking for full motion video 9-band SWIR sensor

NASA Astrophysics Data System (ADS)

Kanaev, Andrey V.; Rawhouser, Marjorie; Kutteruf, Mary R.; Yetzbacher, Michael K.; DePrenger, Michael J.; Novak, Kyle M.; Miller, Corey A.; Miller, Christopher W.

2014-05-01

Short wave infrared (SWIR) spectral imaging systems are vital for Intelligence, Surveillance, and Reconnaissance (ISR) applications because of their abilities to autonomously detect targets and classify materials. Typically the spectral imagers are incapable of providing Full Motion Video (FMV) because of their reliance on line scanning. We enable FMV capability for a SWIR multi-spectral camera by creating a repeating pattern of 3x3 spectral filters on a staring focal plane array (FPA). In this paper we present the imagery from an FMV SWIR camera with nine discrete bands and discuss image processing algorithms necessary for its operation. The main task of image processing in this case is demosaicking of the spectral bands i.e. reconstructing full spectral images with original FPA resolution from spatially subsampled and incomplete spectral data acquired with the choice of filter array pattern. To the best of author's knowledge, the demosaicking algorithms for nine or more equally sampled bands have not been reported before. Moreover all existing algorithms developed for demosaicking visible color filter arrays with less than nine colors assume either certain relationship between the visible colors, which are not valid for SWIR imaging, or presence of one color band with higher sampling rate compared to the rest of the bands, which does not conform to our spectral filter pattern. We will discuss and present results for two novel approaches to demosaicking: interpolation using multi-band edge information and application of multi-frame super-resolution to a single frame resolution enhancement of multi-spectral spatially multiplexed images.

Design of coupled mace filters for optical pattern recognition using practical spatial light modulators

NASA Technical Reports Server (NTRS)

Rajan, P. K.; Khan, Ajmal

1993-01-01

Spatial light modulators (SLMs) are being used in correlation-based optical pattern recognition systems to implement the Fourier domain filters. Currently available SLMs have certain limitations with respect to the realizability of these filters. Therefore, it is necessary to incorporate the SLM constraints in the design of the filters. The design of a SLM-constrained minimum average correlation energy (SLM-MACE) filter using the simulated annealing-based optimization technique was investigated. The SLM-MACE filter was synthesized for three different types of constraints. The performance of the filter was evaluated in terms of its recognition (discrimination) capabilities using computer simulations. The correlation plane characteristics of the SLM-MACE filter were found to be reasonably good. The SLM-MACE filter yielded far better results than the analytical MACE filter implemented on practical SLMs using the constrained magnitude technique. Further, the filter performance was evaluated in the presence of noise in the input test images. This work demonstrated the need to include the SLM constraints in the filter design. Finally, a method is suggested to reduce the computation time required for the synthesis of the SLM-MACE filter.

Aperiodic nanoplasmonic devices for directional colour filtering and sensing.

PubMed

Davis, Matthew S; Zhu, Wenqi; Xu, Ting; Lee, Jay K; Lezec, Henri J; Agrawal, Amit

2017-11-07

Exploiting the wave-nature of light in its simplest form, periodic architectures have enabled a panoply of tunable optical devices with the ability to perform useful functions such as filtering, spectroscopy, and multiplexing. Here, we remove the constraint of structural periodicity to enhance, simultaneously, the performance and functionality of passive plasmonic devices operating at optical frequencies. By using a physically intuitive, first-order interference model of plasmon-light interactions, we demonstrate a simple and efficient route towards designing devices with flexible, multi-spectral optical response, fundamentally not achievable using periodic architectures. Leveraging this approach, we experimentally implement ultra-compact directional light-filters and colour-sorters exhibiting angle- or spectrally-tunable optical responses with high contrast, and low spectral or spatial crosstalk. Expanding the potential of aperiodic systems to implement tailored spectral and angular responses, these results hint at promising applications in solar-energy harvesting, optical signal multiplexing, and integrated sensing.

Analysis of ICESat Data Using Kalman Filter and Kriging to Study Height Changes in East Antarctica

NASA Technical Reports Server (NTRS)

Herring, Thomas A.

2005-01-01

We analyze ICESat derived heights collected between Feb. 03-Nov. 04 using a kriging/Kalman filtering approach to investigate height changes in East Antarctica. The model's parameters are height change to an a priori static digital height model, seasonal signal expressed as an amplitude Beta and phase Theta, and height-change rate dh/dt for each (100 km)(exp 2) block. From the Kalman filter results, dh/dt has a mean of -0.06 m/yr in the flat interior of East Antarctica. Spatially correlated pointing errors in the current data releases give uncertainties in the range 0.06 m/yr, making height change detection unreliable at this time. Our test shows that when using all available data with pointing knowledge equivalent to that of Laser 2a, height change detection with an accuracy level 0.02 m/yr can be achieved over flat terrains in East Antarctica.

EEG based zero-phase phase-locking value (PLV) and effects of spatial filtering during actual movement.

PubMed

Jian, Wenjuan; Chen, Minyou; McFarland, Dennis J

2017-04-01

Phase-locking value (PLV) is a well-known feature in sensorimotor rhythm (SMR) based BCI. Zero-phase PLV has not been explored because it is generally regarded as the result of volume conduction. Because spatial filters are often used to enhance the amplitude (square root of band power (BP)) feature and attenuate volume conduction, they are frequently applied as pre-processing methods when computing PLV. However, the effects of spatial filtering on PLV are ambiguous. Therefore, this article aims to explore whether zero-phase PLV is meaningful and how this is influenced by spatial filtering. Based on archival EEG data of left and right hand movement tasks for 32 subjects, we compared BP and PLV feature using data with and without pre-processing by a large Laplacian. Results showed that using ear-referenced data, zero-phase PLV provided unique information independent of BP for task prediction which was not explained by volume conduction and was significantly decreased when a large Laplacian was applied. In other words, the large Laplacian eliminated the useful information in zero-phase PLV for task prediction suggesting that it contains effects of both amplitude and phase. Therefore, zero-phase PLV may have functional significance beyond volume conduction. The interpretation of spatial filtering may be complicated by effects of phase. Copyright © 2017 Elsevier Inc. All rights reserved.

A Spatially Constrained Multi-autoencoder Approach for Multivariate Geochemical Anomaly Recognition

NASA Astrophysics Data System (ADS)

Lirong, C.; Qingfeng, G.; Renguang, Z.; Yihui, X.

2017-12-01

Separating and recognizing geochemical anomalies from the geochemical background is one of the key tasks in geochemical exploration. Many methods have been developed, such as calculating the mean ±2 standard deviation, and fractal/multifractal models. In recent years, deep autoencoder, a deep learning approach, have been used for multivariate geochemical anomaly recognition. While being able to deal with the non-normal distributions of geochemical concentrations and the non-linear relationships among them, this self-supervised learning method does not take into account the spatial heterogeneity of geochemical background and the uncertainty induced by the randomly initialized weights of neurons, leading to ineffective recognition of weak anomalies. In this paper, we introduce a spatially constrained multi-autoencoder (SCMA) approach for multivariate geochemical anomaly recognition, which includes two steps: spatial partitioning and anomaly score computation. The first step divides the study area into multiple sub-regions to segregate the geochemical background, by grouping the geochemical samples through K-means clustering, spatial filtering, and spatial constraining rules. In the second step, for each sub-region, a group of autoencoder neural networks are constructed with an identical structure but different initial weights on neurons. Each autoencoder is trained using the geochemical samples within the corresponding sub-region to learn the sub-regional geochemical background. The best autoencoder of a group is chosen as the final model for the corresponding sub-region. The anomaly score at each location can then be calculated as the euclidean distance between the observed concentrations and reconstructed concentrations of geochemical elements.The experiments using the geochemical data and Fe deposits in the southwestern Fujian province of China showed that our SCMA approach greatly improved the recognition of weak anomalies, achieving the AUC of 0.89, compared with the AUC of 0.77 using a single deep autoencoder approach.

AgBufferBuilder: A geographic information system (GIS) tool for precision design and performance assessment of filter strips

Treesearch

M. G. Dosskey; S. Neelakantan; T. G. Mueller; T. Kellerman; M. J. Helmers; E. Rienzi

2015-01-01

Spatially nonuniform runoif reduces the water qua1iry perfortnance of constant- width filter strips. A geographic inlormation system (Gls)-based tool was developed and tested that ernploys terrain analysis to account lor spatially nonuniform runoffand produce more ellbctive filter strip designs.The computer program,AgBufTerBuilder, runs with ATcGIS versions 10.0 and 10...

Reversible wavelet filter banks with side informationless spatially adaptive low-pass filters

NASA Astrophysics Data System (ADS)

Abhayaratne, Charith

2011-07-01

Wavelet transforms that have an adaptive low-pass filter are useful in applications that require the signal singularities, sharp transitions, and image edges to be left intact in the low-pass signal. In scalable image coding, the spatial resolution scalability is achieved by reconstructing the low-pass signal subband, which corresponds to the desired resolution level, and discarding other high-frequency wavelet subbands. In such applications, it is vital to have low-pass subbands that are not affected by smoothing artifacts associated with low-pass filtering. We present the mathematical framework for achieving 1-D wavelet transforms that have a spatially adaptive low-pass filter (SALP) using the prediction-first lifting scheme. The adaptivity decisions are computed using the wavelet coefficients, and no bookkeeping is required for the perfect reconstruction. Then, 2-D wavelet transforms that have a spatially adaptive low-pass filter are designed by extending the 1-D SALP framework. Because the 2-D polyphase decompositions are used in this case, the 2-D adaptivity decisions are made nonseparable as opposed to the separable 2-D realization using 1-D transforms. We present examples using the 2-D 5/3 wavelet transform and their lossless image coding and scalable decoding performances in terms of quality and resolution scalability. The proposed 2-D-SALP scheme results in better performance compared to the existing adaptive update lifting schemes.

Construction of Low Dissipative High Order Well-Balanced Filter Schemes for Non-Equilibrium Flows

NASA Technical Reports Server (NTRS)

Wang, Wei; Yee, H. C.; Sjogreen, Bjorn; Magin, Thierry; Shu, Chi-Wang

2009-01-01

The goal of this paper is to generalize the well-balanced approach for non-equilibrium flow studied by Wang et al. [26] to a class of low dissipative high order shock-capturing filter schemes and to explore more advantages of well-balanced schemes in reacting flows. The class of filter schemes developed by Yee et al. [30], Sjoegreen & Yee [24] and Yee & Sjoegreen [35] consist of two steps, a full time step of spatially high order non-dissipative base scheme and an adaptive nonlinear filter containing shock-capturing dissipation. A good property of the filter scheme is that the base scheme and the filter are stand alone modules in designing. Therefore, the idea of designing a well-balanced filter scheme is straightforward, i.e., choosing a well-balanced base scheme with a well-balanced filter (both with high order). A typical class of these schemes shown in this paper is the high order central difference schemes/predictor-corrector (PC) schemes with a high order well-balanced WENO filter. The new filter scheme with the well-balanced property will gather the features of both filter methods and well-balanced properties: it can preserve certain steady state solutions exactly; it is able to capture small perturbations, e.g., turbulence fluctuations; it adaptively controls numerical dissipation. Thus it shows high accuracy, efficiency and stability in shock/turbulence interactions. Numerical examples containing 1D and 2D smooth problems, 1D stationary contact discontinuity problem and 1D turbulence/shock interactions are included to verify the improved accuracy, in addition to the well-balanced behavior.

Proposed New Vision Standards for the 1980’s and Beyond: Contrast Sensitivity

DTIC Science & Technology

1981-09-01

spatial frequency, visual acuity, target aquistion, visual filters, spatial filtering, target detection, recognitio identification, eye charts, workload...visual standards, as well as other performance criteria, are required to be thown relevant to "real-world" performance before acceptance. On the sur- face

Early season monitoring of corn and soybeans with TerraSAR-X and RADARSAT-2

NASA Astrophysics Data System (ADS)

McNairn, H.; Kross, A.; Lapen, D.; Caves, R.; Shang, J.

2014-05-01

Early and on-going crop production forecasts are important to facilitate food price stability for regions at risk, and for agriculture exporters, to set market value. Most regional and global efforts in forecasting rely on multiple sources of information from the field. With increased access to data from spaceborne Synthetic Aperture Radar (SAR), these sensors could contribute information on crop acreage. But these acreage estimates must be available early in the season to assist with production forecasts. This study acquired TerraSAR-X and RADARSAT-2 data over a region in eastern Canada dominated by economically important corn and soybean production. Using a supervised decision tree classifier, results determined that either sensor was capable of delivering highly accurate maps of corn and soybeans at the end of the growing season. Accuracies far exceeded 90%. Spatial and multi-temporal filtering approaches were compared and small improvements in accuracies were found by applying the multi-temporal filter to the RADARSAT-2 data. Of significant interest, this study determined that by using only three TerraSAR-X images corn could be accurately identified by the end of June, a mere six weeks after planting and at a vegetative growth stage (V6 - sixth leaf collar developed). However, soybeans required additional acquisitions given the variance in planting densities and planting dates in this region of Canada. In this case, accurate soybean classification required TerraSAR-X images until early August at the start of the reproductive stage (R5 - seed development is beginning). Also important, by applying a multi-temporal filter accurate mapping (close to 90%) of corn and soybeans from RADARSAT-2 could occur five weeks earlier (by August 19) than if a spatial filter was used. Thus application of this filtering approach could accelerate delivery of a crop inventory for this region of Canada. Corn and soybeans are important commodities both globally and within Canada. This study makes an important contribution as it demonstrates that TerraSAR-X can deliver acreage estimates of these two crops early enough to assist with in-season production forecasting.

Small target detection using bilateral filter and temporal cross product in infrared images

NASA Astrophysics Data System (ADS)

Bae, Tae-Wuk

2011-09-01

We introduce a spatial and temporal target detection method using spatial bilateral filter (BF) and temporal cross product (TCP) of temporal pixels in infrared (IR) image sequences. At first, the TCP is presented to extract the characteristics of temporal pixels by using temporal profile in respective spatial coordinates of pixels. The TCP represents the cross product values by the gray level distance vector of a current temporal pixel and the adjacent temporal pixel, as well as the horizontal distance vector of the current temporal pixel and a temporal pixel corresponding to potential target center. The summation of TCP values of temporal pixels in spatial coordinates makes the temporal target image (TTI), which represents the temporal target information of temporal pixels in spatial coordinates. And then the proposed BF filter is used to extract the spatial target information. In order to predict background without targets, the proposed BF filter uses standard deviations obtained by an exponential mapping of the TCP value corresponding to the coordinate of a pixel processed spatially. The spatial target image (STI) is made by subtracting the predicted image from the original image. Thus, the spatial and temporal target image (STTI) is achieved by multiplying the STI and the TTI, and then targets finally are detected in STTI. In experimental result, the receiver operating characteristics (ROC) curves were computed experimentally to compare the objective performance. From the results, the proposed algorithm shows better discrimination of target and clutters and lower false alarm rates than the existing target detection methods.

Anti-aliasing filters for deriving high-accuracy DEMs from TLS data: A case study from Freeport, Texas

NASA Astrophysics Data System (ADS)

Xiong, L.; Wang, G.; Wessel, P.

2017-12-01

Terrestrial laser scanning (TLS), also known as ground-based Light Detection and Ranging (LiDAR), has been frequently applied to build bare-earth digital elevation models (DEMs) for high-accuracy geomorphology studies. The point clouds acquired from TLS often achieve a spatial resolution at fingerprint (e.g., 3cm×3cm) to handprint (e.g., 10cm×10cm) level. A downsampling process has to be applied to decimate the massive point clouds and obtain portable DEMs. It is well known that downsampling can result in aliasing that causes different signal components to become indistinguishable when the signal is reconstructed from the datasets with a lower sampling rate. Conventional DEMs are mainly the results of upsampling of sparse elevation measurements from land surveying, satellite remote sensing, and aerial photography. As a consequence, the effects of aliasing have not been fully investigated in the open literature of DEMs. This study aims to investigate the spatial aliasing problem and implement an anti-aliasing procedure of regridding dense TLS data. The TLS data collected in the beach and dune area near Freeport, Texas in the summer of 2015 are used for this study. The core idea of the anti-aliasing procedure is to apply a low-pass spatial filter prior to conducting downsampling. This article describes the successful use of a fourth-order Butterworth low-pass spatial filter employed in the Generic Mapping Tools (GMT) software package as anti-aliasing filters. The filter can be applied as an isotropic filter with a single cutoff wavelength or as an anisotropic filter with different cutoff wavelengths in the X and Y directions. The cutoff wavelength for the isotropic filter is recommended to be three times the grid size of the target DEM.

Anti-aliasing Wiener filtering for wave-front reconstruction in the spatial-frequency domain for high-order astronomical adaptive-optics systems.

PubMed

Correia, Carlos M; Teixeira, Joel

2014-12-01

Computationally efficient wave-front reconstruction techniques for astronomical adaptive-optics (AO) systems have seen great development in the past decade. Algorithms developed in the spatial-frequency (Fourier) domain have gathered much attention, especially for high-contrast imaging systems. In this paper we present the Wiener filter (resulting in the maximization of the Strehl ratio) and further develop formulae for the anti-aliasing (AA) Wiener filter that optimally takes into account high-order wave-front terms folded in-band during the sensing (i.e., discrete sampling) process. We employ a continuous spatial-frequency representation for the forward measurement operators and derive the Wiener filter when aliasing is explicitly taken into account. We further investigate and compare to classical estimates using least-squares filters the reconstructed wave-front, measurement noise, and aliasing propagation coefficients as a function of the system order. Regarding high-contrast systems, we provide achievable performance results as a function of an ensemble of forward models for the Shack-Hartmann wave-front sensor (using sparse and nonsparse representations) and compute point-spread-function raw intensities. We find that for a 32×32 single-conjugated AOs system the aliasing propagation coefficient is roughly 60% of the least-squares filters, whereas the noise propagation is around 80%. Contrast improvements of factors of up to 2 are achievable across the field in the H band. For current and next-generation high-contrast imagers, despite better aliasing mitigation, AA Wiener filtering cannot be used as a standalone method and must therefore be used in combination with optical spatial filters deployed before image formation actually takes place.

Anti-aliasing filters for deriving high-accuracy DEMs from TLS data: A case study from Freeport, Texas

NASA Astrophysics Data System (ADS)

Xiong, Lin.; Wang, Guoquan; Wessel, Paul

2017-03-01

Terrestrial laser scanning (TLS), also known as ground-based Light Detection and Ranging (LiDAR), has been frequently applied to build bare-earth digital elevation models (DEMs) for high-accuracy geomorphology studies. The point clouds acquired from TLS often achieve a spatial resolution at fingerprint (e.g., 3 cm×3 cm) to handprint (e.g., 10 cm×10 cm) level. A downsampling process has to be applied to decimate the massive point clouds and obtain manageable DEMs. It is well known that downsampling can result in aliasing that causes different signal components to become indistinguishable when the signal is reconstructed from the datasets with a lower sampling rate. Conventional DEMs are mainly the results of upsampling of sparse elevation measurements from land surveying, satellite remote sensing, and aerial photography. As a consequence, the effects of aliasing caused by downsampling have not been fully investigated in the open literature of DEMs. This study aims to investigate the spatial aliasing problem of regridding dense TLS data. The TLS data collected from the beach and dune area near Freeport, Texas in the summer of 2015 are used for this study. The core idea of the anti-aliasing procedure is to apply a low-pass spatial filter prior to conducting downsampling. This article describes the successful use of a fourth-order Butterworth low-pass spatial filter employed in the Generic Mapping Tools (GMT) software package as an anti-aliasing filter. The filter can be applied as an isotropic filter with a single cutoff wavelength or as an anisotropic filter with two different cutoff wavelengths in the X and Y directions. The cutoff wavelength for the isotropic filter is recommended to be three times the grid size of the target DEM.

Spatial shaping for generating arbitrary optical dipole traps for ultracold degenerate gases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Jeffrey G., E-mail: jglee@umd.edu; Institute for Physical Science and Technology, University of Maryland, College Park, Maryland 20742; Hill, W. T., E-mail: wth@umd.edu

2014-10-15

We present two spatial-shaping approaches – phase and amplitude – for creating two-dimensional optical dipole potentials for ultracold neutral atoms. When combined with an attractive or repulsive Gaussian sheet formed by an astigmatically focused beam, atoms are trapped in three dimensions resulting in planar confinement with an arbitrary network of potentials – a free-space atom chip. The first approach utilizes an adaptation of the generalized phase-contrast technique to convert a phase structure embedded in a beam after traversing a phase mask, to an identical intensity profile in the image plane. Phase masks, and a requisite phase-contrast filter, can be chemicallymore » etched into optical material (e.g., fused silica) or implemented with spatial light modulators; etching provides the highest quality while spatial light modulators enable prototyping and realtime structure modification. This approach was demonstrated on an ensemble of thermal atoms. Amplitude shaping is possible when the potential structure is made as an opaque mask in the path of a dipole trap beam, followed by imaging the shadow onto the plane of the atoms. While much more lossy, this very simple and inexpensive approach can produce dipole potentials suitable for containing degenerate gases. High-quality amplitude masks can be produced with standard photolithography techniques. Amplitude shaping was demonstrated on a Bose-Einstein condensate.« less

A Bayesian consistent dual ensemble Kalman filter for state-parameter estimation in subsurface hydrology

NASA Astrophysics Data System (ADS)

Ait-El-Fquih, Boujemaa; El Gharamti, Mohamad; Hoteit, Ibrahim

2016-08-01

Ensemble Kalman filtering (EnKF) is an efficient approach to addressing uncertainties in subsurface groundwater models. The EnKF sequentially integrates field data into simulation models to obtain a better characterization of the model's state and parameters. These are generally estimated following joint and dual filtering strategies, in which, at each assimilation cycle, a forecast step by the model is followed by an update step with incoming observations. The joint EnKF directly updates the augmented state-parameter vector, whereas the dual EnKF empirically employs two separate filters, first estimating the parameters and then estimating the state based on the updated parameters. To develop a Bayesian consistent dual approach and improve the state-parameter estimates and their consistency, we propose in this paper a one-step-ahead (OSA) smoothing formulation of the state-parameter Bayesian filtering problem from which we derive a new dual-type EnKF, the dual EnKFOSA. Compared with the standard dual EnKF, it imposes a new update step to the state, which is shown to enhance the performance of the dual approach with almost no increase in the computational cost. Numerical experiments are conducted with a two-dimensional (2-D) synthetic groundwater aquifer model to investigate the performance and robustness of the proposed dual EnKFOSA, and to evaluate its results against those of the joint and dual EnKFs. The proposed scheme is able to successfully recover both the hydraulic head and the aquifer conductivity, providing further reliable estimates of their uncertainties. Furthermore, it is found to be more robust to different assimilation settings, such as the spatial and temporal distribution of the observations, and the level of noise in the data. Based on our experimental setups, it yields up to 25 % more accurate state and parameter estimations than the joint and dual approaches.

Multi-frequency Phase Unwrap from Noisy Data: Adaptive Least Squares Approach

NASA Astrophysics Data System (ADS)

Katkovnik, Vladimir; Bioucas-Dias, José

2010-04-01

Multiple frequency interferometry is, basically, a phase acquisition strategy aimed at reducing or eliminating the ambiguity of the wrapped phase observations or, equivalently, reducing or eliminating the fringe ambiguity order. In multiple frequency interferometry, the phase measurements are acquired at different frequencies (or wavelengths) and recorded using the corresponding sensors (measurement channels). Assuming that the absolute phase to be reconstructed is piece-wise smooth, we use a nonparametric regression technique for the phase reconstruction. The nonparametric estimates are derived from a local least squares criterion, which, when applied to the multifrequency data, yields denoised (filtered) phase estimates with extended ambiguity (periodized), compared with the phase ambiguities inherent to each measurement frequency. The filtering algorithm is based on local polynomial (LPA) approximation for design of nonlinear filters (estimators) and adaptation of these filters to unknown smoothness of the spatially varying absolute phase [9]. For phase unwrapping, from filtered periodized data, we apply the recently introduced robust (in the sense of discontinuity preserving) PUMA unwrapping algorithm [1]. Simulations give evidence that the proposed algorithm yields state-of-the-art performance for continuous as well as for discontinues phase surfaces, enabling phase unwrapping in extraordinary difficult situations when all other algorithms fail.

On the ``optimal'' spatial distribution and directional anisotropy of the filter-width and grid-resolution in large eddy simulation

NASA Astrophysics Data System (ADS)

Toosi, Siavash; Larsson, Johan

2017-11-01

The accuracy of an LES depends directly on the accuracy of the resolved part of the turbulence. The continuing increase in computational power enables the application of LES to increasingly complex flow problems for which the LES community lacks the experience of knowing what the ``optimal'' or even an ``acceptable'' grid (or equivalently filter-width distribution) is. The goal of this work is to introduce a systematic approach to finding the ``optimal'' grid/filter-width distribution and their ``optimal'' anisotropy. The method is tested first on the turbulent channel flow, mainly to see if it is able to predict the right anisotropy of the filter/grid, and then on the more complicated case of flow over a backward-facing step, to test its ability to predict the right distribution and anisotropy of the filter/grid simultaneously, hence leading to a converged solution. This work has been supported by the Naval Air Warfare Center Aircraft Division at Pax River, MD, under contract N00421132M021. Computing time has been provided by the University of Maryland supercomputing resources (http://hpcc.umd.edu).

Improved methods of performing coherent optical correlation

NASA Technical Reports Server (NTRS)

Husain-Abidi, A. S.

1972-01-01

Coherent optical correlators are described in which complex spatial filters are recorded by a quasi-Fourier transform method. The high-pass spatial filtering effects (due to the dynamic range of photographic films) normally encountered in Vander Lugt type complex filters are not present in this system. Experimental results for both transmittive as well as reflective objects are presented. Experiments are also performed by illuminating the object with diffused light. A correlator using paraboloidal mirror segments as the Fourier-transforming element is also described.

Control of experimental uncertainties in filtered Rayleigh scattering measurements

NASA Technical Reports Server (NTRS)

Forkey, Joseph N.; Finkelstein, N. D.; Lempert, Walter R.; Miles, Richard B.

1995-01-01

Filtered Rayleigh Scattering is a technique which allows for measurement of velocity, temperature, and pressure in unseeded flows, spatially resolved in 2-dimensions. We present an overview of the major components of a Filtered Rayleigh Scattering system. In particular, we develop and discuss a detailed theoretical model along with associated model parameters and related uncertainties. Based on this model, we then present experimental results for ambient room air and for a Mach 2 free jet, including spatially resolved measurements of velocity, temperature, and pressure.

The Improvement of Spatial-Temporal PM2.5 Resolution in Taiwan by Using Data Assimilation Method

NASA Astrophysics Data System (ADS)

Lin, Yong-Qing; Lin, Yuan-Chien

2017-04-01

Forecasting air pollution concentration, e.g., the concentration of PM2.5, is of great significance to protect human health and the environment. Accurate prediction of PM2.5 concentrations is limited in number and the data quality of air quality monitoring stations. The spatial and temporal variations of PM2.5 concentrations are measured by 76 National Air Quality Monitoring Stations (built by the TW-EPA) in Taiwan. The National Air Quality Monitoring Stations are costly and scarce because of the highly precise instrument and their size. Therefore, many places still out of the range of National Air Quality Monitoring Stations. Recently, there are an enormous number of portable air quality sensors called "AirBox" developed jointly by the Taiwan government and a private company. By virtue of its price and portative, the AirBox can provide higher resolution of space-time PM2.5 measurement. However, the spatiotemporal distribution and data quality are different between AirBox and National Air Quality Monitoring Stations. To integrate the heterogeneous PM2.5 data, the data assimilation method should be performed before further analysis. In this study, we propose a data assimilation method based on Ensemble Kalman Filter (EnKF), which is a variant of classic Kalman Filter, can be used to combine additional heterogeneous data from different source while modeling to improve the estimation of spatial-temporal PM2.5 concentration. The assimilation procedure uses the advantages of the two kinds of heterogeneous data and merges them to produce the final estimation. The results have shown that by combining AirBox PM2.5 data as additional information in our model based EnKF can bring the better estimation of spatial-temporal PM2.5 concentration and improve the it's space-time resolution. Under the approach proposed in this study, higher spatial-temporal resoultion could provide a very useful information for a better spatial-temporal data analysis and further environmental management, such as air pollution source localization and micro-scale air pollution analysis. Keywords: PM2.5, Data Assimilation, Ensemble Kalman Filter, Air Quality

Stable time filtering of strongly unstable spatially extended systems

PubMed Central

Grote, Marcus J.; Majda, Andrew J.

2006-01-01

Many contemporary problems in science involve making predictions based on partial observation of extremely complicated spatially extended systems with many degrees of freedom and with physical instabilities on both large and small scale. Various new ensemble filtering strategies have been developed recently for these applications, and new mathematical issues arise. Because ensembles are extremely expensive to generate, one such issue is whether it is possible under appropriate circumstances to take long time steps in an explicit difference scheme and violate the classical Courant–Friedrichs–Lewy (CFL)-stability condition yet obtain stable accurate filtering by using the observations. These issues are explored here both through elementary mathematical theory, which provides simple guidelines, and the detailed study of a prototype model. The prototype model involves an unstable finite difference scheme for a convection–diffusion equation, and it is demonstrated below that appropriate observations can result in stable accurate filtering of this strongly unstable spatially extended system. PMID:16682626

Stable time filtering of strongly unstable spatially extended systems.

PubMed

Grote, Marcus J; Majda, Andrew J

2006-05-16

Many contemporary problems in science involve making predictions based on partial observation of extremely complicated spatially extended systems with many degrees of freedom and with physical instabilities on both large and small scale. Various new ensemble filtering strategies have been developed recently for these applications, and new mathematical issues arise. Because ensembles are extremely expensive to generate, one such issue is whether it is possible under appropriate circumstances to take long time steps in an explicit difference scheme and violate the classical Courant-Friedrichs-Lewy (CFL)-stability condition yet obtain stable accurate filtering by using the observations. These issues are explored here both through elementary mathematical theory, which provides simple guidelines, and the detailed study of a prototype model. The prototype model involves an unstable finite difference scheme for a convection-diffusion equation, and it is demonstrated below that appropriate observations can result in stable accurate filtering of this strongly unstable spatially extended system.

Combination of oriented partial differential equation and shearlet transform for denoising in electronic speckle pattern interferometry fringe patterns.

PubMed

Xu, Wenjun; Tang, Chen; Gu, Fan; Cheng, Jiajia

2017-04-01

It is a key step to remove the massive speckle noise in electronic speckle pattern interferometry (ESPI) fringe patterns. In the spatial-domain filtering methods, oriented partial differential equations have been demonstrated to be a powerful tool. In the transform-domain filtering methods, the shearlet transform is a state-of-the-art method. In this paper, we propose a filtering method for ESPI fringe patterns denoising, which is a combination of second-order oriented partial differential equation (SOOPDE) and the shearlet transform, named SOOPDE-Shearlet. Here, the shearlet transform is introduced into the ESPI fringe patterns denoising for the first time. This combination takes advantage of the fact that the spatial-domain filtering method SOOPDE and the transform-domain filtering method shearlet transform benefit from each other. We test the proposed SOOPDE-Shearlet on five experimentally obtained ESPI fringe patterns with poor quality and compare our method with SOOPDE, shearlet transform, windowed Fourier filtering (WFF), and coherence-enhancing diffusion (CEDPDE). Among them, WFF and CEDPDE are the state-of-the-art methods for ESPI fringe patterns denoising in transform domain and spatial domain, respectively. The experimental results have demonstrated the good performance of the proposed SOOPDE-Shearlet.

CHAMP: a locally adaptive unmixing-based hyperspectral anomaly detection algorithm

NASA Astrophysics Data System (ADS)

Crist, Eric P.; Thelen, Brian J.; Carrara, David A.

1998-10-01

Anomaly detection offers a means by which to identify potentially important objects in a scene without prior knowledge of their spectral signatures. As such, this approach is less sensitive to variations in target class composition, atmospheric and illumination conditions, and sensor gain settings than would be a spectral matched filter or similar algorithm. The best existing anomaly detectors generally fall into one of two categories: those based on local Gaussian statistics, and those based on linear mixing moles. Unmixing-based approaches better represent the real distribution of data in a scene, but are typically derived and applied on a global or scene-wide basis. Locally adaptive approaches allow detection of more subtle anomalies by accommodating the spatial non-homogeneity of background classes in a typical scene, but provide a poorer representation of the true underlying background distribution. The CHAMP algorithm combines the best attributes of both approaches, applying a linear-mixing model approach in a spatially adaptive manner. The algorithm itself, and teste results on simulated and actual hyperspectral image data, are presented in this paper.

Tracking Virus Particles in Fluorescence Microscopy Images Using Multi-Scale Detection and Multi-Frame Association.

PubMed

Jaiswal, Astha; Godinez, William J; Eils, Roland; Lehmann, Maik Jorg; Rohr, Karl

2015-11-01

Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.

VAUD: A Visual Analysis Approach for Exploring Spatio-Temporal Urban Data.

PubMed

Chen, Wei; Huang, Zhaosong; Wu, Feiran; Zhu, Minfeng; Guan, Huihua; Maciejewski, Ross

2017-10-02

Urban data is massive, heterogeneous, and spatio-temporal, posing a substantial challenge for visualization and analysis. In this paper, we design and implement a novel visual analytics approach, Visual Analyzer for Urban Data (VAUD), that supports the visualization, querying, and exploration of urban data. Our approach allows for cross-domain correlation from multiple data sources by leveraging spatial-temporal and social inter-connectedness features. Through our approach, the analyst is able to select, filter, aggregate across multiple data sources and extract information that would be hidden to a single data subset. To illustrate the effectiveness of our approach, we provide case studies on a real urban dataset that contains the cyber-, physical-, and socialinformation of 14 million citizens over 22 days.

A Comparative Study on the Detection of Covert Attention in Event-Related EEG and MEG Signals to Control a BCI

PubMed Central

Reichert, Christoph; Dürschmid, Stefan; Heinze, Hans-Jochen; Hinrichs, Hermann

2017-01-01

In brain-computer interface (BCI) applications the detection of neural processing as revealed by event-related potentials (ERPs) is a frequently used approach to regain communication for people unable to interact through any peripheral muscle control. However, the commonly used electroencephalography (EEG) provides signals of low signal-to-noise ratio, making the systems slow and inaccurate. As an alternative noninvasive recording technique, the magnetoencephalography (MEG) could provide more advantageous electrophysiological signals due to a higher number of sensors and the magnetic fields not being influenced by volume conduction. We investigated whether MEG provides higher accuracy in detecting event-related fields (ERFs) compared to detecting ERPs in simultaneously recorded EEG, both evoked by a covert attention task, and whether a combination of the modalities is advantageous. In our approach, a detection algorithm based on spatial filtering is used to identify ERP/ERF components in a data-driven manner. We found that MEG achieves higher decoding accuracy (DA) compared to EEG and that the combination of both further improves the performance significantly. However, MEG data showed poor performance in cross-subject classification, indicating that the algorithm's ability for transfer learning across subjects is better in EEG. Here we show that BCI control by covert attention is feasible with EEG and MEG using a data-driven spatial filter approach with a clear advantage of the MEG regarding DA but with a better transfer learning in EEG. PMID:29085279

Irrelevant Singletons in Pop-Out Search: Attentional Capture or Filtering Costs?

ERIC Educational Resources Information Center

Becker, Stefanie I.

2007-01-01

The aim of the present study was to investigate whether costs invoked by the presence of an irrelevant singleton distractor in a visual search task are due to attentional capture by the irrelevant singleton or spatially unrelated filtering costs. Measures of spatial effects were based on distance effects, compatibility effects, and differences…

Anti-impulse-noise Edge Detection via Anisotropic Morphological Directional Derivatives.

PubMed

Shui, Peng-Lang; Wang, Fu-Ping

2017-07-13

Traditional differential-based edge detection suffers from abrupt degradation in performance when images are corrupted by impulse noises. The morphological operators such as the median filters and weighted median filters possess the intrinsic ability to counteract impulse noise. In this paper, by combining the biwindow configuration with weighted median filters, anisotropic morphological directional derivatives (AMDD) robust to impulse noise are proposed to measure the local grayscale variation around a pixel. For ideal step edges, the AMDD spatial response and directional representation are derived. The characteristics and edge resolution of two kinds of typical biwindows are analyzed thoroughly. In terms of the AMDD spatial response and directional representation of ideal step edges, the spatial matched filter is used to extract the edge strength map (ESM) from the AMDDs of an image. The spatial and directional matched filters are used to extract the edge direction map (EDM). Embedding the extracted ESM and EDM into the standard route of the differential-based edge detection, an anti-impulse-noise AMDD-based edge detector is constructed. It is compared with the existing state-of-the-art detectors on a recognized image dataset for edge detection evaluation. The results show that it attains competitive performance in noise-free and Gaussian noise cases and the best performance in impulse noise cases.

High-resolution land cover classification using low resolution global data

NASA Astrophysics Data System (ADS)

Carlotto, Mark J.

2013-05-01

A fusion approach is described that combines texture features from high-resolution panchromatic imagery with land cover statistics derived from co-registered low-resolution global databases to obtain high-resolution land cover maps. The method does not require training data or any human intervention. We use an MxN Gabor filter bank consisting of M=16 oriented bandpass filters (0-180°) at N resolutions (3-24 meters/pixel). The size range of these spatial filters is consistent with the typical scale of manmade objects and patterns of cultural activity in imagery. Clustering reduces the complexity of the data by combining pixels that have similar texture into clusters (regions). Texture classification assigns a vector of class likelihoods to each cluster based on its textural properties. Classification is unsupervised and accomplished using a bank of texture anomaly detectors. Class likelihoods are modulated by land cover statistics derived from lower resolution global data over the scene. Preliminary results from a number of Quickbird scenes show our approach is able to classify general land cover features such as roads, built up area, forests, open areas, and bodies of water over a wide range of scenes.

An Improved Framework for Confound Regression and Filtering for Control of Motion Artifact in the Preprocessing of Resting-State Functional Connectivity Data

PubMed Central

Satterthwaite, Theodore D.; Elliott, Mark A.; Gerraty, Raphael T.; Ruparel, Kosha; Loughead, James; Calkins, Monica E.; Eickhoff, Simon B.; Hakonarson, Hakon; Gur, Ruben C.; Gur, Raquel E.; Wolf, Daniel H.

2013-01-01

Several recent reports in large, independent samples have demonstrated the influence of motion artifact on resting-state functional connectivity MRI (rsfc-MRI). Standard rsfc-MRI preprocessing typically includes regression of confounding signals and band-pass filtering. However, substantial heterogeneity exists in how these techniques are implemented across studies, and no prior study has examined the effect of differing approaches for the control of motion-induced artifacts. To better understand how in-scanner head motion affects rsfc-MRI data, we describe the spatial, temporal, and spectral characteristics of motion artifacts in a sample of 348 adolescents. Analyses utilize a novel approach for describing head motion on a voxelwise basis. Next, we systematically evaluate the efficacy of a range of confound regression and filtering techniques for the control of motion-induced artifacts. Results reveal that the effectiveness of preprocessing procedures on the control of motion is heterogeneous, and that improved preprocessing provides a substantial benefit beyond typical procedures. These results demonstrate that the effect of motion on rsfc-MRI can be substantially attenuated through improved preprocessing procedures, but not completely removed. PMID:22926292

Image sharpening for mixed spatial and spectral resolution satellite systems

NASA Technical Reports Server (NTRS)

Hallada, W. A.; Cox, S.

1983-01-01

Two methods of image sharpening (reconstruction) are compared. The first, a spatial filtering technique, extrapolates edge information from a high spatial resolution panchromatic band at 10 meters and adds it to the low spatial resolution narrow spectral bands. The second method, a color normalizing technique, is based on the ability to separate image hue and brightness components in spectral data. Using both techniques, multispectral images are sharpened from 30, 50, 70, and 90 meter resolutions. Error rates are calculated for the two methods and all sharpened resolutions. The results indicate that the color normalizing method is superior to the spatial filtering technique.

Distinct Brain Mechanisms Support Spatial vs. Temporal Filtering of Nociceptive Information

PubMed Central

Nahman-Averbuch, H.; Martucci, K.T.; Granovsky, Y.; Weissman-Fogel, I.; Yarnitsky, D.; Coghill, R. C.

2014-01-01

The role of endogenous analgesic mechanisms has largely been viewed in the context of gain modulation during nociceptive processing. However, these analgesic mechanisms may play critical roles in the extraction and subsequent utilization of information related to spatial and temporal features of nociceptive input. To date, it remains unknown if spatial and temporal filtering of nociceptive information is supported by similar analgesic mechanisms. To address this question, human volunteers were recruited to assess brain activation with functional MRI during conditioned pain modulation (CPM) and offset analgesia (OA). CPM provides one paradigm for assessing spatial filtering of nociceptive information while OA provides a paradigm for assessing temporal filtering of nociceptive information. CPM and OA both produced statistically significant reductions in pain intensity. However, the magnitude of pain reduction elicited by CPM was not correlated with that elicited by OA across different individuals. Different patterns of brain activation were consistent with the psychophysical findings. CPM elicited widespread reductions in regions engaged in nociceptive processing such as the thalamus, insula and SII. OA produced reduced activity in SI, but was associated with greater activation in the anterior insula, dorso-lateral prefrontal cortex, intra-parietal sulcus, and inferior parietal lobule relative to CPM. In the brainstem, CPM consistently produced reductions in activity while OA produced increases in activity. Conjunction analysis confirmed that CPM related activity did not overlap with that of OA. Thus, dissociable mechanisms support inhibitory processes engaged during spatial vs. temporal filtering of nociceptive information. PMID:25047783

Optimized method for atmospheric signal reduction in irregular sampled InSAR time series assisted by external atmospheric information

NASA Astrophysics Data System (ADS)

Gong, W.; Meyer, F. J.

2013-12-01

It is well known that spatio-temporal the tropospheric phase signatures complicate the interpretation and detection of smaller magnitude deformation signals or unstudied motion fields. Several advanced time-series InSAR techniques were developed in the last decade that make assumptions about the stochastic properties of the signal components in interferometric phases to reduce atmospheric delay effects on surface deformation estimates. However, their need for large datasets to successfully separate the different phase contributions limits their performance if data is scarce and irregularly sampled. Limited SAR data coverage is true for many areas affected by geophysical deformation. This is either due to their low priority in mission programming, unfavorable ground coverage condition, or turbulent seasonal weather effects. In this paper, we present new adaptive atmospheric phase filtering algorithms that are specifically designed to reconstruct surface deformation signals from atmosphere-affected and irregularly sampled InSAR time series. The filters take advantage of auxiliary atmospheric delay information that is extracted from various sources, e.g. atmospheric weather models. They are embedded into a model-free Persistent Scatterer Interferometry (PSI) approach that was selected to accommodate non-linear deformation patterns that are often observed near volcanoes and earthquake zones. Two types of adaptive phase filters were developed that operate in the time dimension and separate atmosphere from deformation based on their different temporal correlation properties. Both filter types use the fact that atmospheric models can reliably predict the spatial statistics and signal power of atmospheric phase delay fields in order to automatically optimize the filter's shape parameters. In essence, both filter types will attempt to maximize the linear correlation between a-priori and the extracted atmospheric phase information. Topography-related phase components, orbit errors and the master atmospheric delays are first removed in a pre-processing step before the atmospheric filters are applied. The first adaptive filter type is using a filter kernel of Gaussian shape and is adaptively adjusting the width (defined in days) of this filter until the correlation of extracted and modeled atmospheric signal power is maximized. If atmospheric properties vary along the time series, this approach will lead to filter setting that are adapted to best reproduce atmospheric conditions at a certain observation epoch. Despite the superior performance of this first filter design, its Gaussian shape imposes non-physical relative weights onto acquisitions that ignore the known atmospheric noise in the data. Hence, in our second approach we are using atmospheric a-priori information to adaptively define the full shape of the atmospheric filter. For this process, we use a so-called normalized convolution (NC) approach that is often used in image reconstruction. Several NC designs will be presented in this paper and studied for relative performance. A cross-validation of all developed algorithms was done using both synthetic and real data. This validation showed designed filters are outperforming conventional filter methods that particularly useful for regions with limited data coverage or lack of a deformation field prior.

The spatial extent of polycyclic aromatic hydrocarbons emission in the Herbig star HD 179218

NASA Astrophysics Data System (ADS)

Taha, A. S.; Labadie, L.; Pantin, E.; Matter, A.; Alvarez, C.; Esquej, P.; Grellmann, R.; Rebolo, R.; Telesco, C.; Wolf, S.

2018-04-01

Aim. We investigate, in the mid-infrared, the spatial properties of the polycyclic aromatic hydrocarbons (PAHs) emission in the disk of HD 179218, an intermediate-mass Herbig star at 300 pc. Methods: We obtained mid-infrared images in the PAH-1, PAH-2 and Si-6 filters centered at 8.6, 11.3, and 12.5 μm, and N-band low-resolution spectra using CanariCam on the 10-m Gran Telescopio Canarias (GTC). We compared the point spread function (PSF) profiles measured in the PAH filters to the profile derived in the Si-6 filter, where the thermal continuum emission dominates. We performed radiative transfer modeling of the spectral energy distribution (SED) and produced synthetic images in the three filters to investigate different spatial scenarios. Results: Our data show that the disk emission is spatially resolved in the PAH-1 and PAH-2 filters, while unresolved in the Si-6 filter. Thanks to very good observing conditions, an average full width at half maximum (FWHM) of 0.232'', 0.280'' and 0.293'' is measured in the three filters, respectively. Gaussian disk fitting and quadratic subtraction of the science and calibrator PSFs suggests a lower-limit characteristic angular diameter of the emission of 100 mas, or 30 au. The photometric and spectroscopic results are compatible with previous findings. Our radiative transfer (RT) modeling of the continuum suggests that the resolved emission should result from PAH molecules on the disk atmosphere being UV-excited by the central star. Simple geometrical models of the PAH component compared to the underlying continuum point to a PAH emission uniformly extended out to the physical limits of the disk model. Furthermore, our RT best model of the continuum requires a negative exponent of the surface density power-law, in contrast with earlier modeling pointing to a positive exponent. Conclusions: We have spatially resolved - for the first time to our knowledge - the PAHs emission in the disk of HD 179218 and set constraints on its spatial extent. Based on spatial and spectroscopic considerations as well as on qualitative comparison with IRS 48 and HD 97048, we favor a scenario in which PAHs extend out to large radii across the flared disk surface and are at the same time predominantly in an ionized charge state due to the strong UV radiation field of the 180 L⊙ central star.

Effects of spatial coherence in diffraction phase microscopy.

PubMed

Edwards, Chris; Bhaduri, Basanta; Nguyen, Tan; Griffin, Benjamin G; Pham, Hoa; Kim, Taewoo; Popescu, Gabriel; Goddard, Lynford L

2014-03-10

Quantitative phase imaging systems using white light illumination can exhibit lower noise figures than laser-based systems. However, they can also suffer from object-dependent artifacts, such as halos, which prevent accurate reconstruction of the surface topography. In this work, we show that white light diffraction phase microscopy using a standard halogen lamp can produce accurate height maps of even the most challenging structures provided that there is proper spatial filtering at: 1) the condenser to ensure adequate spatial coherence and 2) the output Fourier plane to produce a uniform reference beam. We explain that these object-dependent artifacts are a high-pass filtering phenomenon, establish design guidelines to reduce the artifacts, and then apply these guidelines to eliminate the halo effect. Since a spatially incoherent source requires significant spatial filtering, the irradiance is lower and proportionally longer exposure times are needed. To circumvent this tradeoff, we demonstrate that a supercontinuum laser, due to its high radiance, can provide accurate measurements with reduced exposure times, allowing for fast dynamic measurements.

Band registration of tuneable frame format hyperspectral UAV imagers in complex scenes

NASA Astrophysics Data System (ADS)

Honkavaara, Eija; Rosnell, Tomi; Oliveira, Raquel; Tommaselli, Antonio

2017-12-01

A recent revolution in miniaturised sensor technology has provided markets with novel hyperspectral imagers operating in the frame format principle. In the case of unmanned aerial vehicle (UAV) based remote sensing, the frame format technology is highly attractive in comparison to the commonly utilised pushbroom scanning technology, because it offers better stability and the possibility to capture stereoscopic data sets, bringing an opportunity for 3D hyperspectral object reconstruction. Tuneable filters are one of the approaches for capturing multi- or hyperspectral frame images. The individual bands are not aligned when operating a sensor based on tuneable filters from a mobile platform, such as UAV, because the full spectrum recording is carried out in the time-sequential principle. The objective of this investigation was to study the aspects of band registration of an imager based on tuneable filters and to develop a rigorous and efficient approach for band registration in complex 3D scenes, such as forests. The method first determines the orientations of selected reference bands and reconstructs the 3D scene using structure-from-motion and dense image matching technologies. The bands, without orientation, are then matched to the oriented bands accounting the 3D scene to provide exterior orientations, and afterwards, hyperspectral orthomosaics, or hyperspectral point clouds, are calculated. The uncertainty aspects of the novel approach were studied. An empirical assessment was carried out in a forested environment using hyperspectral images captured with a hyperspectral 2D frame format camera, based on a tuneable Fabry-Pérot interferometer (FPI) on board a multicopter and supported by a high spatial resolution consumer colour camera. A theoretical assessment showed that the method was capable of providing band registration accuracy better than 0.5-pixel size. The empirical assessment proved the performance and showed that, with the novel method, most parts of the band misalignments were less than the pixel size. Furthermore, it was shown that the performance of the band alignment was dependent on the spatial distance from the reference band.

On the effect of using the Shapiro filter to smooth winds on a sphere

NASA Technical Reports Server (NTRS)

Takacs, L. L.; Balgovind, R. C.

1984-01-01

Spatial differencing schemes which are not enstrophy conserving nor implicitly damping require global filtering of short waves to eliminate the build-up of energy in the shortest wavelengths due to aliasing. Takacs and Balgovind (1983) have shown that filtering on a sphere with a latitude dependent damping function will cause spurious vorticity and divergence source terms to occur if care is not taken to ensure the irrotationality of the gradients of the stream function and velocity potential. Using a shallow water model with fourth-order energy-conserving spatial differencing, it is found that using a 16th-order Shapiro (1979) filter on the winds and heights to control nonlinear instability also creates spurious source terms when the winds are filtered in the meridional direction.

The Multi-Spectral Imaging Diagnostic on Alcator C-MOD and TCV

NASA Astrophysics Data System (ADS)

Linehan, B. L.; Mumgaard, R. T.; Duval, B. P.; Theiler, C. G.; TCV Team

2017-10-01

The Multi-Spectral Imaging (MSI) diagnostic is a new instrument that captures simultaneous spectrally filtered images from a common sight view while maintaining a large tendue and high spatial resolution. The system uses a polychromator layout where each image is sequentially filtered. This procedure yields a high transmission for each spectral channel with minimal vignetting and aberrations. A four-wavelength system was installed on Alcator C-Mod and then moved to TCV. The system uses industrial cameras to simultaneously image the divertor region at 95 frames per second at f/# 2.8 via a coherent fiber bundle (C-Mod) or a lens-based relay optic (TCV). The images are absolutely calibrated and spatially registered enabling accurate measurement of atomic line ratios and absolute line intensities. The images will be used to study divertor detachment by imaging impurities and Balmer series emissions. Furthermore, the large field of view and an ability to support many types of detectors opens the door for other novel approaches to optically measuring plasma with high temporal, spatial, and spectral resolution. Such measurements will allow for the study of Stark broadening and divertor turbulence. Here, we present the first measurements taken with this cavity imaging system. USDoE awards DE-FC02-99ER54512 and award DE-AC05-06OR23100, ORISE, administered by ORAU.

Portable, stand-off spectral imaging camera for detection of effluents and residues

NASA Astrophysics Data System (ADS)

Goldstein, Neil; St. Peter, Benjamin; Grot, Jonathan; Kogan, Michael; Fox, Marsha; Vujkovic-Cvijin, Pajo; Penny, Ryan; Cline, Jason

2015-06-01

A new, compact and portable spectral imaging camera, employing a MEMs-based encoded imaging approach, has been built and demonstrated for detection of hazardous contaminants including gaseous effluents and solid-liquid residues on surfaces. The camera is called the Thermal infrared Reconfigurable Analysis Camera for Effluents and Residues (TRACER). TRACER operates in the long wave infrared and has the potential to detect a wide variety of materials with characteristic spectral signatures in that region. The 30 lb. camera is tripod mounted and battery powered. A touch screen control panel provides a simple user interface for most operations. The MEMS spatial light modulator is a Texas Instruments Digital Microarray Array with custom electronics and firmware control. Simultaneous 1D-spatial and 1Dspectral dimensions are collected, with the second spatial dimension obtained by scanning the internal spectrometer slit. The sensor can be configured to collect data in several modes including full hyperspectral imagery using Hadamard multiplexing, panchromatic thermal imagery, and chemical-specific contrast imagery, switched with simple user commands. Matched filters and other analog filters can be generated internally on-the-fly and applied in hardware, substantially reducing detection time and improving SNR over HSI software processing, while reducing storage requirements. Results of preliminary instrument evaluation and measurements of flame exhaust are presented.

Preprocessing of SAR interferometric data using anisotropic diffusion filter

NASA Astrophysics Data System (ADS)

Sartor, Kenneth; Allen, Josef De Vaughn; Ganthier, Emile; Tenali, Gnana Bhaskar

2007-04-01

The most commonly used smoothing algorithms for complex data processing are blurring functions (i.e., Hanning, Taylor weighting, Gaussian, etc.). Unfortunately, the filters so designed blur the edges in a Synthetic Aperture Radar (SAR) scene, reduce the accuracy of features, and blur the fringe lines in an interferogram. For the Digital Surface Map (DSM) extraction, the blurring of these fringe lines causes inaccuracies in the height of the unwrapped terrain surface. Our goal here is to perform spatially non-uniform smoothing to overcome the above mentioned disadvantages. This is achieved by using a Complex Anisotropic Non-Linear Diffuser (CANDI) filter that is a spatially varying. In particular, an appropriate choice of the convection function in the CANDI filter is able to accomplish the non-uniform smoothing. This boundary sharpening intra-region smoothing filter acts on interferometric SAR (IFSAR) data with noise to produce an interferogram with significantly reduced noise contents and desirable local smoothing. Results of CANDI filtering will be discussed and compared with those obtained by using the standard filters on simulated data.

GOES Cloud Detection at the Global Hydrology and Climate Center

NASA Technical Reports Server (NTRS)

Laws, Kevin; Jedlovec, Gary J.; Arnold, James E. (Technical Monitor)

2002-01-01

The bi-spectral threshold (BTH) for cloud detection and height assignment is now operational at NASA's Global Hydrology and Climate Center (GHCC). This new approach is similar in principle to the bi-spectral spatial coherence (BSC) method with improvements made to produce a more robust cloud-filtering algorithm for nighttime cloud detection and subsequent 24-hour operational cloud top pressure assignment. The method capitalizes on cloud and surface emissivity differences from the GOES 3.9 and 10.7-micrometer channels to distinguish cloudy from clear pixels. Separate threshold values are determined for day and nighttime detection, and applied to a 20-day minimum composite difference image to better filter background effects and enhance differences in cloud properties. A cloud top pressure is assigned to each cloudy pixel by referencing the 10.7-micrometer channel temperature to a thermodynamic profile from a locally -run regional forecast model. This paper and supplemental poster will present an objective validation of nighttime cloud detection by the BTH approach in comparison with previous methods. The cloud top pressure will be evaluated by comparing to the NESDIS operational CO2 slicing approach.

HARDI denoising using nonlocal means on S2

NASA Astrophysics Data System (ADS)

Kuurstra, Alan; Dolui, Sudipto; Michailovich, Oleg

2012-02-01

Diffusion MRI (dMRI) is a unique imaging modality for in vivo delineation of the anatomical structure of white matter in the brain. In particular, high angular resolution diffusion imaging (HARDI) is a specific instance of dMRI which is known to excel in detection of multiple neural fibers within a single voxel. Unfortunately, the angular resolution of HARDI is known to be inversely proportional to SNR, which makes the problem of denoising of HARDI data be of particular practical importance. Since HARDI signals are effectively band-limited, denoising can be accomplished by means of linear filtering. However, the spatial dependency of diffusivity in brain tissue makes it impossible to find a single set of linear filter parameters which is optimal for all types of diffusion signals. Hence, adaptive filtering is required. In this paper, we propose a new type of non-local means (NLM) filtering which possesses the required adaptivity property. As opposed to similar methods in the field, however, the proposed NLM filtering is applied in the spherical domain of spatial orientations. Moreover, the filter uses an original definition of adaptive weights, which are designed to be invariant to both spatial rotations as well as to a particular sampling scheme in use. As well, we provide a detailed description of the proposed filtering procedure, its efficient implementation, as well as experimental results with synthetic data. We demonstrate that our filter has substantially better adaptivity as compared to a number of alternative methods.

The Amateur Scientist: Simple Optical Experiments in Which Spatial Filtering Removes the "Noise" from Pictures.

ERIC Educational Resources Information Center

Walker, Jearl

1982-01-01

Spatial filtering, based on diffraction/interference of light waves, is a technique by which unwanted information in a picture ("noise") can be separated from wanted information. A series of experiments is described in which students can create a system that functions as an optical computer to create clearer pictures. (Author/JN)

A systems approach for data compression and latency reduction in cortically controlled brain machine interfaces.

PubMed

Oweiss, Karim G

2006-07-01

This paper suggests a new approach for data compression during extracutaneous transmission of neural signals recorded by high-density microelectrode array in the cortex. The approach is based on exploiting the temporal and spatial characteristics of the neural recordings in order to strip the redundancy and infer the useful information early in the data stream. The proposed signal processing algorithms augment current filtering and amplification capability and may be a viable replacement to on chip spike detection and sorting currently employed to remedy the bandwidth limitations. Temporal processing is devised by exploiting the sparseness capabilities of the discrete wavelet transform, while spatial processing exploits the reduction in the number of physical channels through quasi-periodic eigendecomposition of the data covariance matrix. Our results demonstrate that substantial improvements are obtained in terms of lower transmission bandwidth, reduced latency and optimized processor utilization. We also demonstrate the improvements qualitatively in terms of superior denoising capabilities and higher fidelity of the obtained signals.

Comparison of ocean mass content change from direct and inversion based approaches

NASA Astrophysics Data System (ADS)

Uebbing, Bernd; Kusche, Jürgen; Rietbroek, Roelof

2017-04-01

The GRACE satellite mission provides an indispensable tool for measuring oceanic mass variations. Such time series are essential to separate global mean sea level rise in thermosteric and mass driven contributions, and thus to constrain ocean heat content and (deep) ocean warming when viewed together with altimetry and Argo data. However, published estimates over the GRACE era differ, not only depending on the time window considered. Here, we will look into sources of such differences with direct and inverse approaches. Deriving ocean mass time series requires several processing steps; choosing a GRACE (and altimetry and Argo) product, data coverage, masks and filters to be applied in either spatial or spectral domain, corrections related to spatial leakage, GIA and geocenter motion need to be accounted for. In this study, we quantify the effects of individual processing choices and assumptions of the direct and inversion based approaches to derive ocean mass content change. Furthermore, we compile the different estimates from existing literature and sources, to highlight the differences.

Single-trial laser-evoked potentials feature extraction for prediction of pain perception.

PubMed

Huang, Gan; Xiao, Ping; Hu, Li; Hung, Yeung Sam; Zhang, Zhiguo

2013-01-01

Pain is a highly subjective experience, and the availability of an objective assessment of pain perception would be of great importance for both basic and clinical applications. The objective of the present study is to develop a novel approach to extract pain-related features from single-trial laser-evoked potentials (LEPs) for classification of pain perception. The single-trial LEP feature extraction approach combines a spatial filtering using common spatial pattern (CSP) and a multiple linear regression (MLR). The CSP method is effective in separating laser-evoked EEG response from ongoing EEG activity, while MLR is capable of automatically estimating the amplitudes and latencies of N2 and P2 from single-trial LEP waveforms. The extracted single-trial LEP features are used in a Naïve Bayes classifier to classify different levels of pain perceived by the subjects. The experimental results show that the proposed single-trial LEP feature extraction approach can effectively extract pain-related LEP features for achieving high classification accuracy.

Multi-channel spatialization systems for audio signals

NASA Technical Reports Server (NTRS)

Begault, Durand R. (Inventor)

1993-01-01

Synthetic head related transfer functions (HRTF's) for imposing reprogrammable spatial cues to a plurality of audio input signals included, for example, in multiple narrow-band audio communications signals received simultaneously are generated and stored in interchangeable programmable read only memories (PROM's) which store both head related transfer function impulse response data and source positional information for a plurality of desired virtual source locations. The analog inputs of the audio signals are filtered and converted to digital signals from which synthetic head related transfer functions are generated in the form of linear phase finite impulse response filters. The outputs of the impulse response filters are subsequently reconverted to analog signals, filtered, mixed, and fed to a pair of headphones.

Multi-channel spatialization system for audio signals

NASA Technical Reports Server (NTRS)

Begault, Durand R. (Inventor)

1995-01-01

Synthetic head related transfer functions (HRTF's) for imposing reprogramable spatial cues to a plurality of audio input signals included, for example, in multiple narrow-band audio communications signals received simultaneously are generated and stored in interchangeable programmable read only memories (PROM's) which store both head related transfer function impulse response data and source positional information for a plurality of desired virtual source locations. The analog inputs of the audio signals are filtered and converted to digital signals from which synthetic head related transfer functions are generated in the form of linear phase finite impulse response filters. The outputs of the impulse response filters are subsequently reconverted to analog signals, filtered, mixed and fed to a pair of headphones.

Sparse-view photoacoustic tomography using virtual parallel-projections and spatially adaptive filtering

NASA Astrophysics Data System (ADS)

Wang, Yihan; Lu, Tong; Wan, Wenbo; Liu, Lingling; Zhang, Songhe; Li, Jiao; Zhao, Huijuan; Gao, Feng

2018-02-01

To fully realize the potential of photoacoustic tomography (PAT) in preclinical and clinical applications, rapid measurements and robust reconstructions are needed. Sparse-view measurements have been adopted effectively to accelerate the data acquisition. However, since the reconstruction from the sparse-view sampling data is challenging, both of the effective measurement and the appropriate reconstruction should be taken into account. In this study, we present an iterative sparse-view PAT reconstruction scheme where a virtual parallel-projection concept matching for the proposed measurement condition is introduced to help to achieve the "compressive sensing" procedure of the reconstruction, and meanwhile the spatially adaptive filtering fully considering the a priori information of the mutually similar blocks existing in natural images is introduced to effectively recover the partial unknown coefficients in the transformed domain. Therefore, the sparse-view PAT images can be reconstructed with higher quality compared with the results obtained by the universal back-projection (UBP) algorithm in the same sparse-view cases. The proposed approach has been validated by simulation experiments, which exhibits desirable performances in image fidelity even from a small number of measuring positions.

Vehicle monitoring under Vehicular Ad-Hoc Networks (VANET) parameters employing illumination invariant correlation filters for the Pakistan motorway police

NASA Astrophysics Data System (ADS)

Gardezi, A.; Umer, T.; Butt, F.; Young, R. C. D.; Chatwin, C. R.

2016-04-01

A spatial domain optimal trade-off Maximum Average Correlation Height (SPOT-MACH) filter has been previously developed and shown to have advantages over frequency domain implementations in that it can be made locally adaptive to spatial variations in the input image background clutter and normalised for local intensity changes. The main concern for using the SPOT-MACH is its computationally intensive nature. However in the past enhancements techniques were proposed for the SPOT-MACH to make its execution time comparable to its frequency domain counterpart. In this paper a novel approach is discussed which uses VANET parameters coupled with the SPOT-MACH in order to minimise the extensive processing of the large video dataset acquired from the Pakistan motorways surveillance system. The use of VANET parameters gives us an estimation criterion of the flow of traffic on the Pakistan motorway network and acts as a precursor to the training algorithm. The use of VANET in this scenario would contribute heavily towards the computational complexity minimization of the proposed monitoring system.

Optical Correlation of Images With Signal-Dependent Noise Using Constrained-Modulation Filter Devices

NASA Technical Reports Server (NTRS)

Downie, John D.

1995-01-01

Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

Single laser beam of spatial coherence from an array of GaAs lasers - Free-running mode

NASA Technical Reports Server (NTRS)

Philipp-Rutz, E. M.

1975-01-01

Spatially coherent radiation from a monolithic array of three GaAs lasers in a free-running mode is reported. The lasers, with their mirror faces antireflection coated, are operated in an external optical cavity built of spherical lenses and plane mirrors. The spatially coherent-beam formation makes use of the Fourier-transformation property of the internal lenses. Transverse mode control is accomplished by a spatial filter. The optical cavity is similar to that used for the phase-controlled mode of spatially coherent-beam formation; only the spatial filters are different. In the far field (when restored by an external lens), the intensities of the lasers in the array are concentrated in a single laser beam of spatial coherence, without any grating lobes. The far-field distribution of the laser array in the free-running mode differs significantly from the interference pattern of the phase-controlled mode. The modulation characteristics of the optical waveforms of the two modes are also quite different because modulation is related to the interaction of the spatial filter with the longitudinal modes of the laser array within the optical cavity. The modulation of the optical waveform of the free-running mode is nonperiodic, confirming that the fluctuations of the optical fields of the lasers are random.

Selection of optimal spectral sensitivity functions for color filter arrays.

PubMed

Parmar, Manu; Reeves, Stanley J

2010-12-01

A color image meant for human consumption can be appropriately displayed only if at least three distinct color channels are present. Typical digital cameras acquire three-color images with only one sensor. A color filter array (CFA) is placed on the sensor such that only one color is sampled at a particular spatial location. This sparsely sampled signal is then reconstructed to form a color image with information about all three colors at each location. In this paper, we show that the wavelength sensitivity functions of the CFA color filters affect both the color reproduction ability and the spatial reconstruction quality of recovered images. We present a method to select perceptually optimal color filter sensitivity functions based upon a unified spatial-chromatic sampling framework. A cost function independent of particular scenes is defined that expresses the error between a scene viewed by the human visual system and the reconstructed image that represents the scene. A constrained minimization of the cost function is used to obtain optimal values of color-filter sensitivity functions for several periodic CFAs. The sensitivity functions are shown to perform better than typical RGB and CMY color filters in terms of both the s-CIELAB ∆E error metric and a qualitative assessment.

Controlling nitrogen migration through micro-nano networks

NASA Astrophysics Data System (ADS)

Cai, Dongqing; Wu, Zhengyan; Jiang, Jiang; Wu, Yuejin; Feng, Huiyun; Brown, Ian G.; Chu, Paul K.; Yu, Zengliang

2014-01-01

Nitrogen fertilizer unabsorbed by crops eventually discharges into the environment through runoff, leaching and volatilization, resulting in three-dimensional (3D) pollution spanning from underground into space. Here we describe an approach for controlling nitrogen loss, developed using loss control fertilizer (LCF) prepared by adding modified natural nanoclay (attapulgite) to traditional fertilizer. In the aqueous phase, LCF self-assembles to form 3D micro/nano networks via hydrogen bonds and other weak interactions, obtaining a higher nitrogen spatial scale so that it is retained by a soil filtering layer. Thus nitrogen loss is reduced and sufficient nutrition for crops is supplied, while the pollution risk of the fertilizer is substantially lowered. As such, self-fabrication of nano-material was used to manipulate the nitrogen spatial scale, which provides a novel and promising approach for the research and control of the migration of other micro-scaled pollutants in environmental medium.

Dynamic design of ecological monitoring networks for non-Gaussian spatio-temporal data

USGS Publications Warehouse

Wikle, C.K.; Royle, J. Andrew

2005-01-01

Many ecological processes exhibit spatial structure that changes over time in a coherent, dynamical fashion. This dynamical component is often ignored in the design of spatial monitoring networks. Furthermore, ecological variables related to processes such as habitat are often non-Gaussian (e.g. Poisson or log-normal). We demonstrate that a simulation-based design approach can be used in settings where the data distribution is from a spatio-temporal exponential family. The key random component in the conditional mean function from this distribution is then a spatio-temporal dynamic process. Given the computational burden of estimating the expected utility of various designs in this setting, we utilize an extended Kalman filter approximation to facilitate implementation. The approach is motivated by, and demonstrated on, the problem of selecting sampling locations to estimate July brood counts in the prairie pothole region of the U.S.

Controlling nitrogen migration through micro-nano networks.

PubMed

Cai, Dongqing; Wu, Zhengyan; Jiang, Jiang; Wu, Yuejin; Feng, Huiyun; Brown, Ian G; Chu, Paul K; Yu, Zengliang

2014-01-14

Nitrogen fertilizer unabsorbed by crops eventually discharges into the environment through runoff, leaching and volatilization, resulting in three-dimensional (3D) pollution spanning from underground into space. Here we describe an approach for controlling nitrogen loss, developed using loss control fertilizer (LCF) prepared by adding modified natural nanoclay (attapulgite) to traditional fertilizer. In the aqueous phase, LCF self-assembles to form 3D micro/nano networks via hydrogen bonds and other weak interactions, obtaining a higher nitrogen spatial scale so that it is retained by a soil filtering layer. Thus nitrogen loss is reduced and sufficient nutrition for crops is supplied, while the pollution risk of the fertilizer is substantially lowered. As such, self-fabrication of nano-material was used to manipulate the nitrogen spatial scale, which provides a novel and promising approach for the research and control of the migration of other micro-scaled pollutants in environmental medium.

Rapid mapping of polarization switching through complete information acquisition

NASA Astrophysics Data System (ADS)

Somnath, Suhas; Belianinov, Alex; Kalinin, Sergei V.; Jesse, Stephen

2016-12-01

Polarization switching in ferroelectric and multiferroic materials underpins a broad range of current and emergent applications, ranging from random access memories to field-effect transistors, and tunnelling devices. Switching in these materials is exquisitely sensitive to local defects and microstructure on the nanometre scale, necessitating spatially resolved high-resolution studies of these phenomena. Classical piezoresponse force microscopy and spectroscopy, although providing necessary spatial resolution, are fundamentally limited in data acquisition rates and energy resolution. This limitation stems from their two-tiered measurement protocol that combines slow (~1 s) switching and fast (~10 kHz-1 MHz) detection waveforms. Here we develop an approach for rapid probing of ferroelectric switching using direct strain detection of material response to probe bias. This approach, facilitated by high-sensitivity electronics and adaptive filtering, enables spectroscopic imaging at a rate 3,504 times faster the current state of the art, achieving high-veracity imaging of polarization dynamics in complex microstructures.

Controlling nitrogen migration through micro-nano networks

PubMed Central

Cai, Dongqing; Wu, Zhengyan; Jiang, Jiang; Wu, Yuejin; Feng, Huiyun; Brown, Ian G.; Chu, Paul K.; Yu, Zengliang

2014-01-01

Nitrogen fertilizer unabsorbed by crops eventually discharges into the environment through runoff, leaching and volatilization, resulting in three-dimensional (3D) pollution spanning from underground into space. Here we describe an approach for controlling nitrogen loss, developed using loss control fertilizer (LCF) prepared by adding modified natural nanoclay (attapulgite) to traditional fertilizer. In the aqueous phase, LCF self-assembles to form 3D micro/nano networks via hydrogen bonds and other weak interactions, obtaining a higher nitrogen spatial scale so that it is retained by a soil filtering layer. Thus nitrogen loss is reduced and sufficient nutrition for crops is supplied, while the pollution risk of the fertilizer is substantially lowered. As such, self-fabrication of nano-material was used to manipulate the nitrogen spatial scale, which provides a novel and promising approach for the research and control of the migration of other micro-scaled pollutants in environmental medium. PMID:24419037

Single-Chip FPGA Azimuth Pre-Filter for SAR

NASA Technical Reports Server (NTRS)

Gudim, Mimi; Cheng, Tsan-Huei; Madsen, Soren; Johnson, Robert; Le, Charles T-C; Moghaddam, Mahta; Marina, Miguel

2005-01-01

A field-programmable gate array (FPGA) on a single lightweight, low-power integrated-circuit chip has been developed to implement an azimuth pre-filter (AzPF) for a synthetic-aperture radar (SAR) system. The AzPF is needed to enable more efficient use of data-transmission and data-processing resources: In broad terms, the AzPF reduces the volume of SAR data by effectively reducing the azimuth resolution, without loss of range resolution, during times when end users are willing to accept lower azimuth resolution as the price of rapid access to SAR imagery. The data-reduction factor is selectable at a decimation factor, M, of 2, 4, 8, 16, or 32 so that users can trade resolution against processing and transmission delays. In principle, azimuth filtering could be performed in the frequency domain by use of fast-Fourier-transform processors. However, in the AzPF, azimuth filtering is performed in the time domain by use of finite-impulse-response filters. The reason for choosing the time-domain approach over the frequency-domain approach is that the time-domain approach demands less memory and a lower memory-access rate. The AzPF operates on the raw digitized SAR data. The AzPF includes a digital in-phase/quadrature (I/Q) demodulator. In general, an I/Q demodulator effects a complex down-conversion of its input signal followed by low-pass filtering, which eliminates undesired sidebands. In the AzPF case, the I/Q demodulator takes offset video range echo data to the complex baseband domain, ensuring preservation of signal phase through the azimuth pre-filtering process. In general, in an SAR I/Q demodulator, the intermediate frequency (fI) is chosen to be a quarter of the range-sampling frequency and the pulse-repetition frequency (fPR) is chosen to be a multiple of fI. The AzPF also includes a polyphase spatial-domain pre-filter comprising four weighted integrate-and-dump filters with programmable decimation factors and overlapping phases. To prevent aliasing of signals, the bandwidth of the AzPF is made 80 percent of fPR/M. The choice of four as the number of overlapping phases is justified by prior research in which it was shown that a filter of length 4M can effect an acceptable transfer function. The figure depicts prototype hardware comprising the AzPF and ancillary electronic circuits. The hardware was found to satisfy performance requirements in real-time tests at a sampling rate of 100 MHz.

Distinct brain mechanisms support spatial vs temporal filtering of nociceptive information.

PubMed

Nahman-Averbuch, Hadas; Martucci, Katherine T; Granovsky, Yelena; Weissman-Fogel, Irit; Yarnitsky, David; Coghill, Robert C

2014-12-01

The role of endogenous analgesic mechanisms has largely been viewed in the context of gain modulation during nociceptive processing. However, these analgesic mechanisms may play critical roles in the extraction and subsequent utilization of information related to spatial and temporal features of nociceptive input. To date, it remains unknown if spatial and temporal filtering of nociceptive information is supported by similar analgesic mechanisms. To address this question, human volunteers were recruited to assess brain activation with functional magnetic resonance imaging during conditioned pain modulation (CPM) and offset analgesia (OA). CPM provides one paradigm for assessing spatial filtering of nociceptive information while OA provides a paradigm for assessing temporal filtering of nociceptive information. CPM and OA both produced statistically significant reductions in pain intensity. However, the magnitude of pain reduction elicited by CPM was not correlated with that elicited by OA across different individuals. Different patterns of brain activation were consistent with the psychophysical findings. CPM elicited widespread reductions in regions engaged in nociceptive processing such as the thalamus, insula, and secondary somatosensory cortex. OA produced reduced activity in the primary somatosensory cortex but was associated with greater activation in the anterior insula, dorsolateral prefrontal cortex, intraparietal sulcus, and inferior parietal lobule relative to CPM. In the brain stem, CPM consistently produced reductions in activity, while OA produced increases in activity. Conjunction analysis confirmed that CPM-related activity did not overlap with that of OA. Thus, dissociable mechanisms support inhibitory processes engaged during spatial vs temporal filtering of nociceptive information. Copyright © 2014 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Computational multispectral video imaging [Invited].

PubMed

Wang, Peng; Menon, Rajesh

2018-01-01

Multispectral imagers reveal information unperceivable to humans and conventional cameras. Here, we demonstrate a compact single-shot multispectral video-imaging camera by placing a micro-structured diffractive filter in close proximity to the image sensor. The diffractive filter converts spectral information to a spatial code on the sensor pixels. Following a calibration step, this code can be inverted via regularization-based linear algebra to compute the multispectral image. We experimentally demonstrated spectral resolution of 9.6 nm within the visible band (430-718 nm). We further show that the spatial resolution is enhanced by over 30% compared with the case without the diffractive filter. We also demonstrate Vis-IR imaging with the same sensor. Because no absorptive color filters are utilized, sensitivity is preserved as well. Finally, the diffractive filters can be easily manufactured using optical lithography and replication techniques.

Counting Magnetic Bipoles on the Sun by Polarity Inversion

NASA Technical Reports Server (NTRS)

Jones, Harrison P.

2004-01-01

This paper presents a simple and efficient algorithm for deriving images of polarity inversion from NSO/Kitt Peak magnetograms without use of contouring routines and shows by example how these maps depend upon the spatial scale for filtering the raw data. Smaller filtering scales produce many localized closed contours in mixed polarity regions while supergranular and larger filtering scales produce more global patterns. The apparent continuity of an inversion line depends on how the spatial filtering is accomplished, but its shape depends only on scale. The total length of the magnetic polarity inversion contours varies as a power law of the filter scale with fractal dimension of order 1.9. The amplitude but nut the exponent of this power-law relation varies with solar activity. The results are compared to similar analyses of areal distributions of bipolar magnetic regions.

Advancing the detection of steady-state visual evoked potentials in brain-computer interfaces

NASA Astrophysics Data System (ADS)

Abu-Alqumsan, Mohammad; Peer, Angelika

2016-06-01

Objective. Spatial filtering has proved to be a powerful pre-processing step in detection of steady-state visual evoked potentials and boosted typical detection rates both in offline analysis and online SSVEP-based brain-computer interface applications. State-of-the-art detection methods and the spatial filters used thereby share many common foundations as they all build upon the second order statistics of the acquired Electroencephalographic (EEG) data, that is, its spatial autocovariance and cross-covariance with what is assumed to be a pure SSVEP response. The present study aims at highlighting the similarities and differences between these methods. Approach. We consider the canonical correlation analysis (CCA) method as a basis for the theoretical and empirical (with real EEG data) analysis of the state-of-the-art detection methods and the spatial filters used thereby. We build upon the findings of this analysis and prior research and propose a new detection method (CVARS) that combines the power of the canonical variates and that of the autoregressive spectral analysis in estimating the signal and noise power levels. Main results. We found that the multivariate synchronization index method and the maximum contrast combination method are variations of the CCA method. All three methods were found to provide relatively unreliable detections in low signal-to-noise ratio (SNR) regimes. CVARS and the minimum energy combination methods were found to provide better estimates for different SNR levels. Significance. Our theoretical and empirical results demonstrate that the proposed CVARS method outperforms other state-of-the-art detection methods when used in an unsupervised fashion. Furthermore, when used in a supervised fashion, a linear classifier learned from a short training session is able to estimate the hidden user intention, including the idle state (when the user is not attending to any stimulus), rapidly, accurately and reliably.

Geostationary Operational Environmental Satellite (GOES-N report). Volume 2: Technical appendix

NASA Technical Reports Server (NTRS)

1992-01-01

The contents include: operation with inclinations up to 3.5 deg to extend life; earth sensor improvements to reduce noise; sensor configurations studied; momentum management system design; reaction wheel induced dynamic interaction; controller design; spacecraft motion compensation; analog filtering; GFRP servo design - modern control approach; feedforward compensation as applied to GOES-1 sounder; discussion of allocation of navigation, inframe registration and image-to-image error budget overview; and spatial response and cloud smearing study.

A Fuzzy Logic Based Controller for the Automated Alignment of a Laser-beam-smoothing Spatial Filter

NASA Technical Reports Server (NTRS)

Krasowski, M. J.; Dickens, D. E.

1992-01-01

A fuzzy logic based controller for a laser-beam-smoothing spatial filter is described. It is demonstrated that a human operator's alignment actions can easily be described by a system of fuzzy rules of inference. The final configuration uses inexpensive, off-the-shelf hardware and allows for a compact, readily implemented embedded control system.

Social media as an information source for rapid flood inundation mapping

NASA Astrophysics Data System (ADS)

Fohringer, J.; Dransch, D.; Kreibich, H.; Schröter, K.

2015-12-01

During and shortly after a disaster, data about the hazard and its consequences are scarce and not readily available. Information provided by eyewitnesses via social media is a valuable information source, which should be explored in a~more effective way. This research proposes a methodology that leverages social media content to support rapid inundation mapping, including inundation extent and water depth in the case of floods. The novelty of this approach is the utilization of quantitative data that are derived from photos from eyewitnesses extracted from social media posts and their integration with established data. Due to the rapid availability of these posts compared to traditional data sources such as remote sensing data, areas affected by a flood, for example, can be determined quickly. The challenge is to filter the large number of posts to a manageable amount of potentially useful inundation-related information, as well as to interpret and integrate the posts into mapping procedures in a timely manner. To support rapid inundation mapping we propose a methodology and develop "PostDistiller", a tool to filter geolocated posts from social media services which include links to photos. This spatial distributed contextualized in situ information is further explored manually. In an application case study during the June 2013 flood in central Europe we evaluate the utilization of this approach to infer spatial flood patterns and inundation depths in the city of Dresden.

Social media as an information source for rapid flood inundation mapping

NASA Astrophysics Data System (ADS)

Fohringer, J.; Dransch, D.; Kreibich, H.; Schröter, K.

2015-07-01

During and shortly after a disaster data about the hazard and its consequences are scarce and not readily available. Information provided by eye-witnesses via social media are a valuable information source, which should be explored in a more effective way. This research proposes a methodology that leverages social media content to support rapid inundation mapping, including inundation extent and water depth in case of floods. The novelty of this approach is the utilization of quantitative data that are derived from photos from eye-witnesses extracted from social media posts and its integration with established data. Due to the rapid availability of these posts compared to traditional data sources such as remote sensing data, for example areas affected by a flood can be determined quickly. The challenge is to filter the large number of posts to a manageable amount of potentially useful inundation-related information as well as their timely interpretation and integration in mapping procedures. To support rapid inundation mapping we propose a methodology and develop a tool to filter geo-located posts from social media services which include links to photos. This spatial distributed contextualized in-situ information is further explored manually. In an application case study during the June 2013 flood in central Europe we evaluate the utilization of this approach to infer spatial flood patterns and inundation depths in the city of Dresden.

MR Image Reconstruction Using Block Matching and Adaptive Kernel Methods.

PubMed

Schmidt, Johannes F M; Santelli, Claudio; Kozerke, Sebastian

2016-01-01

An approach to Magnetic Resonance (MR) image reconstruction from undersampled data is proposed. Undersampling artifacts are removed using an iterative thresholding algorithm applied to nonlinearly transformed image block arrays. Each block array is transformed using kernel principal component analysis where the contribution of each image block to the transform depends in a nonlinear fashion on the distance to other image blocks. Elimination of undersampling artifacts is achieved by conventional principal component analysis in the nonlinear transform domain, projection onto the main components and back-mapping into the image domain. Iterative image reconstruction is performed by interleaving the proposed undersampling artifact removal step and gradient updates enforcing consistency with acquired k-space data. The algorithm is evaluated using retrospectively undersampled MR cardiac cine data and compared to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT reconstruction. Evaluation of image quality and root-mean-squared-error (RMSE) reveal improved image reconstruction for up to 8-fold undersampled data with the proposed approach relative to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT. In conclusion, block matching and kernel methods can be used for effective removal of undersampling artifacts in MR image reconstruction and outperform methods using standard compressed sensing and ℓ1-regularized parallel imaging methods.

Optoelectronic image scanning with high spatial resolution and reconstruction fidelity

NASA Astrophysics Data System (ADS)

Craubner, Siegfried I.

2002-02-01

In imaging systems the detector arrays deliver at the output time-discrete signals, where the spatial frequencies of the object scene are mapped into the electrical signal frequencies. Since the spatial frequency spectrum cannot be bandlimited by the front optics, the usual detector arrays perform a spatial undersampling and as a consequence aliasing occurs. A means to partially suppress the backfolded alias band is bandwidth limitation in the reconstruction low-pass, at the price of resolution loss. By utilizing a bilinear detector array in a pushbroom-type scanner, undersampling and aliasing can be overcome. For modeling the perception, the theory of discrete systems and multirate digital filter banks is applied, where aliasing cancellation and perfect reconstruction play an important role. The discrete transfer function of a bilinear array can be imbedded into the scheme of a second-order filter bank. The detector arrays already build the analysis bank and the overall filter bank is completed with the synthesis bank, for which stabilized inverse filters are proposed, to compensate for the low-pass characteristics and to approximate perfect reconstruction. The synthesis filter branch can be realized in a so-called `direct form,' or the `polyphase form,' where the latter is an expenditure-optimal solution, which gives advantages when implemented in a signal processor. This paper attempts to introduce well-established concepts of the theory of multirate filter banks into the analysis of scanning imagers, which is applicable in a much broader sense than for the problems addressed here. To the author's knowledge this is also a novelty.

Analysis of atmospheric pollutant metals by laser ablation inductively coupled plasma mass spectrometry with a radial line-scan dried-droplet approach

NASA Astrophysics Data System (ADS)

Tang, Xiaoxing; Qian, Yuan; Guo, Yanchuan; Wei, Nannan; Li, Yulan; Yao, Jian; Wang, Guanghua; Ma, Jifei; Liu, Wei

2017-12-01

A novel method has been improved for analyzing atmospheric pollutant metals (Be, Mn, Fe, Co, Ni, Cu, Zn, Se, Sr, Cd, and Pb) by laser ablation inductively coupled plasma mass spectrometry. In this method, solid standards are prepared by depositing droplets of aqueous standard solutions on the surface of a membrane filter, which is the same type as used for collecting atmospheric pollutant metals. Laser parameters were optimized, and ablation behaviors of the filter discs were studied. The mode of radial line scans across the filter disc was a representative ablation strategy and can avoid error from the inhomogeneous filter standards and marginal effect of the filter disc. Pt, as the internal standard, greatly improved the correlation coefficient of the calibration curve. The developed method provides low detection limits, from 0.01 ng m- 3 for Be and Co to 1.92 ng m- 3 for Fe. It was successfully applied for the determination of atmospheric pollutant metals collected in Lhasa, China. The analytical results showed good agreement with those obtained by conventional liquid analysis. In contrast to the conventional acid digestion procedure, the novel method not only greatly reduces sample preparation and shortens the analysis time but also provides a possible means for studying the spatial distribution of atmospheric filter samples.

Nonlinear Attitude Filtering Methods

NASA Technical Reports Server (NTRS)

Markley, F. Landis; Crassidis, John L.; Cheng, Yang

2005-01-01

This paper provides a survey of modern nonlinear filtering methods for attitude estimation. Early applications relied mostly on the extended Kalman filter for attitude estimation. Since these applications, several new approaches have been developed that have proven to be superior to the extended Kalman filter. Several of these approaches maintain the basic structure of the extended Kalman filter, but employ various modifications in order to provide better convergence or improve other performance characteristics. Examples of such approaches include: filter QUEST, extended QUEST, the super-iterated extended Kalman filter, the interlaced extended Kalman filter, and the second-order Kalman filter. Filters that propagate and update a discrete set of sigma points rather than using linearized equations for the mean and covariance are also reviewed. A two-step approach is discussed with a first-step state that linearizes the measurement model and an iterative second step to recover the desired attitude states. These approaches are all based on the Gaussian assumption that the probability density function is adequately specified by its mean and covariance. Other approaches that do not require this assumption are reviewed, including particle filters and a Bayesian filter based on a non-Gaussian, finite-parameter probability density function on SO(3). Finally, the predictive filter, nonlinear observers and adaptive approaches are shown. The strengths and weaknesses of the various approaches are discussed.

Propagation of flat-topped multi-Gaussian beams through a double-lens system with apertures.

PubMed

Gao, Yanqi; Zhu, Baoqiang; Liu, Daizhong; Lin, Zunqi

2009-07-20

A general model for different apertures and flat-topped laser beams based on the multi-Gaussian function is developed. The general analytical expression for the propagation of a flat-topped beam through a general double-lens system with apertures is derived using the above model. Then, the propagation characteristics of the flat-topped beam through a spatial filter are investigated by using a simplified analytical expression. Based on the Fluence beam contrast and the Fill factor, the influences of a pinhole size on the propagation of the flat-topped multi-Gaussian beam (FMGB) through the spatial filter are illustrated. An analytical expression for the propagation of the FMGB through the spatial filter with a misaligned pinhole is presented, and the influences of the pinhole offset are evaluated.

Hierarchical faunal filters: An approach to assessing effects of habitat and nonnative species on native fishes

USGS Publications Warehouse

Quist, M.C.; Rahel, F.J.; Hubert, W.A.

2005-01-01

Understanding factors related to the occurrence of species across multiple spatial and temporal scales is critical to the conservation and management of native fishes, especially for those species at the edge of their natural distribution. We used the concept of hierarchical faunal filters to provide a framework for investigating the influence of habitat characteristics and normative piscivores on the occurrence of 10 native fishes in streams of the North Platte River watershed in Wyoming. Three faunal filters were developed for each species: (i) large-scale biogeographic, (ii) local abiotic, and (iii) biotic. The large-scale biogeographic filter, composed of elevation and stream-size thresholds, was used to determine the boundaries within which each species might be expected to occur. Then, a local abiotic filter (i.e., habitat associations), developed using binary logistic-regression analysis, estimated the probability of occurrence of each species from features such as maximum depth, substrate composition, submergent aquatic vegetation, woody debris, and channel morphology (e.g., amount of pool habitat). Lastly, a biotic faunal filter was developed using binary logistic regression to estimate the probability of occurrence of each species relative to the abundance of nonnative piscivores in a reach. Conceptualising fish assemblages within a framework of hierarchical faunal filters is simple and logical, helps direct conservation and management activities, and provides important information on the ecology of fishes in the western Great Plains of North America. ?? Blackwell Munksgaard, 2004.

On simplified application of multidimensional Savitzky-Golay filters and differentiators

NASA Astrophysics Data System (ADS)

Shekhar, Chandra

2016-02-01

I propose a simplified approach for multidimensional Savitzky-Golay filtering, to enable its fast and easy implementation in scientific and engineering applications. The proposed method, which is derived from a generalized framework laid out by Thornley (D. J. Thornley, "Novel anisotropic multidimensional convolution filters for derivative estimation and reconstruction" in Proceedings of International Conference on Signal Processing and Communications, November 2007), first transforms any given multidimensional problem into a unique one, by transforming coordinates of the sampled data nodes to unity-spaced, uniform data nodes, and then performs filtering and calculates partial derivatives on the unity-spaced nodes. It is followed by transporting the calculated derivatives back onto the original data nodes by using the chain rule of differentiation. The burden to performing the most cumbersome task, which is to carry out the filtering and to obtain derivatives on the unity-spaced nodes, is almost eliminated by providing convolution coefficients for a number of convolution kernel sizes and polynomial orders, up to four spatial dimensions. With the availability of the convolution coefficients, the task of filtering at a data node reduces merely to multiplication of two known matrices. Simplified strategies to adequately address near-boundary data nodes and to calculate partial derivatives there are also proposed. Finally, the proposed methodologies are applied to a three-dimensional experimentally obtained data set, which shows that multidimensional Savitzky-Golay filters and differentiators perform well in both the internal and the near-boundary regions of the domain.

A Tensor-Based Subspace Approach for Bistatic MIMO Radar in Spatial Colored Noise

PubMed Central

Wang, Xianpeng; Wang, Wei; Li, Xin; Wang, Junxiang

2014-01-01

In this paper, a new tensor-based subspace approach is proposed to estimate the direction of departure (DOD) and the direction of arrival (DOA) for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise. Firstly, the received signals can be packed into a third-order measurement tensor by exploiting the inherent structure of the matched filter. Then, the measurement tensor can be divided into two sub-tensors, and a cross-covariance tensor is formulated to eliminate the spatial colored noise. Finally, the signal subspace is constructed by utilizing the higher-order singular value decomposition (HOSVD) of the cross-covariance tensor, and the DOD and DOA can be obtained through the estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm, which are paired automatically. Since the multidimensional inherent structure and the cross-covariance tensor technique are used, the proposed method provides better angle estimation performance than Chen's method, the ESPRIT algorithm and the multi-SVD method. Simulation results confirm the effectiveness and the advantage of the proposed method. PMID:24573313

A tensor-based subspace approach for bistatic MIMO radar in spatial colored noise.

PubMed

Wang, Xianpeng; Wang, Wei; Li, Xin; Wang, Junxiang

2014-02-25

In this paper, a new tensor-based subspace approach is proposed to estimate the direction of departure (DOD) and the direction of arrival (DOA) for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise. Firstly, the received signals can be packed into a third-order measurement tensor by exploiting the inherent structure of the matched filter. Then, the measurement tensor can be divided into two sub-tensors, and a cross-covariance tensor is formulated to eliminate the spatial colored noise. Finally, the signal subspace is constructed by utilizing the higher-order singular value decomposition (HOSVD) of the cross-covariance tensor, and the DOD and DOA can be obtained through the estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm, which are paired automatically. Since the multidimensional inherent structure and the cross-covariance tensor technique are used, the proposed method provides better angle estimation performance than Chen's method, the ESPRIT algorithm and the multi-SVD method. Simulation results confirm the effectiveness and the advantage of the proposed method.

A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti

PubMed Central

2013-01-01

Background Fine-scale and longitudinal geospatial analysis of health risks in challenging urban areas is often limited by the lack of other spatial layers even if case data are available. Underlying population counts, residential context, and associated causative factors such as standing water or trash locations are often missing unless collected through logistically difficult, and often expensive, surveys. The lack of spatial context also hinders the interpretation of results and designing intervention strategies structured around analytical insights. This paper offers a ubiquitous spatial data collection approach using a spatial video that can be used to improve analysis and involve participatory collaborations. A case study will be used to illustrate this approach with three health risks mapped at the street scale for a coastal community in Haiti. Methods Spatial video was used to collect street and building scale information, including standing water, trash accumulation, presence of dogs, cohort specific population characteristics, and other cultural phenomena. These data were digitized into Google Earth and then coded and analyzed in a GIS using kernel density and spatial filtering approaches. The concentrations of these risks around area schools which are sometimes sources of diarrheal disease infection because of the high concentration of children and variable sanitary practices will show the utility of the method. In addition schools offer potential locations for cholera education interventions. Results Previously unavailable fine scale health risk data vary in concentration across the town, with some schools being proximate to greater concentrations of the mapped risks. The spatial video is also used to validate coded data and location specific risks within these “hotspots”. Conclusions Spatial video is a tool that can be used in any environment to improve local area health analysis and intervention. The process is rapid and can be repeated in study sites through time to track spatio-temporal dynamics of the communities. Its simplicity should also be used to encourage local participatory collaborations. PMID:23587358

A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti.

PubMed

Curtis, Andrew; Blackburn, Jason K; Widmer, Jocelyn M; Morris, J Glenn

2013-04-15

Fine-scale and longitudinal geospatial analysis of health risks in challenging urban areas is often limited by the lack of other spatial layers even if case data are available. Underlying population counts, residential context, and associated causative factors such as standing water or trash locations are often missing unless collected through logistically difficult, and often expensive, surveys. The lack of spatial context also hinders the interpretation of results and designing intervention strategies structured around analytical insights. This paper offers a ubiquitous spatial data collection approach using a spatial video that can be used to improve analysis and involve participatory collaborations. A case study will be used to illustrate this approach with three health risks mapped at the street scale for a coastal community in Haiti. Spatial video was used to collect street and building scale information, including standing water, trash accumulation, presence of dogs, cohort specific population characteristics, and other cultural phenomena. These data were digitized into Google Earth and then coded and analyzed in a GIS using kernel density and spatial filtering approaches. The concentrations of these risks around area schools which are sometimes sources of diarrheal disease infection because of the high concentration of children and variable sanitary practices will show the utility of the method. In addition schools offer potential locations for cholera education interventions. Previously unavailable fine scale health risk data vary in concentration across the town, with some schools being proximate to greater concentrations of the mapped risks. The spatial video is also used to validate coded data and location specific risks within these "hotspots". Spatial video is a tool that can be used in any environment to improve local area health analysis and intervention. The process is rapid and can be repeated in study sites through time to track spatio-temporal dynamics of the communities. Its simplicity should also be used to encourage local participatory collaborations.

Optimal speckle noise reduction filter for range gated laser illuminated imaging

NASA Astrophysics Data System (ADS)

Dayton, David; Gonglewski, John; Lasche, James; Hassall, Arthur

2016-09-01

Laser illuminated imaging has a number of applications in the areas of night time air-to-ground target surveillance, ID, and pointing and tracking. Using a laser illuminator, the illumination intensity and thus the signal to noise ratio can be controlled. With the advent of high performance range gated cameras in the short-wave infra-red band, higher spatial resolution can be achieved over passive thermal night imaging cameras in the mid-wave infra-red due to the shorter wave-length. If a coherent illuminator is used the resulting imagery often suffers from speckle noise due to the scattering off of a rough target surface, which gives it a grainy "salt and pepper" appearance. The probability density function for the intensity of focal plane speckle is well understood to follow a negative exponential distribution. This can be exploited to develop a Bayesian speckle noise filter. The filter has the advantage over simple frame averaging approaches in that it preserves target features and motion while reducing speckle noise without smearing or blurring the images. The resulting filtered images have the appearance of passive imagery and so are more amenable to sensor fusion with simultaneous mid-wave infra-red thermal images for enhanced target ID. The noise filter improvement is demonstrated using examples from real world laser imaging tests on tactical targets.

Filters for Improvement of Multiscale Data from Atomistic Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gardner, David J.; Reynolds, Daniel R.

Multiscale computational models strive to produce accurate and efficient numerical simulations of systems involving interactions across multiple spatial and temporal scales that typically differ by several orders of magnitude. Some such models utilize a hybrid continuum-atomistic approach combining continuum approximations with first-principles-based atomistic models to capture multiscale behavior. By following the heterogeneous multiscale method framework for developing multiscale computational models, unknown continuum scale data can be computed from an atomistic model. Concurrently coupling the two models requires performing numerous atomistic simulations which can dominate the computational cost of the method. Furthermore, when the resulting continuum data is noisy due tomore » sampling error, stochasticity in the model, or randomness in the initial conditions, filtering can result in significant accuracy gains in the computed multiscale data without increasing the size or duration of the atomistic simulations. In this work, we demonstrate the effectiveness of spectral filtering for increasing the accuracy of noisy multiscale data obtained from atomistic simulations. Moreover, we present a robust and automatic method for closely approximating the optimum level of filtering in the case of additive white noise. By improving the accuracy of this filtered simulation data, it leads to a dramatic computational savings by allowing for shorter and smaller atomistic simulations to achieve the same desired multiscale simulation precision.« less

Filters for Improvement of Multiscale Data from Atomistic Simulations

DOE PAGES

Gardner, David J.; Reynolds, Daniel R.

2017-01-05

Multiscale computational models strive to produce accurate and efficient numerical simulations of systems involving interactions across multiple spatial and temporal scales that typically differ by several orders of magnitude. Some such models utilize a hybrid continuum-atomistic approach combining continuum approximations with first-principles-based atomistic models to capture multiscale behavior. By following the heterogeneous multiscale method framework for developing multiscale computational models, unknown continuum scale data can be computed from an atomistic model. Concurrently coupling the two models requires performing numerous atomistic simulations which can dominate the computational cost of the method. Furthermore, when the resulting continuum data is noisy due tomore » sampling error, stochasticity in the model, or randomness in the initial conditions, filtering can result in significant accuracy gains in the computed multiscale data without increasing the size or duration of the atomistic simulations. In this work, we demonstrate the effectiveness of spectral filtering for increasing the accuracy of noisy multiscale data obtained from atomistic simulations. Moreover, we present a robust and automatic method for closely approximating the optimum level of filtering in the case of additive white noise. By improving the accuracy of this filtered simulation data, it leads to a dramatic computational savings by allowing for shorter and smaller atomistic simulations to achieve the same desired multiscale simulation precision.« less

Variation in coastal Antarctic microbial community composition at sub-mesoscale: spatial distance or environmental filtering?

PubMed

Moreno-Pino, Mario; De la Iglesia, Rodrigo; Valdivia, Nelson; Henríquez-Castilo, Carlos; Galán, Alexander; Díez, Beatriz; Trefault, Nicole

2016-07-01

Spatial environmental heterogeneity influences diversity of organisms at different scales. Environmental filtering suggests that local environmental conditions provide habitat-specific scenarios for niche requirements, ultimately determining the composition of local communities. In this work, we analyze the spatial variation of microbial communities across environmental gradients of sea surface temperature, salinity and photosynthetically active radiation and spatial distance in Fildes Bay, King George Island, Antarctica. We hypothesize that environmental filters are the main control of the spatial variation of these communities. Thus, strong relationships between community composition and environmental variation and weak relationships between community composition and spatial distance are expected. Combining physical characterization of the water column, cell counts by flow cytometry, small ribosomal subunit genes fingerprinting and next generation sequencing, we contrast the abundance and composition of photosynthetic eukaryotes and heterotrophic bacterial local communities at a submesoscale. Our results indicate that the strength of the environmental controls differed markedly between eukaryotes and bacterial communities. Whereas eukaryotic photosynthetic assemblages responded weakly to environmental variability, bacteria respond promptly to fine-scale environmental changes in this polar marine system. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Detection and extraction of orientation-and-scale-dependent information from two-dimensional GPR data with tuneable directional wavelet filters

NASA Astrophysics Data System (ADS)

Tzanis, Andreas

2013-02-01

The Ground Probing Radar (GPR) is a valuable tool for near surface geological, geotechnical, engineering, environmental, archaeological and other work. GPR images of the subsurface frequently contain geometric information (constant or variable-dip reflections) from various structures such as bedding, cracks, fractures, etc. Such features are frequently the target of the survey; however, they are usually not good reflectors and they are highly localized in time and in space. Their scale is therefore a factor significantly affecting their detectability. At the same time, the GPR method is very sensitive to broadband noise from buried small objects, electromagnetic anthropogenic activity and systemic factors, which frequently blurs the reflections from such targets. This paper introduces a method to de-noise GPR data and extract geometric information from scale-and-dip dependent structural features, based on one-dimensional B-Spline Wavelets, two-dimensional directional B-Spline Wavelet (BSW) Filters and two-dimensional Gabor Filters. A directional BSW Filter is built by sidewise arranging s identical one-dimensional wavelets of length L, tapering the s-parallel direction (span) with a suitable window function and rotating the resulting matrix to the desired orientation. The length L of the wavelet defines the temporal and spatial scale to be isolated and the span determines the length over which to smooth (spatial resolution). The Gabor Filter is generated by multiplying an elliptical Gaussian by a complex plane wave; at any orientation the temporal or spatial scale(s) to be isolated are determined by the wavelength. λ of the plane wave and the spatial resolution by the spatial aspect ratio γ, which specifies the ellipticity of the support of the Gabor function. At any orientation, both types of filter may be tuned at any frequency or spatial wavenumber by varying the length or the wavelength respectively. The filters can be applied directly to two-dimensional radargrams, in which case they abstract information about given scales at given orientations. Alternatively, they can be rotated to different orientations under adaptive control, so that they remain tuned at a given frequency or wavenumber and the resulting images can be stacked in the LS sense, so as to obtain a complete representation of the input data at a given temporal or spatial scale. In addition to isolating geometrical information for further scrutiny, the proposed filtering methods can be used to enhance the S/N ratio in a manner particularly suitable for GPR data, because the frequency response of the filters mimics the frequency characteristics of the source wavelet. Finally, signal attenuation and temporal localization are closely associated: low attenuation interfaces tend to produce reflections rich in high frequencies and fine-scale localization as a function of time. Conversely, high attenuation interfaces will produce reflections rich in low frequencies and broad localization. Accordingly, the temporal localization characteristics of the filters may be exploited to investigate the characteristics of signal propagation (hence material properties). The method is shown to be very effective in extracting fine to coarse scale information from noisy data and is demonstrated with applications to noisy GPR data from archaeometric and geotechnical surveys.

Improved reading performance using individualized compensation filters for observers with losses in central vision

NASA Technical Reports Server (NTRS)

Lawton, Teri B.

1989-01-01

A method to improve the reading performance of subjects with losses in central vision is proposed in which the amplitudes of the intermediate spatial frequencies are boosted relative to the lower spatial frequencies. In the method, words are filtered using an image enhancement function which is based on a subject's losses in visual function relative to a normal subject. It was found that 30-70 percent less magnification was necessary, and that reading rates were improved 2-3 times, using the method. The individualized compensation filters improved the clarity and visibility of words. The shape of the enhancement function was shown to be important in determining the optimum compensation filter for improving reading performance.

Filtering of non-linear instabilities

NASA Technical Reports Server (NTRS)

Khosla, P. K.; Rubin, S. G.

1978-01-01

For Courant numbers larger than one and cell Reynolds numbers larger than two, oscillations and in some cases instabilities are typically found with implicit numerical solutions of the fluid dynamics equations. This behavior has sometimes been associated with the loss of diagonal dominance of the coefficient matrix. It is shown that these problems can be related to the choice of the spatial differences, with the resulting instability related to aliasing or nonlinear interaction. Appropriate filtering can reduce the intensity of these oscillations and possibly eliminate the instability. These filtering procedures are equivalent to a weighted average of conservation and nonconservation differencing. The entire spectrum of filtered equations retains a three point character as well as second order spatial accuracy. Burgers equation was considered as a model.

Comparison between GSTAR and GSTAR-Kalman Filter models on inflation rate forecasting in East Java

NASA Astrophysics Data System (ADS)

Rahma Prillantika, Jessica; Apriliani, Erna; Wahyuningsih, Nuri

2018-03-01

Up to now, we often find data which have correlation between time and location. This data also known as spatial data. Inflation rate is one type of spatial data because it is not only related to the events of the previous time, but also has relevance to the other location or elsewhere. In this research, we do comparison between GSTAR model and GSTAR-Kalman Filter to get prediction which have small error rate. Kalman Filter is one estimator that estimates state changes due to noise from white noise. The final result shows that Kalman Filter is able to improve the GSTAR forecast result. This is shown through simulation results in the form of graphs and clarified with smaller RMSE values.

2D Fast Vessel Visualization Using a Vessel Wall Mask Guiding Fine Vessel Detection

PubMed Central

Raptis, Sotirios; Koutsouris, Dimitris

2010-01-01

The paper addresses the fine retinal-vessel's detection issue that is faced in diagnostic applications and aims at assisting in better recognizing fine vessel anomalies in 2D. Our innovation relies in separating key visual features vessels exhibit in order to make the diagnosis of eventual retinopathologies easier to detect. This allows focusing on vessel segments which present fine changes detectable at different sampling scales. We advocate that these changes can be addressed as subsequent stages of the same vessel detection procedure. We first carry out an initial estimate of the basic vessel-wall's network, define the main wall-body, and then try to approach the ridges and branches of the vasculature's using fine detection. Fine vessel screening looks into local structural inconsistencies in vessels properties, into noise, or into not expected intensity variations observed inside pre-known vessel-body areas. The vessels are first modelled sufficiently but not precisely by their walls with a tubular model-structure that is the result of an initial segmentation. This provides a chart of likely Vessel Wall Pixels (VWPs) yielding a form of a likelihood vessel map mainly based on gradient filter's intensity and spatial arrangement parameters (e.g., linear consistency). Specific vessel parameters (centerline, width, location, fall-away rate, main orientation) are post-computed by convolving the image with a set of pre-tuned spatial filters called Matched Filters (MFs). These are easily computed as Gaussian-like 2D forms that use a limited range sub-optimal parameters adjusted to the dominant vessel characteristics obtained by Spatial Grey Level Difference statistics limiting the range of search into vessel widths of 16, 32, and 64 pixels. Sparse pixels are effectively eliminated by applying a limited range Hough Transform (HT) or region growing. Major benefits are limiting the range of parameters, reducing the search-space for post-convolution to only masked regions, representing almost 2% of the 2D volume, good speed versus accuracy/time trade-off. Results show the potentials of our approach in terms of time for detection ROC analysis and accuracy of vessel pixel (VP) detection. PMID:20706682

Control of the amplifications of large-band amplitude-modulated pulses in an Nd-glass amplifier chain

NASA Astrophysics Data System (ADS)

Videau, Laurent; Bar, Emmanuel; Rouyer, Claude; Gouedard, Claude; Garnier, Josselin C.; Migus, Arnold

1999-07-01

We study nonlinear effects in amplification of partially coherent pulses in a high power laser chain. We compare statistical models with experimental results for temporal and spatial effects. First we show the interplay between self-phase modulation which broadens spectrum bandwidth and gain narrowing which reduces output spectrum. Theoretical results are presented for spectral broadening and energy limitation in case of time-incoherent pulses. In a second part, we introduce spatial incoherence with a multimode optical fiber which provides a smoothed beam. We show with experimental result that spatial filter pinholes are responsible for additive energy losses in the amplification. We develop a statistical model which takes into account the deformation of the focused beam as a function of B integral. We estimate the energy transmission of the spatial filter pinholes and compare this model with experimental data. We find a good agreement between theory and experiments. As a conclusion, we present an analogy between temporal and spatial effects with spectral broadening and spectral filter. Finally, we propose some solutions to control energy limitations in smoothed pulses amplification.

Fourier Spectral Filter Array for Optimal Multispectral Imaging.

PubMed

Jia, Jie; Barnard, Kenneth J; Hirakawa, Keigo

2016-04-01

Limitations to existing multispectral imaging modalities include speed, cost, range, spatial resolution, and application-specific system designs that lack versatility of the hyperspectral imaging modalities. In this paper, we propose a novel general-purpose single-shot passive multispectral imaging modality. Central to this design is a new type of spectral filter array (SFA) based not on the notion of spatially multiplexing narrowband filters, but instead aimed at enabling single-shot Fourier transform spectroscopy. We refer to this new SFA pattern as Fourier SFA, and we prove that this design solves the problem of optimally sampling the hyperspectral image data.

Imaging through scattering media by Fourier filtering and single-pixel detection

NASA Astrophysics Data System (ADS)

Jauregui-Sánchez, Y.; Clemente, P.; Lancis, J.; Tajahuerce, E.

2018-02-01

We present a novel imaging system that combines the principles of Fourier spatial filtering and single-pixel imaging in order to recover images of an object hidden behind a turbid medium by transillumination. We compare the performance of our single-pixel imaging setup with that of a conventional system. We conclude that the introduction of Fourier gating improves the contrast of images in both cases. Furthermore, we show that the combination of single-pixel imaging and Fourier spatial filtering techniques is particularly well adapted to provide images of objects transmitted through scattering media.

Real-time optical signal processors employing optical feedback: amplitude and phase control.

PubMed

Gallagher, N C

1976-04-01

The development of real-time coherent optical signal processors has increased the appeal of optical computing techniques in signal processing applications. A major limitation of these real-time systems is the. fact that the optical processing material is generally of a phase-only type. The result is that the spatial filters synthesized with these systems must be either phase-only filters or amplitude-only filters. The main concern of this paper is the application of optical feedback techniques to obtain simultaneous and independent amplitude and phase control of the light passing through the system. It is shown that optical feedback techniques may be employed with phase-only spatial filters to obtain this amplitude and phase control. The feedback system with phase-only filters is compared with other feedback systems that employ combinations of phase-only and amplitude-only filters; it is found that the phase-only system is substantially more flexible than the other two systems investigated.

Synthetic ultraviolet light filtering chemical contamination of coastal waters of Virgin Islands National Park, St. John, U.S. Virgin Islands

USGS Publications Warehouse

Bargar, Timothy A.; Alvarez, David; Garrison, Virginia H.

2015-01-01

Contamination of surface waters by synthetic ultraviolet light (UV) filtering chemicals is a concern for the Virgin Islands National Park (VINP). Discrete water samples were collected from VINP bays to determine UV filter chemical presence in the coastal waters. Spatial distribution and the potential for partitioning between subsurface waters and the sea surface microlayer (SML) were also examined. The UV filter chemicals 4-methylbenzylidene camphor, benzophenone-3, octinoxate, homosalate, and octocrylene were detected at concentrations up to 6073 ng/L (benzophenone-3). Concentrations for benzophenone-3 and homosalate declined exponentially (r2 = 0.86 to 0.98) with distance from the beach. Limited data indicate that some UV filter chemicals may partition to the SML relative to the subsurface waters. Contamination of VINP coastal waters by UV filter chemicals may be a significant issue, but an improved understanding of the temporal and spatial variability of their concentrations would be necessary to better understand the risk they present.

Optimizing binary phase and amplitude filters for PCE, SNR, and discrimination

NASA Technical Reports Server (NTRS)

Downie, John D.

1992-01-01

Binary phase-only filters (BPOFs) have generated much study because of their implementation on currently available spatial light modulator devices. On polarization-rotating devices such as the magneto-optic spatial light modulator (SLM), it is also possible to encode binary amplitude information into two SLM transmission states, in addition to the binary phase information. This is done by varying the rotation angle of the polarization analyzer following the SLM in the optical train. Through this parameter, a continuum of filters may be designed that span the space of binary phase and amplitude filters (BPAFs) between BPOFs and binary amplitude filters. In this study, we investigate the design of optimal BPAFs for the key correlation characteristics of peak sharpness (through the peak-to-correlation energy (PCE) metric), signal-to-noise ratio (SNR), and discrimination between in-class and out-of-class images. We present simulation results illustrating improvements obtained over conventional BPOFs, and trade-offs between the different performance criteria in terms of the filter design parameter.

Fine-scale structure in the far-infrared Milky-Way

NASA Technical Reports Server (NTRS)

Waller, William H.; Wall, William F.; Reach, William T.; Varosi, Frank; Ebert, Rick; Laughlin, Gaylin; Boulanger, Francois

1995-01-01

This final report summarizes the work performed and which falls into five broad categories: (1) generation of a new data product (mosaics of the far-infrared emission in the Milky Way); (2) acquisition of associated data products at other wavelengths; (3) spatial filtering of the far-infrared mosaics and resulting images of the FIR fine-scale structure; (4) evaluation of the spatially filtered data; (5) characterization of the FIR fine-scale structure in terms of its spatial statistics; and (6) identification of interstellar counterparts to the FIR fine-scale structure.

Evaluation of Pan-Sharpening Methods for Automatic Shadow Detection in High Resolution Images of Urban Areas

NASA Astrophysics Data System (ADS)

de Azevedo, Samara C.; Singh, Ramesh P.; da Silva, Erivaldo A.

2017-04-01

Finer spatial resolution of areas with tall objects within urban environment causes intense shadows that lead to wrong information in urban mapping. Due to the shadows, automatic detection of objects (such as buildings, trees, structures, towers) and to estimate the surface coverage from high spatial resolution is difficult. Thus, automatic shadow detection is the first necessary preprocessing step to improve the outcome of many remote sensing applications, particularly for high spatial resolution images. Efforts have been made to explore spatial and spectral information to evaluate such shadows. In this paper, we have used morphological attribute filtering to extract contextual relations in an efficient multilevel approach for high resolution images. The attribute selected for the filtering was the area estimated from shadow spectral feature using the Normalized Saturation-Value Difference Index (NSVDI) derived from pan-sharpening images. In order to assess the quality of fusion products and the influence on shadow detection algorithm, we evaluated three pan-sharpening methods - Intensity-Hue-Saturation (IHS), Principal Components (PC) and Gran-Schmidt (GS) through the image quality measures: Correlation Coefficient (CC), Root Mean Square Error (RMSE), Relative Dimensionless Global Error in Synthesis (ERGAS) and Universal Image Quality Index (UIQI). Experimental results over Worldview II scene from São Paulo city (Brazil) show that GS method provides good correlation with original multispectral bands with no radiometric and contrast distortion. The automatic method using GS method for NSDVI generation clearly provide a clear distinction of shadows and non-shadows pixels with an overall accuracy more than 90%. The experimental results confirm the effectiveness of the proposed approach which could be used for further shadow removal and reliable for object recognition, land-cover mapping, 3D reconstruction, etc. especially in developing countries where land use and land cover are rapidly changing with tall objects within urban areas.

An improved discriminative filter bank selection approach for motor imagery EEG signal classification using mutual information.

PubMed

Kumar, Shiu; Sharma, Alok; Tsunoda, Tatsuhiko

2017-12-28

Common spatial pattern (CSP) has been an effective technique for feature extraction in electroencephalography (EEG) based brain computer interfaces (BCIs). However, motor imagery EEG signal feature extraction using CSP generally depends on the selection of the frequency bands to a great extent. In this study, we propose a mutual information based frequency band selection approach. The idea of the proposed method is to utilize the information from all the available channels for effectively selecting the most discriminative filter banks. CSP features are extracted from multiple overlapping sub-bands. An additional sub-band has been introduced that cover the wide frequency band (7-30 Hz) and two different types of features are extracted using CSP and common spatio-spectral pattern techniques, respectively. Mutual information is then computed from the extracted features of each of these bands and the top filter banks are selected for further processing. Linear discriminant analysis is applied to the features extracted from each of the filter banks. The scores are fused together, and classification is done using support vector machine. The proposed method is evaluated using BCI Competition III dataset IVa, BCI Competition IV dataset I and BCI Competition IV dataset IIb, and it outperformed all other competing methods achieving the lowest misclassification rate and the highest kappa coefficient on all three datasets. Introducing a wide sub-band and using mutual information for selecting the most discriminative sub-bands, the proposed method shows improvement in motor imagery EEG signal classification.

Comparison of holographic lens and filter systems for lateral spectrum splitting

NASA Astrophysics Data System (ADS)

Vorndran, Shelby; Chrysler, Benjamin; Kostuk, Raymond K.

2016-09-01

Spectrum splitting is an approach to increasing the conversion efficiency of a photovoltaic (PV) system. Several methods can be used to perform this function which requires efficient spatial separation of different spectral bands of the incident solar radiation. In this paper several of holographic methods for implementing spectrum splitting are reviewed along with the benefits and disadvantages associated with each approach. The review indicates that a volume holographic lens has many advantages for spectrum splitting in terms of both power conversion efficiency and energy yield. A specific design for a volume holographic spectrum splitting lens is discussed for use with high bandgap InGaP and low bandgap silicon PV cells. The holographic lenses are modeled using rigorous coupled wave analysis, and the optical efficiency is evaluated using non-sequential raytracing. A proof-of-concept off-axis holographic lens is also recorded in dichromated gelatin film and the spectral diffraction efficiency of the hologram is measured with multiple laser sources across the diffracted spectral band. The experimental volume holographic lens (VHL) characteristics are compared to an ideal spectrum splitting filter in terms of power conversion efficiency and energy yield in environments with high direct normal incidence (DNI) illumination and high levels of diffuse illumination. The results show that the experimental VHL can achieve 62.5% of the ideal filter power conversion efficiency, 64.8% of the ideal filter DNI environment energy yield, and 57.7% of the ideal diffuse environment energy yield performance.

Filtering of non-linear instabilities. [from finite difference solution of fluid dynamics equations

NASA Technical Reports Server (NTRS)

Khosla, P. K.; Rubin, S. G.

1979-01-01

For Courant numbers larger than one and cell Reynolds numbers larger than two, oscillations and in some cases instabilities are typically found with implicit numerical solutions of the fluid dynamics equations. This behavior has sometimes been associated with the loss of diagonal dominance of the coefficient matrix. It is shown here that these problems can in fact be related to the choice of the spatial differences, with the resulting instability related to aliasing or nonlinear interaction. Appropriate 'filtering' can reduce the intensity of these oscillations and in some cases possibly eliminate the instability. These filtering procedures are equivalent to a weighted average of conservation and non-conservation differencing. The entire spectrum of filtered equations retains a three-point character as well as second-order spatial accuracy. Burgers equation has been considered as a model. Several filters are examined in detail, and smooth solutions have been obtained for extremely large cell Reynolds numbers.

Assessment of the pseudo-tracking approach for the calculation of material acceleration and pressure fields from time-resolved PIV: part II. Spatio-temporal filtering

NASA Astrophysics Data System (ADS)

van Gent, P. L.; Schrijer, F. F. J.; van Oudheusden, B. W.

2018-04-01

The present study characterises the spatio-temporal filtering associated with pseudo-tracking. A combined theoretical and numerical assessment is performed that uses the relatively simple flow case of a two-dimensional Taylor vortex as analytical test case. An additional experimental assessment considers the more complex flow of a low-speed axisymmetric base flow, for which time-resolved tomographic PIV measurements and microphone measurements were obtained. The results of these assessments show how filtering along Lagrangian tracks leads to amplitude modulation of flow structures. A cut-off track length and spatial resolution are specified to support future applications of the pseudo-tracking approach. The experimental results show a fair agreement between PIV and microphone pressure data in terms of fluctuation levels and pressure frequency spectra. The coherence and correlation between microphone and PIV pressure measurements were found to be substantial and almost independent of the track length, indicating that the low-frequency behaviour of the flow could be reproduced regardless of the track length. It is suggested that a spectral analysis can be used inform the selection of a suitable track length and to estimate the local error margin of reconstructed pressure values.

Multispectral Image Enhancement Through Adaptive Wavelet Fusion

DTIC Science & Technology

2016-09-14

13. SUPPLEMENTARY NOTES 14. ABSTRACT This research developed a multiresolution image fusion scheme based on guided filtering . Guided filtering can...effectively reduce noise while preserving detail boundaries. When applied in an iterative mode, guided filtering selectively eliminates small scale...details while restoring larger scale edges. The proposed multi-scale image fusion scheme achieves spatial consistency by using guided filtering both at

Projective filtering of the fundamental eigenmode from spatially multimode radiation

NASA Astrophysics Data System (ADS)

Pérez, A. M.; Sharapova, P. R.; Straupe, S. S.; Miatto, F. M.; Tikhonova, O. V.; Leuchs, G.; Chekhova, M. V.

2015-11-01

Lossless filtering of a single coherent (Schmidt) mode from spatially multimode radiation is a problem crucial for optics in general and for quantum optics in particular. It becomes especially important in the case of nonclassical light that is fragile to optical losses. An example is bright squeezed vacuum generated via high-gain parametric down conversion or four-wave mixing. Its highly multiphoton and multimode structure offers a huge increase in the information capacity provided that each mode can be addressed separately. However, the nonclassical signature of bright squeezed vacuum, photon-number correlations, are highly susceptible to losses. Here we demonstrate lossless filtering of a single spatial Schmidt mode by projecting the spatial spectrum of bright squeezed vacuum on the eigenmode of a single-mode fiber. Moreover, we show that the first Schmidt mode can be captured by simply maximizing the fiber-coupled intensity. Importantly, the projection operation does not affect the targeted mode and leaves it usable for further applications.

Spatial band-pass filtering aids decoding musical genres from auditory cortex 7T fMRI.

PubMed

Sengupta, Ayan; Pollmann, Stefan; Hanke, Michael

2018-01-01

Spatial filtering strategies, combined with multivariate decoding analysis of BOLD images, have been used to investigate the nature of the neural signal underlying the discriminability of brain activity patterns evoked by sensory stimulation -- primarily in the visual cortex. Reported evidence indicates that such signals are spatially broadband in nature, and are not primarily comprised of fine-grained activation patterns. However, it is unclear whether this is a general property of the BOLD signal, or whether it is specific to the details of employed analyses and stimuli. Here we performed an analysis of publicly available, high-resolution 7T fMRI on the response BOLD response to musical genres in primary auditory cortex that matches a previously conducted study on decoding visual orientation from V1.  The results show that the pattern of decoding accuracies with respect to different types and levels of spatial filtering is comparable to that obtained from V1, despite considerable differences in the respective cortical circuitry.

Accounting for the measurement error of spectroscopically inferred soil carbon data for improved precision of spatial predictions.

PubMed

Somarathna, P D S N; Minasny, Budiman; Malone, Brendan P; Stockmann, Uta; McBratney, Alex B

2018-08-01

Spatial modelling of environmental data commonly only considers spatial variability as the single source of uncertainty. In reality however, the measurement errors should also be accounted for. In recent years, infrared spectroscopy has been shown to offer low cost, yet invaluable information needed for digital soil mapping at meaningful spatial scales for land management. However, spectrally inferred soil carbon data are known to be less accurate compared to laboratory analysed measurements. This study establishes a methodology to filter out the measurement error variability by incorporating the measurement error variance in the spatial covariance structure of the model. The study was carried out in the Lower Hunter Valley, New South Wales, Australia where a combination of laboratory measured, and vis-NIR and MIR inferred topsoil and subsoil soil carbon data are available. We investigated the applicability of residual maximum likelihood (REML) and Markov Chain Monte Carlo (MCMC) simulation methods to generate parameters of the Matérn covariance function directly from the data in the presence of measurement error. The results revealed that the measurement error can be effectively filtered-out through the proposed technique. When the measurement error was filtered from the data, the prediction variance almost halved, which ultimately yielded a greater certainty in spatial predictions of soil carbon. Further, the MCMC technique was successfully used to define the posterior distribution of measurement error. This is an important outcome, as the MCMC technique can be used to estimate the measurement error if it is not explicitly quantified. Although this study dealt with soil carbon data, this method is amenable for filtering the measurement error of any kind of continuous spatial environmental data. Copyright © 2018 Elsevier B.V. All rights reserved.

Bilateral filtering using the full noise covariance matrix applied to x-ray phase-contrast computed tomography.

PubMed

Allner, S; Koehler, T; Fehringer, A; Birnbacher, L; Willner, M; Pfeiffer, F; Noël, P B

2016-05-21

The purpose of this work is to develop an image-based de-noising algorithm that exploits complementary information and noise statistics from multi-modal images, as they emerge in x-ray tomography techniques, for instance grating-based phase-contrast CT and spectral CT. Among the noise reduction methods, image-based de-noising is one popular approach and the so-called bilateral filter is a well known algorithm for edge-preserving filtering. We developed a generalization of the bilateral filter for the case where the imaging system provides two or more perfectly aligned images. The proposed generalization is statistically motivated and takes the full second order noise statistics of these images into account. In particular, it includes a noise correlation between the images and spatial noise correlation within the same image. The novel generalized three-dimensional bilateral filter is applied to the attenuation and phase images created with filtered backprojection reconstructions from grating-based phase-contrast tomography. In comparison to established bilateral filters, we obtain improved noise reduction and at the same time a better preservation of edges in the images on the examples of a simulated soft-tissue phantom, a human cerebellum and a human artery sample. The applied full noise covariance is determined via cross-correlation of the image noise. The filter results yield an improved feature recovery based on enhanced noise suppression and edge preservation as shown here on the example of attenuation and phase images captured with grating-based phase-contrast computed tomography. This is supported by quantitative image analysis. Without being bound to phase-contrast imaging, this generalized filter is applicable to any kind of noise-afflicted image data with or without noise correlation. Therefore, it can be utilized in various imaging applications and fields.

DOA-informed source extraction in the presence of competing talkers and background noise

NASA Astrophysics Data System (ADS)

Taseska, Maja; Habets, Emanuël A. P.

2017-12-01

A desired speech signal in hands-free communication systems is often degraded by noise and interfering speech. Even though the number and locations of the interferers are often unknown in practice, it is justified to assume in certain applications that the direction-of-arrival (DOA) of the desired source is approximately known. Using the known DOA, fixed spatial filters such as the delay-and-sum beamformer can be steered to extract the desired source. However, it is well-known that fixed data-independent spatial filters do not provide sufficient reduction of directional interferers. Instead, the DOA information can be used to estimate the statistics of the desired and the undesired signals and to compute optimal data-dependent spatial filters. One way the DOA is exploited for optimal spatial filtering in the literature, is by designing DOA-based narrowband detectors to determine whether a desired or an undesired signal is dominant at each time-frequency (TF) bin. Subsequently, the statistics of the desired and the undesired signals can be estimated during the TF bins where the respective signal is dominant. In a similar manner, a Gaussian signal model-based detector which does not incorporate DOA information has been used in scenarios where the undesired signal consists of stationary background noise. However, when the undesired signal is non-stationary, resulting for example from interfering speakers, such a Gaussian signal model-based detector is unable to robustly distinguish desired from undesired speech. To this end, we propose a DOA model-based detector to determine the dominant source at each TF bin and estimate the desired and undesired signal statistics. We demonstrate that data-dependent spatial filters that use the statistics estimated by the proposed framework achieve very good undesired signal reduction, even when using only three microphones.

Hybrid ICA-Bayesian Network approach reveals distinct effective connectivity differences in schizophrenia

PubMed Central

Kim, D.; Burge, J.; Lane, T.; Pearlson, G. D; Kiehl, K. A; Calhoun, V. D.

2008-01-01

We utilized a discrete dynamic Bayesian network (dDBN) approach (Burge et al., 2007) to determine differences in brain regions between patients with schizophrenia and healthy controls on a measure of effective connectivity, termed the approximate conditional likelihood score (ACL) (Burge and Lane, 2005). The ACL score represents a class-discriminative measure of effective connectivity by measuring the relative likelihood of the correlation between brain regions in one group versus another. The algorithm is capable of finding non-linear relationships between brain regions because it uses discrete rather than continuous values and attempts to model temporal relationships with a first-order Markov and stationary assumption constraint (Papoulis, 1991). Since Bayesian networks are overly sensitive to noisy data, we introduced an independent component analysis (ICA) filtering approach that attempted to reduce the noise found in fMRI data by unmixing the raw datasets into a set of independent spatial component maps. Components that represented noise were removed and the remaining components reconstructed into the dimensions of the original fMRI datasets. We applied the dDBN algorithm to a group of 35 patients with schizophrenia and 35 matched healthy controls using an ICA filtered and unfiltered approach. We determined that filtering the data significantly improved the magnitude of the ACL score. Patients showed the greatest ACL scores in several regions, most markedly the cerebellar vermis and hemispheres. Our findings suggest that schizophrenia patients exhibit weaker connectivity than healthy controls in multiple regions, including bilateral temporal and frontal cortices, plus cerebellum during an auditory paradigm. PMID:18602482

Low-NA single-mode LMA photonic crystal rod fiber amplifier

NASA Astrophysics Data System (ADS)

Alkeskjold, Thomas Tanggaard; Laurila, Marko; Scolari, Lara; Broeng, Jes

2011-02-01

Enabling Single-Mode (SM) operation in Large-Mode-Area (LMA) fiber amplifiers and lasers is critical, since a SM output ensures high beam quality and excellent pointing stability. In this paper, we demonstrate and test a new design approach for achieving ultra-low NA SM rod fibers by using a spatially Distributed Mode Filter (DMF). This approach achieves SM performance in a short and straight rod fiber and allows preform tolerances to be compensated during draw. A low-NA SM rod fiber amplifier having a mode field diameter of ~60μm at 1064nm and a pump absorption of 27dB/m at 976nm is demonstrated.

Colloidal Bandpass and Bandgap Filters

NASA Astrophysics Data System (ADS)

Yellen, Benjamin; Tahir, Mukarram; Ouyang, Yuyu; Nori, Franco

2013-03-01

Thermally or deterministically-driven transport of objects through asymmetric potential energy landscapes (ratchet-based motion) is of considerable interest as models for biological transport and as methods for controlling the flow of information, material, and energy. Here, we provide a general framework for implementing a colloidal bandpass filter, in which particles of a specific size range can be selectively transported through a periodic lattice, whereas larger or smaller particles are dynamically trapped in closed-orbits. Our approach is based on quasi-static (adiabatic) transition in a tunable potential energy landscape composed of a multi-frequency magnetic field input signal with the static field of a spatially-periodic magnetization. By tuning the phase shifts between the input signal and the relative forcing coefficients, large-sized particles may experience no local energy barriers, medium-sized particles experience only one local energy barrier, and small-sized particles experience two local energy barriers. The odd symmetry present in this system can be used to nudge the medium-sized particles along an open pathway, whereas the large or small beads remain trapped in a closed-orbit, leading to a bandpass filter, and vice versa for a bandgap filter. NSF CMMI - 0800173, Youth 100 Scholars Fund

Linking landscape characteristics to mineral site use by band-tailed pigeons in Western Oregon: Coarse-filter conservation with fine-filter tuning

USGS Publications Warehouse

Overton, C.T.; Schmitz, R.A.; Casazza, Michael L.

2006-01-01

Mineral sites are scarce resources of high ion concentration used heavily by the Pacific Coast subpopulation of band-tailed pigeons. Over 20% of all known mineral sites used by band-tailed pigeons in western Oregon, including all hot springs, have been abandoned. Prior investigations have not analyzed stand or landscape level habitat composition in relation to band-tailed pigeon use of mineral sites. We used logistic regression models to evaluate the influence of habitat types, identified from Gap Analysis Program (GAP) products at two spatial scales, on the odds of mineral site use in Oregon (n = 69 currently used and 20 historically used). Our results indicated that the odds of current use were negatively associated with non-forested terrestrial and private land area around mineral sites. Similarly, the odds of current mineral site use were positively associated with forested and special status (GAP stewardship codes 1 and 2) land area. The most important variable associated with the odds of mineral site use was the amount of non-forested land cover at either spatial scale. Our results demonstrate the utility of meso-scale geographic information designed for regional, coarse-filter approaches to conservation in fine-filter investigation of wildlife-habitat relationships. Adjacent landcover and ownership status explain the pattern of use for known mineral sites in western Oregon. In order for conservation and management activities for band-tailed pigeons to be successful, mineral sites need to be addressed as important and vulnerable resources. Management of band-tailed pigeons should incorporate the potential for forest management activities and land ownership patterns to influence the risk of mineral site abandonment.

Effect of spatial filtering on crosstalk reduction in surface EMG recordings.

PubMed

Mesin, Luca; Smith, Stuart; Hugo, Suzanne; Viljoen, Suretha; Hanekom, Tania

2009-04-01

Increasing the selectivity of the detection system in surface electromyography (EMG) is beneficial in the collection of information of a specific portion of the investigated muscle and to reduce the contribution of undesired components, such as non-propagating components (due to generation or end-of-fibre effects) or crosstalk from nearby muscles. A comparison of the ability of different spatial filters to reduce the amount of crosstalk in surface EMG measurements was conducted in this paper using simulated signals. It focused on the influence of different properties of the muscle anatomy (changing subcutaneous layer thickness, skin conductivity, fibre length) and detection system (single, double and normal double differential, with two inter-electrode distances - IED) on the amount of crosstalk present in the measurements. A cylindrical multilayer (skin, subcutaneous tissue, muscle, bone) analytical model was used to simulate single fibre action potentials (SFAPs). Fibres were grouped together in motor units (MUs) and motor unit action potentials (MUAPs) were obtained by adding the SFAPs of the corresponding fibres. Interference surface EMG signals were obtained, modelling the recruitment of MUs and rate coding. The average rectified value (ARV) and mean frequency (MNF) content of the EMG signals were studied and used as a basis for determining the selectivity of each spatial filter. From these results it was found that the selectivity of each spatial filter varies depending on the transversal location of the measurement electrodes and on the anatomy. An increase in skin conductivity favourably affects the selectivity of normal double differential filters as does an increase in subcutaneous layer thickness. An increase in IED decreases the selectivity of all the analysed filters.

Modelling spatial concordance between Rocky Mountain spotted fever disease incidence and habitat probability of its vector Dermacentor variabilis (American dog tick).

PubMed

Atkinson, Samuel F; Sarkar, Sahotra; Aviña, Aldo; Schuermann, Jim A; Williamson, Phillip

2012-11-01

The spatial distribution of Dermacentor variabilis, the most commonly identified vector of the bacterium Rickettsia rickettsii which causes Rocky Mountain spotted fever (RMSF) in humans, and the spatial distribution of RMSF, have not been previously studied in the south central United States of America, particularly in Texas. From an epidemiological perspective, one would tend to hypothesise that there would be a high degree of spatial concordance between the habitat suitability for the tick and the incidence of the disease. Both maximum-entropy modelling of the tick's habitat suitability and spatially adaptive filters modelling of the human incidence of RMSF disease provide reliable portrayals of the spatial distributions of these phenomenons. Even though rates of human cases of RMSF in Texas and rates of Dermacentor ticks infected with Rickettsia bacteria are both relatively low in Texas, the best data currently available allows a preliminary indication that the assumption of high levels of spatial concordance would not be correct in Texas (Kappa coefficient of agreement = 0.17). It will take substantially more data to provide conclusive findings, and to understand the results reported here, but this study provides an approach to begin understanding the discrepancy.

Single-trial detection of visual evoked potentials by common spatial patterns and wavelet filtering for brain-computer interface.

PubMed

Tu, Yiheng; Huang, Gan; Hung, Yeung Sam; Hu, Li; Hu, Yong; Zhang, Zhiguo

2013-01-01

Event-related potentials (ERPs) are widely used in brain-computer interface (BCI) systems as input signals conveying a subject's intention. A fast and reliable single-trial ERP detection method can be used to develop a BCI system with both high speed and high accuracy. However, most of single-trial ERP detection methods are developed for offline EEG analysis and thus have a high computational complexity and need manual operations. Therefore, they are not applicable to practical BCI systems, which require a low-complexity and automatic ERP detection method. This work presents a joint spatial-time-frequency filter that combines common spatial patterns (CSP) and wavelet filtering (WF) for improving the signal-to-noise (SNR) of visual evoked potentials (VEP), which can lead to a single-trial ERP-based BCI.

Evaluating the effect of spatial subsetting on subpixel unmixing methodology applied to ASTER over a hydrothermally altered terrain

NASA Astrophysics Data System (ADS)

Ayoobi, Iman; Tangestani, Majid H.

2017-10-01

This study investigates the effect of spatial subsets of Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) L1B visible-near infrared and short wave-infrared (VNIR-SWIR) data on matched filtering results at the central part of Kerman magmatic arc, where abundant porphyry copper deposits exist. The matched filtering (MF) procedure was run separately at sites containing hydrothermal minerals such as sericite, kaolinite, chlorite, and jarosite to map the abundances of these minerals on spatial subsets containing 100, 75, 50, and 25 percent of the original scene. Results were evaluated by comparing the matched filtering scores with the mineral abundances obtained by semi-quantitative XRD analysis of corresponding field samples. It was concluded that MF method should be applied to the whole scene prior to any data subsetting.

Fast Image Restoration for Spatially Varying Defocus Blur of Imaging Sensor

PubMed Central

Cheong, Hejin; Chae, Eunjung; Lee, Eunsung; Jo, Gwanghyun; Paik, Joonki

2015-01-01

This paper presents a fast adaptive image restoration method for removing spatially varying out-of-focus blur of a general imaging sensor. After estimating the parameters of space-variant point-spread-function (PSF) using the derivative in each uniformly blurred region, the proposed method performs spatially adaptive image restoration by selecting the optimal restoration filter according to the estimated blur parameters. Each restoration filter is implemented in the form of a combination of multiple FIR filters, which guarantees the fast image restoration without the need of iterative or recursive processing. Experimental results show that the proposed method outperforms existing space-invariant restoration methods in the sense of both objective and subjective performance measures. The proposed algorithm can be employed to a wide area of image restoration applications, such as mobile imaging devices, robot vision, and satellite image processing. PMID:25569760

Application of the Karhunen-Loeve transform temporal image filter to reduce noise in real-time cardiac cine MRI

NASA Astrophysics Data System (ADS)

Ding, Yu; Chung, Yiu-Cho; Raman, Subha V.; Simonetti, Orlando P.

2009-06-01

Real-time dynamic magnetic resonance imaging (MRI) typically sacrifices the signal-to-noise ratio (SNR) to achieve higher spatial and temporal resolution. Spatial and/or temporal filtering (e.g., low-pass filtering or averaging) of dynamic images improves the SNR at the expense of edge sharpness. We describe the application of a temporal filter for dynamic MR image series based on the Karhunen-Loeve transform (KLT) to remove random noise without blurring stationary or moving edges and requiring no training data. In this paper, we present several properties of this filter and their effects on filter performance, and propose an automatic way to find the filter cutoff based on the autocorrelation of the eigenimages. Numerical simulation and in vivo real-time cardiac cine MR image series spanning multiple cardiac cycles acquired using multi-channel sensitivity-encoded MRI, i.e., parallel imaging, are used to validate and demonstrate these properties. We found that in this application, the noise standard deviation was reduced to 42% of the original with no apparent image blurring by using the proposed filter cutoff. Greater noise reduction can be achieved by increasing the length of the image series. This advantage of KLT filtering provides flexibility in the form of another scan parameter to trade for SNR.

Assessment of local hydraulic properties from electrical resistivity tomography monitoring of a three-dimensional synthetic tracer test experiment

NASA Astrophysics Data System (ADS)

Camporese, M.; Cassiani, G.; Deiana, R.; Salandin, P.

2011-12-01

In recent years geophysical methods have become increasingly popular for hydrological applications. Time-lapse electrical resistivity tomography (ERT) represents a potentially powerful tool for subsurface solute transport characterization since a full picture of the spatiotemporal evolution of the process can be obtained. However, the quantitative interpretation of tracer tests is difficult because of the uncertainty related to the geoelectrical inversion, the constitutive models linking geophysical and hydrological quantities, and the a priori unknown heterogeneous properties of natural formations. Here an approach based on the Lagrangian formulation of transport and the ensemble Kalman filter (EnKF) data assimilation technique is applied to assess the spatial distribution of hydraulic conductivity K by incorporating time-lapse cross-hole ERT data. Electrical data consist of three-dimensional cross-hole ERT images generated for a synthetic tracer test in a heterogeneous aquifer. Under the assumption that the solute spreads as a passive tracer, for high Peclet numbers the spatial moments of the evolving plume are dominated by the spatial distribution of the hydraulic conductivity. The assimilation of the electrical conductivity 4D images allows updating of the hydrological state as well as the spatial distribution of K. Thus, delineation of the tracer plume and estimation of the local aquifer heterogeneity can be achieved at the same time by means of this interpretation of time-lapse electrical images from tracer tests. We assess the impact on the performance of the hydrological inversion of (i) the uncertainty inherently affecting ERT inversions in terms of tracer concentration and (ii) the choice of the prior statistics of K. Our findings show that realistic ERT images can be integrated into a hydrological model even within an uncoupled inverse modeling framework. The reconstruction of the hydraulic conductivity spatial distribution is satisfactory in the portion of the domain directly covered by the passage of the tracer. Aside from the issues commonly affecting inverse models, the proposed approach is subject to the problem of the filter inbreeding and the retrieval performance is sensitive to the choice of K prior geostatistical parameters.

DVD-COOP: Innovative Conjunction Prediction Using Voronoi-filter based on the Dynamic Voronoi Diagram of 3D Spheres

NASA Astrophysics Data System (ADS)

Cha, J.; Ryu, J.; Lee, M.; Song, C.; Cho, Y.; Schumacher, P.; Mah, M.; Kim, D.

Conjunction prediction is one of the critical operations in space situational awareness (SSA). For geospace objects, common algorithms for conjunction prediction are usually based on all-pairwise check, spatial hash, or kd-tree. Computational load is usually reduced through some filters. However, there exists a good chance of missing potential collisions between space objects. We present a novel algorithm which both guarantees no missing conjunction and is efficient to answer to a variety of spatial queries including pairwise conjunction prediction. The algorithm takes only O(k log N) time for N objects in the worst case to answer conjunctions where k is a constant which is linear to prediction time length. The proposed algorithm, named DVD-COOP (Dynamic Voronoi Diagram-based Conjunctive Orbital Object Predictor), is based on the dynamic Voronoi diagram of moving spherical balls in 3D space. The algorithm has a preprocessing which consists of two steps: The construction of an initial Voronoi diagram (taking O(N) time on average) and the construction of a priority queue for the events of topology changes in the Voronoi diagram (taking O(N log N) time in the worst case). The scalability of the proposed algorithm is also discussed. We hope that the proposed Voronoi-approach will change the computational paradigm in spatial reasoning among space objects.

Adaptive matched filter spatial detection performance on standard imagery from a wideband VHF/UHF SAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allen, M.R.; Phillips, S.A.; Sofianos, D.J.

1994-12-31

The adaptive matched filter was implemented as a spatial detector for amplitude-only or complex images, and applied to an image formed by standard narrow band means from a wide angle, wideband radar. Direct performance comparisons were made between different implementations and various matched and mismatched cases by using a novel approach to generate ROC curves parametrically. For perfectly matched cases, performance using imaged targets was found to be significantly lower than potential performance of artificial targets whose features differed from the background. Incremental gain due to whitening the background was also found to be small, indicating little background spatial correlation.more » It is conjectured that the relatively featureless behavior in both targets and background is due to the image formation process, since this technique averages together all wide angle, wideband information. For mismatched cases where the signature was unknown, the amplitude detector losses were approximately equal to whatever gain over noncoherent integration that matching provided. However, the complex detector was generally very sensitive to unknown information, especially phase, and produced much larger losses. Whitening under these mismatched conditions produced further losses. Detector choice thus depends primarily on how reproducible target signatures are, especially if phase is used, and the subsequent number of stored signatures necessary to account for various imaging aspect angles.« less

A high resolution model of linear trend in mass variations from DMT-2: Added value of accounting for coloured noise in GRACE data

NASA Astrophysics Data System (ADS)

Farahani, Hassan H.; Ditmar, Pavel; Inácio, Pedro; Didova, Olga; Gunter, Brian; Klees, Roland; Guo, Xiang; Guo, Jing; Sun, Yu; Liu, Xianglin; Zhao, Qile; Riva, Riccardo

2017-01-01

We present a high resolution model of the linear trend in the Earth's mass variations based on DMT-2 (Delft Mass Transport model, release 2). DMT-2 was produced primarily from K-Band Ranging (KBR) data of the Gravity Recovery And Climate Experiment (GRACE). It comprises a time series of monthly solutions complete to spherical harmonic degree 120. A novel feature in its production was the accurate computation and incorporation of stochastic properties of coloured noise when processing KBR data. The unconstrained DMT-2 monthly solutions are used to estimate the linear trend together with a bias, as well as annual and semi-annual sinusoidal terms. The linear term is further processed with an anisotropic Wiener filter, which uses full noise and signal covariance matrices. Given the fact that noise in an unconstrained model of the trend is reduced substantially as compared to monthly solutions, the Wiener filter associated with the trend is much less aggressive compared to a Wiener filter applied to monthly solutions. Consequently, the trend estimate shows an enhanced spatial resolution. It allows signals in relatively small water bodies, such as Aral sea and Ladoga lake, to be detected. Over the ice sheets, it allows for a clear identification of signals associated with some outlet glaciers or their groups. We compare the obtained trend estimate with the ones from the CSR-RL05 model using (i) the same approach based on monthly noise covariance matrices and (ii) a commonly-used approach based on the DDK-filtered monthly solutions. We use satellite altimetry data as independent control data. The comparison demonstrates a high spatial resolution of the DMT-2 linear trend. We link this to the usage of high-accuracy monthly noise covariance matrices, which is due to an accurate computation and incorporation of coloured noise when processing KBR data. A preliminary comparison of the linear trend based on DMT-2 with that computed from GSFC_global_mascons_v01 reveals, among other, a high concentration of the signal along the coast for both models in areas like the ice sheets, Gulf of Alaska, and Iceland.

Betty Petersen Memorial Library - NCWCP Publications - NWS

Science.gov Websites

Filters to Variational Statistical Analysis with Spatially Inhomogeneous Covariances (.PDF file) 432 2001 file) 456 2008 Purser, R. James Normalization Of The Diffusive Filters That Represent The Inhomogeneous file) 457 2008 Purser, R. James Normalization Of The Diffusive Filters That Represent The Inhomogeneous

Characterisation of optical filters for broadband UVA radiometer

NASA Astrophysics Data System (ADS)

Alves, Luciana C.; Coelho, Carla T.; Corrêa, Jaqueline S. P. M.; Menegotto, Thiago; Ferreira da Silva, Thiago; Aparecida de Souza, Muriel; Melo da Silva, Elisama; Simões de Lima, Maurício; Dornelles de Alvarenga, Ana Paula

2016-07-01

Optical filters were characterized in order to know its suitability for use in broadband UVA radiometer head for spectral irradiance measurements. The spectral transmittance, the angular dependence and the spatial uniformity of the spectral transmittance of the UVA optical filters were investigated. The temperature dependence of the transmittance was also studied.

Use of phase-locking value in sensorimotor rhythm-based brain-computer interface: zero-phase coupling and effects of spatial filters.

PubMed

Jian, Wenjuan; Chen, Minyou; McFarland, Dennis J

2017-11-01

Phase-locking value (PLV) is a potentially useful feature in sensorimotor rhythm-based brain-computer interface (BCI). However, volume conduction may cause spurious zero-phase coupling between two EEG signals and it is not clear whether PLV effects are independent of spectral amplitude. Volume conduction might be reduced by spatial filtering, but it is uncertain what impact this might have on PLV. Therefore, the goal of this study was to explore whether zero-phase PLV is meaningful and how it is affected by spatial filtering. Both amplitude and PLV feature were extracted in the frequency band of 10-15 Hz by classical methods using archival EEG data of 18 subjects trained on a two-target BCI task. The results show that with right ear-referenced data, there is meaningful long-range zero-phase synchronization likely involving the primary motor area and the supplementary motor area that cannot be explained by volume conduction. Another novel finding is that the large Laplacian spatial filter enhances the amplitude feature but eliminates most of the phase information seen in ear-referenced data. A bipolar channel using phase-coupled areas also includes both phase and amplitude information and has a significant practical advantage since fewer channels required.

Forensic steganalysis: determining the stego key in spatial domain steganography

NASA Astrophysics Data System (ADS)

Fridrich, Jessica; Goljan, Miroslav; Soukal, David; Holotyak, Taras

2005-03-01

This paper is an extension of our work on stego key search for JPEG images published at EI SPIE in 2004. We provide a more general theoretical description of the methodology, apply our approach to the spatial domain, and add a method that determines the stego key from multiple images. We show that in the spatial domain the stego key search can be made significantly more efficient by working with the noise component of the image obtained using a denoising filter. The technique is tested on the LSB embedding paradigm and on a special case of embedding by noise adding (the +/-1 embedding). The stego key search can be performed for a wide class of steganographic techniques even for sizes of secret message well below those detectable using known methods. The proposed strategy may prove useful to forensic analysts and law enforcement.

Scanning probe acceleration microscopy (SPAM) in fluids: Mapping mechanical properties of surfaces at the nanoscale

NASA Astrophysics Data System (ADS)

Legleiter, Justin; Park, Matthew; Cusick, Brian; Kowalewski, Tomasz

2006-03-01

One of the major thrusts in proximal probe techniques is combination of imaging capabilities with simultaneous measurements of physical properties. In tapping mode atomic force microscopy (TMAFM), the most straightforward way to accomplish this goal is to reconstruct the time-resolved force interaction between the tip and surface. These tip-sample forces can be used to detect interactions (e.g., binding sites) and map material properties with nanoscale spatial resolution. Here, we describe a previously unreported approach, which we refer to as scanning probe acceleration microscopy (SPAM), in which the TMAFM cantilever acts as an accelerometer to extract tip-sample forces during imaging. This method utilizes the second derivative of the deflection signal to recover the tip acceleration trajectory. The challenge in such an approach is that with real, noisy data, the second derivative of the signal is strongly dominated by the noise. This problem is solved by taking advantage of the fact that most of the information about the deflection trajectory is contained in the higher harmonics, making it possible to filter the signal by “comb” filtering, i.e., by taking its Fourier transform and inverting it while selectively retaining only the intensities at integer harmonic frequencies. Such a comb filtering method works particularly well in fluid TMAFM because of the highly distorted character of the deflection signal. Numerical simulations and in situ TMAFM experiments on supported lipid bilayer patches on mica are reported to demonstrate the validity of this approach.

Robust estimation approach for blind denoising.

PubMed

Rabie, Tamer

2005-11-01

This work develops a new robust statistical framework for blind image denoising. Robust statistics addresses the problem of estimation when the idealized assumptions about a system are occasionally violated. The contaminating noise in an image is considered as a violation of the assumption of spatial coherence of the image intensities and is treated as an outlier random variable. A denoised image is estimated by fitting a spatially coherent stationary image model to the available noisy data using a robust estimator-based regression method within an optimal-size adaptive window. The robust formulation aims at eliminating the noise outliers while preserving the edge structures in the restored image. Several examples demonstrating the effectiveness of this robust denoising technique are reported and a comparison with other standard denoising filters is presented.

Locating Sensors for Detecting Source-to-Target Patterns of Special Nuclear Material Smuggling: A Spatial Information Theoretic Approach

PubMed Central

Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong

2010-01-01

In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy. PMID:22163641

Simultaneous two-wavelength tri-window common-path digital holography

NASA Astrophysics Data System (ADS)

Liu, Lei; Shan, Mingguang; Zhong, Zhi

2018-06-01

Two-wavelength common-path off-axis digital holography is proposed with a tri-window in a single shot. It is established using a standard 4f optical image system with a 2D Ronchi grating placed outside the Fourier plane. The input plane consists of three windows: one for the object and the other two for reference. Aided by a spatial filter together with two orthogonal linear polarizers in the Fourier plane, the two-wavelength information is encoded into a multiplexed hologram with two orthogonal spatial frequencies that enable full separation of spectral information in the digital Fourier space without resolution loss. Theoretical analysis and experimental results illustrate that our approach can simultaneously perform quantitative phase imaging at two wavelengths.

Locating sensors for detecting source-to-target patterns of special nuclear material smuggling: a spatial information theoretic approach.

PubMed

Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong

2010-01-01

In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy.

Spatially adaptive bases in wavelet-based coding of semi-regular meshes

NASA Astrophysics Data System (ADS)

Denis, Leon; Florea, Ruxandra; Munteanu, Adrian; Schelkens, Peter

2010-05-01

In this paper we present a wavelet-based coding approach for semi-regular meshes, which spatially adapts the employed wavelet basis in the wavelet transformation of the mesh. The spatially-adaptive nature of the transform requires additional information to be stored in the bit-stream in order to allow the reconstruction of the transformed mesh at the decoder side. In order to limit this overhead, the mesh is first segmented into regions of approximately equal size. For each spatial region, a predictor is selected in a rate-distortion optimal manner by using a Lagrangian rate-distortion optimization technique. When compared against the classical wavelet transform employing the butterfly subdivision filter, experiments reveal that the proposed spatially-adaptive wavelet transform significantly decreases the energy of the wavelet coefficients for all subbands. Preliminary results show also that employing the proposed transform for the lowest-resolution subband systematically yields improved compression performance at low-to-medium bit-rates. For the Venus and Rabbit test models the compression improvements add up to 1.47 dB and 0.95 dB, respectively.

Confocal laser induced fluorescence with comparable spatial localization to the conventional method

NASA Astrophysics Data System (ADS)

Thompson, Derek S.; Henriquez, Miguel F.; Scime, Earl E.; Good, Timothy N.

2017-10-01

We present measurements of ion velocity distributions obtained by laser induced fluorescence (LIF) using a single viewport in an argon plasma. A patent pending design, which we refer to as the confocal fluorescence telescope, combines large objective lenses with a large central obscuration and a spatial filter to achieve high spatial localization along the laser injection direction. Models of the injection and collection optics of the two assemblies are used to provide a theoretical estimate of the spatial localization of the confocal arrangement, which is taken to be the full width at half maximum of the spatial optical response. The new design achieves approximately 1.4 mm localization at a focal length of 148.7 mm, improving on previously published designs by an order of magnitude and approaching the localization achieved by the conventional method. The confocal method, however, does so without requiring a pair of separated, perpendicular optical paths. The confocal technique therefore eases the two window access requirement of the conventional method, extending the application of LIF to experiments where conventional LIF measurements have been impossible or difficult, or where multiple viewports are scarce.

Daytime adaptive optics for deep space optical communications

NASA Technical Reports Server (NTRS)

Wilson, Keith; Troy, M.; Srinivasan, M.; Platt, B.; Vilnrotter, V.; Wright, M.; Garkanian, V.; Hemmati, H.

2003-01-01

The deep space optical communications subsystem offers a higher bandwidth communications link in smaller size, lower mass, and lower power consumption subsystem than does RF. To demonstrate the benefit of this technology to deep space communications NASA plans to launch an optical telecommunications package on the 2009 Mars Telecommunications orbiter spacecraft. Current performance goals are 30-Mbps from opposition, and 1-Mbps near conjunction (-3 degrees Sun-Earth-Probe angle). Yet, near conjunction the background noise from the day sky will degrade the performance of the optical link. Spectral and spatial filtering and higher modulation formats can mitigate the effects of background sky. Narrowband spectral filters can result in loss of link margin, and higher modulation formats require higher transmitted peak powers. In contrast, spatial filtering at the receiver has the potential of being lossless while providing the required sky background rejection. Adaptive optics techniques can correct wave front aberrations caused by atmospheric turbulence and enable near-diffraction-limited performance of the receiving telescope. Such performance facilitates spatial filtering, and allows the receiver field-of-view and hence the noise from the sky background to be reduced.

Multi-Temporal Land Cover Classification with Sequential Recurrent Encoders

NASA Astrophysics Data System (ADS)

Rußwurm, Marc; Körner, Marco

2018-03-01

Earth observation (EO) sensors deliver data with daily or weekly temporal resolution. Most land use and land cover (LULC) approaches, however, expect cloud-free and mono-temporal observations. The increasing temporal capabilities of today's sensors enables the use of temporal, along with spectral and spatial features. Domains, such as speech recognition or neural machine translation, work with inherently temporal data and, today, achieve impressive results using sequential encoder-decoder structures. Inspired by these sequence-to-sequence models, we adapt an encoder structure with convolutional recurrent layers in order to approximate a phenological model for vegetation classes based on a temporal sequence of Sentinel 2 (S2) images. In our experiments, we visualize internal activations over a sequence of cloudy and non-cloudy images and find several recurrent cells, which reduce the input activity for cloudy observations. Hence, we assume that our network has learned cloud-filtering schemes solely from input data, which could alleviate the need for tedious cloud-filtering as a preprocessing step for many EO approaches. Moreover, using unfiltered temporal series of top-of-atmosphere (TOA) reflectance data, we achieved in our experiments state-of-the-art classification accuracies on a large number of crop classes with minimal preprocessing compared to other classification approaches.

Robust Kriged Kalman Filtering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baingana, Brian; Dall'Anese, Emiliano; Mateos, Gonzalo

2015-11-11

Although the kriged Kalman filter (KKF) has well-documented merits for prediction of spatial-temporal processes, its performance degrades in the presence of outliers due to anomalous events, or measurement equipment failures. This paper proposes a robust KKF model that explicitly accounts for presence of measurement outliers. Exploiting outlier sparsity, a novel l1-regularized estimator that jointly predicts the spatial-temporal process at unmonitored locations, while identifying measurement outliers is put forth. Numerical tests are conducted on a synthetic Internet protocol (IP) network, and real transformer load data. Test results corroborate the effectiveness of the novel estimator in joint spatial prediction and outlier identification.

Selected annotated bibliographies for adaptive filtering of digital image data

USGS Publications Warehouse

Mayers, Margaret; Wood, Lynnette

1988-01-01

Digital spatial filtering is an important tool both for enhancing the information content of satellite image data and for implementing cosmetic effects which make the imagery more interpretable and appealing to the eye. Spatial filtering is a context-dependent operation that alters the gray level of a pixel by computing a weighted average formed from the gray level values of other pixels in the immediate vicinity.Traditional spatial filtering involves passing a particular filter or set of filters over an entire image. This assumes that the filter parameter values are appropriate for the entire image, which in turn is based on the assumption that the statistics of the image are constant over the image. However, the statistics of an image may vary widely over the image, requiring an adaptive or "smart" filter whose parameters change as a function of the local statistical properties of the image. Then a pixel would be averaged only with more typical members of the same population. This annotated bibliography cites some of the work done in the area of adaptive filtering. The methods usually fall into two categories, (a) those that segment the image into subregions, each assumed to have stationary statistics, and use a different filter on each subregion, and (b) those that use a two-dimensional "sliding window" to continuously estimate the filter either the spatial or frequency domain, or may utilize both domains. They may be used to deal with images degraded by space variant noise, to suppress undesirable local radiometric statistics while enforcing desirable (user-defined) statistics, to treat problems where space-variant point spread functions are involved, to segment images into regions of constant value for classification, or to "tune" images in order to remove (nonstationary) variations in illumination, noise, contrast, shadows, or haze.Since adpative filtering, like nonadaptive filtering, is used in image processing to accomplish various goals, this bibliography is organized in subsections based on application areas. Contrast enhancement, edge enhancement, noise suppression, and smoothing are typically performed in order imaging process, (for example, degradations due to the optics and electronics of the sensor, or to blurring caused by the intervening atmosphere, uniform motion, or defocused optics). Some of the papers listed may apply to more than one of the above categories; when this happens the paper is listed under the category for which the paper's emphasis is greatest. A list of survey articles is also supplied. These articles are general discussions on adaptive filters and reviews of work done. Finally, a short list of miscellaneous articles are listed which were felt to be sufficiently important to be included, but do not fit into any of the above categories. This bibliography, listing items published from 1970 through 1987, is extensive, but by no means complete. It is intended as a guide for scientists and image analysts, listing references for background information as well as areas of significant development in adaptive filtering.

Effects of spatial frequency and location of fearful faces on human amygdala activity.

PubMed

Morawetz, Carmen; Baudewig, Juergen; Treue, Stefan; Dechent, Peter

2011-01-31

Facial emotion perception plays a fundamental role in interpersonal social interactions. Images of faces contain visual information at various spatial frequencies. The amygdala has previously been reported to be preferentially responsive to low-spatial frequency (LSF) rather than to high-spatial frequency (HSF) filtered images of faces presented at the center of the visual field. Furthermore, it has been proposed that the amygdala might be especially sensitive to affective stimuli in the periphery. In the present study we investigated the impact of spatial frequency and stimulus eccentricity on face processing in the human amygdala and fusiform gyrus using functional magnetic resonance imaging (fMRI). The spatial frequencies of pictures of fearful faces were filtered to produce images that retained only LSF or HSF information. Facial images were presented either in the left or right visual field at two different eccentricities. In contrast to previous findings, we found that the amygdala responds to LSF and HSF stimuli in a similar manner regardless of the location of the affective stimuli in the visual field. Furthermore, the fusiform gyrus did not show differential responses to spatial frequency filtered images of faces. Our findings argue against the view that LSF information plays a crucial role in the processing of facial expressions in the amygdala and of a higher sensitivity to affective stimuli in the periphery. Copyright © 2010 Elsevier B.V. All rights reserved.

Filter arrays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Page, Ralph H.; Doty, Patrick F.

2017-08-01

The various technologies presented herein relate to a tiled filter array that can be used in connection with performance of spatial sampling of optical signals. The filter array comprises filter tiles, wherein a first plurality of filter tiles are formed from a first material, the first material being configured such that only photons having wavelengths in a first wavelength band pass therethrough. A second plurality of filter tiles is formed from a second material, the second material being configured such that only photons having wavelengths in a second wavelength band pass therethrough. The first plurality of filter tiles and themore » second plurality of filter tiles can be interspersed to form the filter array comprising an alternating arrangement of first filter tiles and second filter tiles.« less

Optical restoration of images blurred by atmospheric turbulence using optimum filter theory.

PubMed

Horner, J L

1970-01-01

The results of optimum filtering from communications theory have been applied to an image restoration problem. Photographic film imagery, degraded by long-term artificial atmospheric turbulence, has been restored by spatial filters placed in the Fourier transform plane. The time-averaged point spread function was measured and used in designing the filters. Both the simple inverse filter and the optimum least-mean-square filters were used in the restoration experiments. The superiority of the latter is conclusively demonstrated. An optical analog processor was used for the restoration.

Gaussian Process Kalman Filter for Focal Plane Wavefront Correction and Exoplanet Signal Extraction

NASA Astrophysics Data System (ADS)

Sun, He; Kasdin, N. Jeremy

2018-01-01

Currently, the ultimate limitation of space-based coronagraphy is the ability to subtract the residual PSF after wavefront correction to reveal the planet. Called reference difference imaging (RDI), the technique consists of conducting wavefront control to collect the reference point spread function (PSF) by observing a bright star, and then extracting target planet signals by subtracting a weighted sum of reference PSFs. Unfortunately, this technique is inherently inefficient because it spends a significant fraction of the observing time on the reference star rather than the target star with the planet. Recent progress in model based wavefront estimation suggests an alternative approach. A Kalman filter can be used to estimate the stellar PSF for correction by the wavefront control system while simultaneously estimating the planet signal. Without observing the reference star, the (extended) Kalman filter directly utilizes the wavefront correction data and combines the time series observations and model predictions to estimate the stellar PSF and planet signals. Because wavefront correction is used during the entire observation with no slewing, the system has inherently better stability. In this poster we show our results aimed at further improving our Kalman filter estimation accuracy by including not only temporal correlations but also spatial correlations among neighboring pixels in the images. This technique is known as a Gaussian process Kalman filter (GPKF). We also demonstrate the advantages of using a Kalman filter rather than RDI by simulating a real space exoplanet detection mission.

Spatial frequency domain imaging using a snap-shot filter mosaic camera with multi-wavelength sensitive pixels

NASA Astrophysics Data System (ADS)

Strömberg, Tomas; Saager, Rolf B.; Kennedy, Gordon T.; Fredriksson, Ingemar; Salerud, Göran; Durkin, Anthony J.; Larsson, Marcus

2018-02-01

Spatial frequency domain imaging (SFDI) utilizes a digital light processing (DLP) projector for illuminating turbid media with sinusoidal patterns. The tissue absorption (μa) and reduced scattering coefficient (μ,s) are calculated by analyzing the modulation transfer function for at least two spatial frequencies. We evaluated different illumination strategies with a red, green and blue light emitting diodes (LED) in the DLP, while imaging with a filter mosaic camera, XiSpec, with 16 different multi-wavelength sensitive pixels in the 470-630 nm wavelength range. Data were compared to SFDI by a multispectral camera setup (MSI) consisting of four cameras with bandpass filters centered at 475, 560, 580 and 650 nm. A pointwise system for comprehensive microcirculation analysis was used (EPOS) for comparison. A 5-min arterial occlusion and release protocol on the forearm of a Caucasian male with fair skin was analyzed by fitting the absorption spectra of the chromophores HbO2, Hb and melanin to the estimatedμa. The tissue fractions of red blood cells (fRBC), melanin (/mel) and the Hb oxygenation (S02 ) were calculated at baseline, end of occlusion, early after release and late after release. EPOS results showed a decrease in S02 during the occlusion and hyperemia during release (S02 = 40%, 5%, 80% and 51%). The fRBC showed an increase during occlusion and release phases. The best MSI resemblance to the EPOS was for green LED illumination (S02 = 53%, 9%, 82%, 65%). Several illumination and analysis strategies using the XiSpec gave un-physiological results (e.g. negative S02 ). XiSpec with green LED illumination gave the expected change in /RBC , while the dynamics in S02 were less than those for EPOS. These results may be explained by the calculation of modulation using an illumination and detector setup with a broad spectral transmission bandwidth, with considerable variation in μa of included chromophores. Approaches for either reducing the effective bandwidth of the XiSpec filters or by including their characteristic in a light transport model for SFDI modulation, are proposed.

On-Line Modal State Monitoring of Slowly Time-Varying Structures

NASA Technical Reports Server (NTRS)

Johnson, Erik A.; Bergman, Lawrence A.; Voulgaris, Petros G.

1997-01-01

Monitoring the dynamic response of structures is often performed for a variety of reasons. These reasons include condition-based maintenance, health monitoring, performance improvements, and control. In many cases the data analysis that is performed is part of a repetitive decision-making process, and in these cases the development of effective on-line monitoring schemes help to speed the decision-making process and reduce the risk of erroneous decisions. This report investigates the use of spatial modal filters for tracking the dynamics of slowly time-varying linear structures. The report includes an overview of modal filter theory followed by an overview of several structural system identification methods. Included in this discussion and comparison are H-infinity, eigensystem realization, and several time-domain least squares approaches. Finally, a two-stage adaptive on-line monitoring scheme is developed and evaluated.

Spatial-Heterodyne Interferometry For Reflection And Transm Ission (Shirt) Measurements

DOEpatents

Hanson, Gregory R [Clinton, TN; Bingham, Philip R [Knoxville, TN; Tobin, Ken W [Harriman, TN

2006-02-14

Systems and methods are described for spatial-heterodyne interferometry for reflection and transmission (SHIRT) measurements. A method includes digitally recording a first spatially-heterodyned hologram using a first reference beam and a first object beam; digitally recording a second spatially-heterodyned hologram using a second reference beam and a second object beam; Fourier analyzing the digitally recorded first spatially-heterodyned hologram to define a first analyzed image; Fourier analyzing the digitally recorded second spatially-heterodyned hologram to define a second analyzed image; digitally filtering the first analyzed image to define a first result; and digitally filtering the second analyzed image to define a second result; performing a first inverse Fourier transform on the first result, and performing a second inverse Fourier transform on the second result. The first object beam is transmitted through an object that is at least partially translucent, and the second object beam is reflected from the object.

Spatial filter system as an optical relay line

DOEpatents

Hunt, John T.; Renard, Paul A.

1979-01-01

A system consisting of a set of spatial filters that are used to optically relay a laser beam from one position to a downstream position with minimal nonlinear phase distortion and beam intensity variation. The use of the device will result in a reduction of deleterious beam self-focusing and produce a significant increase in neutron yield from the implosion of targets caused by their irradiation with multi-beam glass laser systems.

Repetition Blindness for Natural Images of Objects with Viewpoint Changes

PubMed Central

Buffat, Stéphane; Plantier, Justin; Roumes, Corinne; Lorenceau, Jean

2013-01-01

When stimuli are repeated in a rapid serial visual presentation (RSVP), observers sometimes fail to report the second occurrence of a target. This phenomenon is referred to as “repetition blindness” (RB). We report an RSVP experiment with photographs in which we manipulated object viewpoints between the first and second occurrences of a target (0°, 45°, or 90° changes), and spatial frequency (SF) content. Natural images were spatially filtered to produce low, medium, or high SF stimuli. RB was observed for all filtering conditions. Surprisingly, for full-spectrum (FS) images, RB increased significantly as the viewpoint reached 90°. For filtered images, a similar pattern of results was found for all conditions except for medium SF stimuli. These findings suggest that object recognition in RSVP are subtended by viewpoint-specific representations for all spatial frequencies except medium ones. PMID:23346069

Measurement of subcellular texture by optical Gabor-like filtering with a digital micromirror device

PubMed Central

Pasternack, Robert M.; Qian, Zhen; Zheng, Jing-Yi; Metaxas, Dimitris N.; White, Eileen; Boustany, Nada N.

2010-01-01

We demonstrate an optical Fourier processing method to quantify object texture arising from subcellular feature orientation within unstained living cells. Using a digital micromirror device as a Fourier spatial filter, we measured cellular responses to two-dimensional optical Gabor-like filters optimized to sense orientation of nonspherical particles, such as mitochondria, with a width around 0.45 μm. Our method showed significantly rounder structures within apoptosis-defective cells lacking the proapoptotic mitochondrial effectors Bax and Bak, when compared with Bax/Bak expressing cells functional for apoptosis, consistent with reported differences in mitochondrial shape in these cells. By decoupling spatial frequency resolution from image resolution, this method enables rapid analysis of nonspherical submicrometer scatterers in an under-sampled large field of view and yields spatially localized morphometric parameters that improve the quantitative assessment of biological function. PMID:18830354

Application of LC and LCoS in Multispectral Polarized Scene Projector (MPSP)

NASA Astrophysics Data System (ADS)

Yu, Haiping; Guo, Lei; Wang, Shenggang; Lippert, Jack; Li, Le

2017-02-01

A Multispectral Polarized Scene Projector (MPSP) had been developed in the short-wave infrared (SWIR) regime for the test & evaluation (T&E) of spectro-polarimetric imaging sensors. This MPSP generates multispectral and hyperspectral video images (up to 200 Hz) with 512×512 spatial resolution with active spatial, spectral, and polarization modulation with controlled bandwidth. It projects input SWIR radiant intensity scenes from stored memory with user selectable wavelength and bandwidth, as well as polarization states (six different states) controllable on a pixel level. The spectral contents are implemented by a tunable filter with variable bandpass built based on liquid crystal (LC) material, together with one passive visible and one passive SWIR cholesteric liquid crystal (CLC) notch filters, and one switchable CLC notch filter. The core of the MPSP hardware is the liquid-crystal-on-silicon (LCoS) spatial light modulators (SLMs) for intensity control and polarization modulation.

Small convolution kernels for high-fidelity image restoration

NASA Technical Reports Server (NTRS)

Reichenbach, Stephen E.; Park, Stephen K.

1991-01-01

An algorithm is developed for computing the mean-square-optimal values for small, image-restoration kernels. The algorithm is based on a comprehensive, end-to-end imaging system model that accounts for the important components of the imaging process: the statistics of the scene, the point-spread function of the image-gathering device, sampling effects, noise, and display reconstruction. Subject to constraints on the spatial support of the kernel, the algorithm generates the kernel values that restore the image with maximum fidelity, that is, the kernel minimizes the expected mean-square restoration error. The algorithm is consistent with the derivation of the spatially unconstrained Wiener filter, but leads to a small, spatially constrained kernel that, unlike the unconstrained filter, can be efficiently implemented by convolution. Simulation experiments demonstrate that for a wide range of imaging systems these small kernels can restore images with fidelity comparable to images restored with the unconstrained Wiener filter.

JunoCam's Images of Jupiter

NASA Astrophysics Data System (ADS)

Hansen, C. J.; Ravine, M. A.; Caplinger, M. A.; Orton, G. S.; Ingersoll, A. P.; Jensen, E.; Lipkaman, L.; Krysak, D.; Zimdar, R.; Bolton, S. J.

2016-12-01

JunoCam is a visible imager on the Juno spacecraft in orbit around Jupiter. It is a wide angle camera (58 deg field of view) with 4 color filters: red, green and blue (RGB) and methane at 889 nm, designed for optimal imaging of Jupiter's poles. Juno's elliptical polar orbit will offer unique views of Jupiter's polar regions with a spatial scale of 50 km/pixel. At closest approach the images will have a spatial scale of 3 km/pixel. As a push-frame imager on a rotating spacecraft, JunoCam uses time-delayed integration to take advantage of the spacecraft spin to extend integration time to increase signal. Images of Jupiter's poles reveal a largely uncharted region of Jupiter, as nearly all earlier spacecraft have orbited or flown by in the equatorial plane. Most of the images of Jupiter will be acquired in the +/-2 hours surrounding closest approach. The polar vortex, polar cloud morphology, and winds will be investigated. RGB color images of the aurora will be acquired if detectable. Stereo images and images taken with the methane filter will allow us to estimate cloud-top heights. Images of the cloud-tops will aid in understanding the data collected by other instruments on Juno that probe deeper in the atmosphere. During the two months that Jupiter is too close to the sun for ground-based observers to collect data, JunoCam will take images routinely to monitor large-scale features. Occasional, opportunistic images of the Galilean moons will be acquired.

The impact of seasonal signals on spatio-temporal filtering

NASA Astrophysics Data System (ADS)

Gruszczynski, Maciej; Klos, Anna; Bogusz, Janusz

2016-04-01

Existence of Common Mode Errors (CMEs) in permanent GNSS networks contribute to spatial and temporal correlation in residual time series. Time series from permanently observing GNSS stations of distance less than 2 000 km are similarly influenced by such CME sources as: mismodelling (Earth Orientation Parameters - EOP, satellite orbits or antenna phase center variations) during the process of the reference frame realization, large-scale atmospheric and hydrospheric effects as well as small scale crust deformations. Residuals obtained as a result of detrending and deseasonalising of topocentric GNSS time series arranged epoch-by-epoch form an observation matrix independently for each component (North, East, Up). CME is treated as internal structure of the data. Assuming a uniform temporal function across the network it is possible to filter CME out using PCA (Principal Component Analysis) approach. Some of above described CME sources may be reflected as a wide range of frequencies in GPS residual time series. In order to determine an impact of seasonal signals modeling to existence of spatial correlation in network and consequently the results of CME filtration, we chose two ways of modeling. The first approach was commonly presented by previous authors, who modeled with the Least-Squares Estimation (LSE) only annual and semi-annual oscillations. In the second one the set of residuals was a result of modeling of deterministic part that included fortnightly periods plus up to 9th harmonics of Chandlerian, tropical and draconitic oscillations. Correlation coefficients for residuals in parallel with KMO (Kaiser-Meyer-Olkin) statistic and Bartlett's test of sphericity were determined. For this research we used time series expressed in ITRF2008 provided by JPL (Jet Propulsion Laboratory). GPS processing was made using GIPSY-OASIS software in a PPP (Precise Point Positioning) mode. In order to form GPS station network that meet demands of uniform spatial response to the CME we chose 18 stations located in Central Europe. Created network extends up to 1500 kilometers. The KMO statistic indicate whether a component analysis may be useful for a chosen data set. We obtained KMO statistic value of 0.87 and 0.62 for residuals of Up component after first and second approaches were applied, what means that both residuals share common errors. Bartlett's test of sphericity analysis met a requirement that in both cases there are correlations in residuals. Another important results are the eigenvalues expressed as a percentage of the total variance explained by the first few components in PCA. For North, East and Up component we obtain respectively 68%, 75%, 65% and 47%, 54%, 52% after first and second approaches were applied. The results of CME filtration using PCA approach performed on both residual time series influence directly the uncertainty of the velocity of permanent stations. In our case spatial filtering reduces the uncertainty of velocity from 0.5 to 0.8 mm for horizontal components and from 0.6 to 0.9 mm on average for Up component when annual and semi-annual signals were assumed. Nevertheless, while second approach to the deterministic part modelling was used, deterioration of velocity uncertainty was noticed only for Up component, probably due to much higher autocorrelation in the time series when comparing to horizontal components.

Broadband spatial optical filtering with a volume Bragg grating and a blazed grating pair

NASA Astrophysics Data System (ADS)

Chen, Guanjin; Sun, Xiaojie; Yuan, Xiao; Zhang, Guiju

2017-10-01

A broadband spatial optical filtering system is presented in this paper, which is composed of a Volume Bragg Grating (VBG) and a blazed grating pair. The diffraction efficiency and filtering properties are calculated and simulated by using Fourier diffraction analysis and Coupled Wave Theory. A blazed grating pair and VBG structures are designed and optimized in our simulation. The diffraction efficiency of filtering system shows more than 77.2% during the wavelength period from 953nm to 1153nm, especially 84.1% at the center wavelength. The beam quality is described with near-field modulation (M) and contrast ratio (C). The M of filtering beam are 1.44, 1.49 and 1.55, respectively and the C of filtering beam are 10.1%, 10.2% and 10.5% , respectively and the beam intensity distribution is great improved. The cut-off frequencies of three filtering systems are 1.57mm-1 , 2.06 mm-1 and 2.38 mm-1 , respectively from power spectral density (PSD) curve. It's clear that the cut-off frequency of filtering system is closely related to the angular selectivity of VBG, and the value of cut-off frequency is decided by VBG's Half Width at First Zero (HWFZ) and center wavelength.

Rule-based topology system for spatial databases to validate complex geographic datasets

NASA Astrophysics Data System (ADS)

Martinez-Llario, J.; Coll, E.; Núñez-Andrés, M.; Femenia-Ribera, C.

2017-06-01

A rule-based topology software system providing a highly flexible and fast procedure to enforce integrity in spatial relationships among datasets is presented. This improved topology rule system is built over the spatial extension Jaspa. Both projects are open source, freely available software developed by the corresponding author of this paper. Currently, there is no spatial DBMS that implements a rule-based topology engine (considering that the topology rules are designed and performed in the spatial backend). If the topology rules are applied in the frontend (as in many GIS desktop programs), ArcGIS is the most advanced solution. The system presented in this paper has several major advantages over the ArcGIS approach: it can be extended with new topology rules, it has a much wider set of rules, and it can mix feature attributes with topology rules as filters. In addition, the topology rule system can work with various DBMSs, including PostgreSQL, H2 or Oracle, and the logic is performed in the spatial backend. The proposed topology system allows users to check the complex spatial relationships among features (from one or several spatial layers) that require some complex cartographic datasets, such as the data specifications proposed by INSPIRE in Europe and the Land Administration Domain Model (LADM) for Cadastral data.

Optimal spatio-temporal filter for the reduction of crosstalk in surface electromyogram

NASA Astrophysics Data System (ADS)

Mesin, Luca

2018-02-01

Objective. Crosstalk can pose limitations to the applications of surface electromyogram (EMG). Its reduction can help in the identification of the activity of specific muscles. The selectivity of different spatial filters was tested in the literature both in simulations and experiments: their performances are affected by many factors (e.g. anatomy, conduction properties of the tissues and dimension/location of the electrodes); moreover, they reduce crosstalk by decreasing the detection volume, recording data that represent only the activity of a small portion of the muscle of interest. In this study, an alternative idea is proposed, based on a spatio-temporal filter. Approach. An adaptive method is applied, which filters both in time and among different channels, providing a signal that maximally preserves the energy of the EMG of interest and discards that of nearby muscles (increasing the signal to crosstalk ratio, SCR). Main results. Tests with simulations and experimental data show an average increase of the SCR of about 2 dB with respect to the single or double differential data processed by the filter. This allows to reduce the bias induced by crosstalk in conduction velocity and force estimation. Significance. The method can be applied to few channels, so that it is useful in applicative studies (e.g. clinics, gate analysis, rehabilitation protocols with EMG biofeedback and prosthesis control) where limited and not selective information is usually available.

Recognition memory for low- and high-frequency-filtered emotional faces: Low spatial frequencies drive emotional memory enhancement, whereas high spatial frequencies drive the emotion-induced recognition bias.

PubMed

Rohr, Michaela; Tröger, Johannes; Michely, Nils; Uhde, Alarith; Wentura, Dirk

2017-07-01

This article deals with two well-documented phenomena regarding emotional stimuli: emotional memory enhancement-that is, better long-term memory for emotional than for neutral stimuli-and the emotion-induced recognition bias-that is, a more liberal response criterion for emotional than for neutral stimuli. Studies on visual emotion perception and attention suggest that emotion-related processes can be modulated by means of spatial-frequency filtering of the presented emotional stimuli. Specifically, low spatial frequencies are assumed to play a primary role for the influence of emotion on attention and judgment. Given this theoretical background, we investigated whether spatial-frequency filtering also impacts (1) the memory advantage for emotional faces and (2) the emotion-induced recognition bias, in a series of old/new recognition experiments. Participants completed incidental-learning tasks with high- (HSF) and low- (LSF) spatial-frequency-filtered emotional and neutral faces. The results of the surprise recognition tests showed a clear memory advantage for emotional stimuli. Most importantly, the emotional memory enhancement was significantly larger for face images containing only low-frequency information (LSF faces) than for HSF faces across all experiments, suggesting that LSF information plays a critical role in this effect, whereas the emotion-induced recognition bias was found only for HSF stimuli. We discuss our findings in terms of both the traditional account of different processing pathways for HSF and LSF information and a stimulus features account. The double dissociation in the results favors the latter account-that is, an explanation in terms of differences in the characteristics of HSF and LSF stimuli.

Spatial and temporal skin blood volume and saturation estimation using a multispectral snapshot imaging camera

NASA Astrophysics Data System (ADS)

Ewerlöf, Maria; Larsson, Marcus; Salerud, E. Göran

2017-02-01

Hyperspectral imaging (HSI) can estimate the spatial distribution of skin blood oxygenation, using visible to near-infrared light. HSI oximeters often use a liquid-crystal tunable filter, an acousto-optic tunable filter or mechanically adjustable filter wheels, which has too long response/switching times to monitor tissue hemodynamics. This work aims to evaluate a multispectral snapshot imaging system to estimate skin blood volume and oxygen saturation with high temporal and spatial resolution. We use a snapshot imager, the xiSpec camera (MQ022HG-IM-SM4X4-VIS, XIMEA), having 16 wavelength-specific Fabry-Perot filters overlaid on the custom CMOS-chip. The spectral distribution of the bands is however substantially overlapping, which needs to be taken into account for an accurate analysis. An inverse Monte Carlo analysis is performed using a two-layered skin tissue model, defined by epidermal thickness, haemoglobin concentration and oxygen saturation, melanin concentration and spectrally dependent reduced-scattering coefficient, all parameters relevant for human skin. The analysis takes into account the spectral detector response of the xiSpec camera. At each spatial location in the field-of-view, we compare the simulated output to the detected diffusively backscattered spectra to find the best fit. The imager is evaluated for spatial and temporal variations during arterial and venous occlusion protocols applied to the forearm. Estimated blood volume changes and oxygenation maps at 512x272 pixels show values that are comparable to reference measurements performed in contact with the skin tissue. We conclude that the snapshot xiSpec camera, paired with an inverse Monte Carlo algorithm, permits us to use this sensor for spatial and temporal measurement of varying physiological parameters, such as skin tissue blood volume and oxygenation.

Filtering analysis of a direct numerical simulation of the turbulent Rayleigh-Benard problem

NASA Technical Reports Server (NTRS)

Eidson, T. M.; Hussaini, M. Y.; Zang, T. A.

1990-01-01

A filtering analysis of a turbulent flow was developed which provides details of the path of the kinetic energy of the flow from its creation via thermal production to its dissipation. A low-pass spatial filter is used to split the velocity and the temperature field into a filtered component (composed mainly of scales larger than a specific size, nominally the filter width) and a fluctuation component (scales smaller than a specific size). Variables derived from these fields can fall into one of the above two ranges or be composed of a mixture of scales dominated by scales near the specific size. The filter is used to split the kinetic energy equation into three equations corresponding to the three scale ranges described above. The data from a direct simulation of the Rayleigh-Benard problem for conditions where the flow is turbulent are used to calculate the individual terms in the three kinetic energy equations. This is done for a range of filter widths. These results are used to study the spatial location and the scale range of the thermal energy production, the cascading of kinetic energy, the diffusion of kinetic energy, and the energy dissipation. These results are used to evaluate two subgrid models typically used in large-eddy simulations of turbulence. Subgrid models attempt to model the energy below the filter width that is removed by a low-pass filter.

Scale-Dependence of Processes Structuring Dung Beetle Metacommunities Using Functional Diversity and Community Deconstruction Approaches

PubMed Central

da Silva, Pedro Giovâni; Hernández, Malva Isabel Medina

2015-01-01

Community structure is driven by mechanisms linked to environmental, spatial and temporal processes, which have been successfully addressed using metacommunity framework. The relative importance of processes shaping community structure can be identified using several different approaches. Two approaches that are increasingly being used are functional diversity and community deconstruction. Functional diversity is measured using various indices that incorporate distinct community attributes. Community deconstruction is a way to disentangle species responses to ecological processes by grouping species with similar traits. We used these two approaches to determine whether they are improvements over traditional measures (e.g., species composition, abundance, biomass) for identification of the main processes driving dung beetle (Scarabaeinae) community structure in a fragmented mainland-island landscape in southern Brazilian Atlantic Forest. We sampled five sites in each of four large forest areas, two on the mainland and two on the island. Sampling was performed in 2012 and 2013. We collected abundance and biomass data from 100 sampling points distributed over 20 sampling sites. We studied environmental, spatial and temporal effects on dung beetle community across three spatial scales, i.e., between sites, between areas and mainland-island. The γ-diversity based on species abundance was mainly attributed to β-diversity as a consequence of the increase in mean α- and β-diversity between areas. Variation partitioning on abundance, biomass and functional diversity showed scale-dependence of processes structuring dung beetle metacommunities. We identified two major groups of responses among 17 functional groups. In general, environmental filters were important at both local and regional scales. Spatial factors were important at the intermediate scale. Our study supports the notion of scale-dependence of environmental, spatial and temporal processes in the distribution and functional organization of Scarabaeinae beetles. We conclude that functional diversity may be used as a complementary approach to traditional measures, and that community deconstruction allows sufficient disentangling of responses of different trait-based groups. PMID:25822150

GIFTed Demons: deformable image registration with local structure-preserving regularization using supervoxels for liver applications

PubMed Central

Gleeson, Fergus V.; Brady, Michael; Schnabel, Julia A.

2018-01-01

Abstract. Deformable image registration, a key component of motion correction in medical imaging, needs to be efficient and provides plausible spatial transformations that reliably approximate biological aspects of complex human organ motion. Standard approaches, such as Demons registration, mostly use Gaussian regularization for organ motion, which, though computationally efficient, rule out their application to intrinsically more complex organ motions, such as sliding interfaces. We propose regularization of motion based on supervoxels, which provides an integrated discontinuity preserving prior for motions, such as sliding. More precisely, we replace Gaussian smoothing by fast, structure-preserving, guided filtering to provide efficient, locally adaptive regularization of the estimated displacement field. We illustrate the approach by applying it to estimate sliding motions at lung and liver interfaces on challenging four-dimensional computed tomography (CT) and dynamic contrast-enhanced magnetic resonance imaging datasets. The results show that guided filter-based regularization improves the accuracy of lung and liver motion correction as compared to Gaussian smoothing. Furthermore, our framework achieves state-of-the-art results on a publicly available CT liver dataset. PMID:29662918

GIFTed Demons: deformable image registration with local structure-preserving regularization using supervoxels for liver applications.

PubMed

Papież, Bartłomiej W; Franklin, James M; Heinrich, Mattias P; Gleeson, Fergus V; Brady, Michael; Schnabel, Julia A

2018-04-01

Deformable image registration, a key component of motion correction in medical imaging, needs to be efficient and provides plausible spatial transformations that reliably approximate biological aspects of complex human organ motion. Standard approaches, such as Demons registration, mostly use Gaussian regularization for organ motion, which, though computationally efficient, rule out their application to intrinsically more complex organ motions, such as sliding interfaces. We propose regularization of motion based on supervoxels, which provides an integrated discontinuity preserving prior for motions, such as sliding. More precisely, we replace Gaussian smoothing by fast, structure-preserving, guided filtering to provide efficient, locally adaptive regularization of the estimated displacement field. We illustrate the approach by applying it to estimate sliding motions at lung and liver interfaces on challenging four-dimensional computed tomography (CT) and dynamic contrast-enhanced magnetic resonance imaging datasets. The results show that guided filter-based regularization improves the accuracy of lung and liver motion correction as compared to Gaussian smoothing. Furthermore, our framework achieves state-of-the-art results on a publicly available CT liver dataset.

Rhythmic entrainment source separation: Optimizing analyses of neural responses to rhythmic sensory stimulation.

PubMed

Cohen, Michael X; Gulbinaite, Rasa

2017-02-15

Steady-state evoked potentials (SSEPs) are rhythmic brain responses to rhythmic sensory stimulation, and are often used to study perceptual and attentional processes. We present a data analysis method for maximizing the signal-to-noise ratio of the narrow-band steady-state response in the frequency and time-frequency domains. The method, termed rhythmic entrainment source separation (RESS), is based on denoising source separation approaches that take advantage of the simultaneous but differential projection of neural activity to multiple electrodes or sensors. Our approach is a combination and extension of existing multivariate source separation methods. We demonstrate that RESS performs well on both simulated and empirical data, and outperforms conventional SSEP analysis methods based on selecting electrodes with the strongest SSEP response, as well as several other linear spatial filters. We also discuss the potential confound of overfitting, whereby the filter captures noise in absence of a signal. Matlab scripts are available to replicate and extend our simulations and methods. We conclude with some practical advice for optimizing SSEP data analyses and interpreting the results. Copyright © 2016 Elsevier Inc. All rights reserved.

State-of-charge estimation in lithium-ion batteries: A particle filter approach

NASA Astrophysics Data System (ADS)

Tulsyan, Aditya; Tsai, Yiting; Gopaluni, R. Bhushan; Braatz, Richard D.

2016-11-01

The dynamics of lithium-ion batteries are complex and are often approximated by models consisting of partial differential equations (PDEs) relating the internal ionic concentrations and potentials. The Pseudo two-dimensional model (P2D) is one model that performs sufficiently accurately under various operating conditions and battery chemistries. Despite its widespread use for prediction, this model is too complex for standard estimation and control applications. This article presents an original algorithm for state-of-charge estimation using the P2D model. Partial differential equations are discretized using implicit stable algorithms and reformulated into a nonlinear state-space model. This discrete, high-dimensional model (consisting of tens to hundreds of states) contains implicit, nonlinear algebraic equations. The uncertainty in the model is characterized by additive Gaussian noise. By exploiting the special structure of the pseudo two-dimensional model, a novel particle filter algorithm that sweeps in time and spatial coordinates independently is developed. This algorithm circumvents the degeneracy problems associated with high-dimensional state estimation and avoids the repetitive solution of implicit equations by defining a 'tether' particle. The approach is illustrated through extensive simulations.

A micropixelated ion-imaging detector for mass resolution enhancement of a QMS instrument.

PubMed

Syed, Sarfaraz U A H; Eijkel, Gert B; Maher, Simon; Kistemaker, Piet; Taylor, Stephen; Heeren, Ron M A

2015-03-01

An in-vacuum position-sensitive micropixelated detector (Timepix) is used to investigate the time-dependent spatial distribution of different charge state (and hence different mass-to-charge (m/z)) ions exiting an electrospray ionization (ESI)-based quadrupole mass spectrometer (QMS) instrument. Ion images obtained from the Timepix detector provide a detailed insight into the positions of stable and unstable ions of the mass peak as they exit the QMS. With the help of image processing algorithms and by selecting areas on the ion images where more stable ions impact the detector, an improvement in mass resolution by a factor of 5 was obtained for certain operating conditions. Moreover, our experimental approach of mass resolution enhancement was confirmed by in-house-developed novel QMS instrument simulation software. Utilizing the imaging-based mass resolution enhancement approach, the software predicts instrument mass resolution of ∼1,0000 for a single-filter QMS instrument with a 210-mm long mass filter and a low operating frequency (880 kHz) of the radio frequency (RF) voltage.

Rapid mapping of polarization switching through complete information acquisition

DOE PAGES

Somnath, Suhas; Belianinov, Alex; Kalinin, Sergei V.; ...

2016-12-02

Polarization switching in ferroelectric and multiferroic materials underpins a broad range of current and emergent applications, ranging from random access memories to field-effect transistors, and tunnelling devices. Switching in these materials is exquisitely sensitive to local defects and microstructure on the nanometre scale, necessitating spatially resolved high-resolution studies of these phenomena. Classical piezoresponse force microscopy and spectroscopy, although providing necessary spatial resolution, are fundamentally limited in data acquisition rates and energy resolution. This limitation stems from their two-tiered measurement protocol that combines slow (~1 s) switching and fast (~10 kHz–1 MHz) detection waveforms. Here we develop an approach for rapidmore » probing of ferroelectric switching using direct strain detection of material response to probe bias. This approach, facilitated by high-sensitivity electronics and adaptive filtering, enables spectroscopic imaging at a rate 3,504 times faster the current state of the art, achieving high-veracity imaging of polarization dynamics in complex microstructures.« less

Rapid mapping of polarization switching through complete information acquisition

PubMed Central

Somnath, Suhas; Belianinov, Alex; Kalinin, Sergei V.; Jesse, Stephen

2016-01-01

Polarization switching in ferroelectric and multiferroic materials underpins a broad range of current and emergent applications, ranging from random access memories to field-effect transistors, and tunnelling devices. Switching in these materials is exquisitely sensitive to local defects and microstructure on the nanometre scale, necessitating spatially resolved high-resolution studies of these phenomena. Classical piezoresponse force microscopy and spectroscopy, although providing necessary spatial resolution, are fundamentally limited in data acquisition rates and energy resolution. This limitation stems from their two-tiered measurement protocol that combines slow (∼1 s) switching and fast (∼10 kHz–1 MHz) detection waveforms. Here we develop an approach for rapid probing of ferroelectric switching using direct strain detection of material response to probe bias. This approach, facilitated by high-sensitivity electronics and adaptive filtering, enables spectroscopic imaging at a rate 3,504 times faster the current state of the art, achieving high-veracity imaging of polarization dynamics in complex microstructures. PMID:27910941

Confocal filtering in cathodoluminescence microscopy of nanostructures

NASA Astrophysics Data System (ADS)

Narváez, Angela C.; Weppelman, I. Gerward C.; Moerland, Robert J.; Hoogenboom, Jacob P.; Kruit, Pieter

2014-06-01

Cathodoluminescence (CL) microscopy allows optical characterization of nanostructures at high spatial resolution. At the nanoscale, a main challenge of the technique is related to the background CL generated within the sample substrate. Here, we implement confocal detection of the CL signal to minimize the background contribution to the measurement. Nano-phosphors were used as point sources to evaluate the filtering capabilities of our confocal CL system, obtaining an axial intensity profile with 2.7 μm full width at half maximum for the central peak, in good correspondence with theoretical expectations. Considering the electron interaction volume, we found that the confocal filter becomes effective for electron energies above 20 keV, when using a 25 μm pinhole (0.86 Airy units). To illustrate our approach, we present confocal CL imaging of gold nanowires and triangular shaped plates deposited on an indium-tin oxide covered glass substrate, comparing the images with those obtained in standard unfiltered CL detection. The results show that confocal CL microscopy is a valuable tool for the investigation of nanostructures on highly cathodoluminescent substrates, widely used in biological and optical applications.

Phase unwrapping algorithm using polynomial phase approximation and linear Kalman filter.

PubMed

Kulkarni, Rishikesh; Rastogi, Pramod

2018-02-01

A noise-robust phase unwrapping algorithm is proposed based on state space analysis and polynomial phase approximation using wrapped phase measurement. The true phase is approximated as a two-dimensional first order polynomial function within a small sized window around each pixel. The estimates of polynomial coefficients provide the measurement of phase and local fringe frequencies. A state space representation of spatial phase evolution and the wrapped phase measurement is considered with the state vector consisting of polynomial coefficients as its elements. Instead of using the traditional nonlinear Kalman filter for the purpose of state estimation, we propose to use the linear Kalman filter operating directly with the wrapped phase measurement. The adaptive window width is selected at each pixel based on the local fringe density to strike a balance between the computation time and the noise robustness. In order to retrieve the unwrapped phase, either a line-scanning approach or a quality guided strategy of pixel selection is used depending on the underlying continuous or discontinuous phase distribution, respectively. Simulation and experimental results are provided to demonstrate the applicability of the proposed method.

Enhancement of the Comb Filtering Selectivity Using Iterative Moving Average for Periodic Waveform and Harmonic Elimination

PubMed Central

Wu, Yan; Aarts, Ronald M.

2018-01-01

A recurring problem regarding the use of conventional comb filter approaches for elimination of periodic waveforms is the degree of selectivity achieved by the filtering process. Some applications, such as the gradient artefact correction in EEG recordings during coregistered EEG-fMRI, require a highly selective comb filtering that provides effective attenuation in the stopbands and gain close to unity in the pass-bands. In this paper, we present a novel comb filtering implementation whereby the iterative filtering application of FIR moving average-based approaches is exploited in order to enhance the comb filtering selectivity. Our results indicate that the proposed approach can be used to effectively approximate the FIR moving average filter characteristics to those of an ideal filter. A cascaded implementation using the proposed approach shows to further increase the attenuation in the filter stopbands. Moreover, broadening of the bandwidth of the comb filtering stopbands around −3 dB according to the fundamental frequency of the stopband can be achieved by the novel method, which constitutes an important characteristic to account for broadening of the harmonic gradient artefact spectral lines. In parallel, the proposed filtering implementation can also be used to design a novel notch filtering approach with enhanced selectivity as well. PMID:29599955

Real-time optical correlator using computer-generated holographic filter on a liquid crystal light valve

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Yu, Jeffrey

1990-01-01

Limitations associated with the binary phase-only filter often used in optical correlators are presently circumvented in the writing of complex-valued data on a gray-scale spatial light modulator through the use of a computer-generated hologram (CGH) algorithm. The CGH encodes complex-valued data into nonnegative real CGH data in such a way that it may be encoded in any of the available gray-scale spatial light modulators. A CdS liquid-crystal light valve is used for the complex-valued CGH encoding; computer simulations and experimental results are compared, and the use of such a CGH filter as the synapse hologram in a holographic optical neural net is discussed.

Extracting the regional common-mode component of GPS station position time series from dense continuous network

NASA Astrophysics Data System (ADS)

Tian, Yunfeng; Shen, Zheng-Kang

2016-02-01

We develop a spatial filtering method to remove random noise and extract the spatially correlated transients (i.e., common-mode component (CMC)) that deviate from zero mean over the span of detrended position time series of a continuous Global Positioning System (CGPS) network. The technique utilizes a weighting scheme that incorporates two factors—distances between neighboring sites and their correlations of long-term residual position time series. We use a grid search algorithm to find the optimal thresholds for deriving the CMC that minimizes the root-mean-square (RMS) of the filtered residual position time series. Comparing to the principal component analysis technique, our method achieves better (>13% on average) reduction of residual position scatters for the CGPS stations in western North America, eliminating regional transients of all spatial scales. It also has advantages in data manipulation: less intervention and applicable to a dense network of any spatial extent. Our method can also be used to detect CMC irrespective of its origins (i.e., tectonic or nontectonic), if such signals are of particular interests for further study. By varying the filtering distance range, the long-range CMC related to atmospheric disturbance can be filtered out, uncovering CMC associated with transient tectonic deformation. A correlation-based clustering algorithm is adopted to identify stations cluster that share the common regional transient characteristics.

Dual-domain point diffraction interferometer

DOEpatents

Naulleau, Patrick P.; Goldberg, Kenneth Alan

2000-01-01

A hybrid spatial/temporal-domain point diffraction interferometer (referred to as the dual-domain PS/PDI) that is capable of suppressing the scattered-reference-light noise that hinders the conventional PS/PDI is provided. The dual-domain PS/PDI combines the separate noise-suppression capabilities of the widely-used phase-shifting and Fourier-transform fringe pattern analysis methods. The dual-domain PS/PDI relies on both a more restrictive implementation of the image plane PS/PDI mask and a new analysis method to be applied to the interferograms generated and recorded by the modified PS/PDI. The more restrictive PS/PDI mask guarantees the elimination of spatial-frequency crosstalk between the signal and the scattered-light noise arising from scattered-reference-light interfering with the test beam. The new dual-domain analysis method is then used to eliminate scattered-light noise arising from both the scattered-reference-light interfering with the test beam and the scattered-reference-light interfering with the "true" pinhole-diffracted reference light. The dual-domain analysis method has also been demonstrated to provide performance enhancement when using the non-optimized standard PS/PDI design. The dual-domain PS/PDI is essentially a three-tiered filtering system composed of lowpass spatial-filtering the test-beam electric field using the more restrictive PS/PDI mask, bandpass spatial-filtering the individual interferogram irradiance frames making up the phase-shifting series, and bandpass temporal-filtering the phase-shifting series as a whole.

Achromatic self-referencing interferometer

DOEpatents

Feldman, Mark

1994-01-01

A self-referencing Mach-Zehnder interferometer for accurately measuring laser wavefronts over a broad wavelength range (for example, 600 nm to 900 nm). The apparatus directs a reference portion of an input beam to a reference arm and a measurement portion of the input beam to a measurement arm, recombines the output beams from the reference and measurement arms, and registers the resulting interference pattern ("first" interferogram) at a first detector. Optionally, subportions of the measurement portion are diverted to second and third detectors, which respectively register intensity and interferogram signals which can be processed to reduce the first interferogram's sensitivity to input noise. The reference arm includes a spatial filter producing a high quality spherical beam from the reference portion, a tilted wedge plate compensating for off-axis aberrations in the spatial filter output, and mirror collimating the radiation transmitted through the tilted wedge plate. The apparatus includes a thermally and mechanically stable baseplate which supports all reference arm optics, or at least the spatial filter, tilted wedge plate, and the collimator. The tilted wedge plate is mounted adjustably with respect to the spatial filter and collimator, so that it can be maintained in an orientation in which it does not introduce significant wave front errors into the beam propagating through the reference arm. The apparatus is polarization insensitive and has an equal path length configuration enabling measurement of radiation from broadband as well as closely spaced laser line sources.

Picking Deep Filter Responses for Fine-Grained Image Recognition (Open Access Author’s Manuscript)

DTIC Science & Technology

2016-12-16

stages. Our method explores a unified framework based on two steps of deep filter response picking. The first picking step is to find distinctive... filters which respond to specific patterns significantly and consistently, and learn a set of part detectors via iteratively alternating between new...positive sample mining and part model retraining. The second picking step is to pool deep filter responses via spatially weighted combination of Fisher

Virtual strain gage size study

DOE PAGES

Reu, Phillip L.

2015-09-22

DIC is a non-linear low-pass spatial filtering operation; whether we consider the effect of the subset and shape function, the strain window used in the strain calculation, of other post-processing of the results, each decision will impact the spatial resolution, of the measurement. More fundamentally, the speckle size limits, the spatial resolution by dictating the smallest possible subset. After this decision the processing settings are controlled by the allowable noise level balanced by possible bias errors created by the data filtering. This article describes a process to determine optimum DIC software settings to determine if the peak displacements or strainsmore » are being found.« less

Multidimensional deconvolution of optical microscope and ultrasound imaging using adaptive least-mean-square (LMS) inverse filtering

NASA Astrophysics Data System (ADS)

Sapia, Mark Angelo

2000-11-01

Three-dimensional microscope images typically suffer from reduced resolution due to the effects of convolution, optical aberrations and out-of-focus blurring. Two- dimensional ultrasound images are also degraded by convolutional bluffing and various sources of noise. Speckle noise is a major problem in ultrasound images. In microscopy and ultrasound, various methods of digital filtering have been used to improve image quality. Several methods of deconvolution filtering have been used to improve resolution by reversing the convolutional effects, many of which are based on regularization techniques and non-linear constraints. The technique discussed here is a unique linear filter for deconvolving 3D fluorescence microscopy or 2D ultrasound images. The process is to solve for the filter completely in the spatial-domain using an adaptive algorithm to converge to an optimum solution for de-blurring and resolution improvement. There are two key advantages of using an adaptive solution: (1)it efficiently solves for the filter coefficients by taking into account all sources of noise and degraded resolution at the same time, and (2)achieves near-perfect convergence to the ideal linear deconvolution filter. This linear adaptive technique has other advantages such as avoiding artifacts of frequency-domain transformations and concurrent adaptation to suppress noise. Ultimately, this approach results in better signal-to-noise characteristics with virtually no edge-ringing. Many researchers have not adopted linear techniques because of poor convergence, noise instability and negative valued data in the results. The methods presented here overcome many of these well-documented disadvantages and provide results that clearly out-perform other linear methods and may also out-perform regularization and constrained algorithms. In particular, the adaptive solution is most responsible for overcoming the poor performance associated with linear techniques. This linear adaptive approach to deconvolution is demonstrated with results of restoring blurred phantoms for both microscopy and ultrasound and restoring 3D microscope images of biological cells and 2D ultrasound images of human subjects (courtesy of General Electric and Diasonics, Inc.).

Event-Related Potential Responses to Task Switching Are Sensitive to Choice of Spatial Filter

PubMed Central

Wong, Aaron S. W.; Cooper, Patrick S.; Conley, Alexander C.; McKewen, Montana; Fulham, W. Ross; Michie, Patricia T.; Karayanidis, Frini

2018-01-01

Event-related potential (ERP) studies using the task-switching paradigm show that multiple ERP components are modulated by activation of proactive control processes involved in preparing to repeat or switch task and reactive control processes involved in implementation of the current or new task. Our understanding of the functional significance of these ERP components has been hampered by variability in their robustness, as well as their temporal and scalp distribution across studies. The aim of this study is to examine the effect of choice of reference electrode or spatial filter on the number, timing and scalp distribution of ERP elicited during task-switching. We compared four configurations, including the two most common (i.e., average mastoid reference and common average reference) and two novel ones that aim to reduce volume conduction (i.e., reference electrode standardization technique (REST) and surface Laplacian) on mixing cost and switch cost effects in cue-locked and target-locked ERP waveforms in 201 healthy participants. All four spatial filters showed the same well-characterized ERP components that are typically seen in task-switching paradigms: the cue-locked switch positivity and target-locked N2/P3 effect. However, both the number of ERP effects associated with mixing and switch cost, and their temporal and spatial resolution were greater with the surface Laplacian transformation which revealed rapid temporal adjustments that were not identifiable with other spatial filters. We conclude that the surface Laplacian transformation may be more suited to characterize EEG signatures of complex spatiotemporal networks involved in cognitive control. PMID:29568260

A graph signal filtering-based approach for detection of different edge types on airborne lidar data

NASA Astrophysics Data System (ADS)

Bayram, Eda; Vural, Elif; Alatan, Aydin

2017-10-01

Airborne Laser Scanning is a well-known remote sensing technology, which provides a dense and highly accurate, yet unorganized point cloud of earth surface. During the last decade, extracting information from the data generated by airborne LiDAR systems has been addressed by many studies in geo-spatial analysis and urban monitoring applications. However, the processing of LiDAR point clouds is challenging due to their irregular structure and 3D geometry. In this study, we propose a novel framework for the detection of the boundaries of an object or scene captured by LiDAR. Our approach is motivated by edge detection techniques in vision research and it is established on graph signal filtering which is an exciting and promising field of signal processing for irregular data types. Due to the convenient applicability of graph signal processing tools on unstructured point clouds, we achieve the detection of the edge points directly on 3D data by using a graph representation that is constructed exclusively to answer the requirements of the application. Moreover, considering the elevation data as the (graph) signal, we leverage aerial characteristic of the airborne LiDAR data. The proposed method can be employed both for discovering the jump edges on a segmentation problem and for exploring the crease edges on a LiDAR object on a reconstruction/modeling problem, by only adjusting the filter characteristics.

Atomic resolution elemental mapping using energy-filtered imaging scanning transmission electron microscopy with chromatic aberration correction.

PubMed

Krause, F F; Rosenauer, A; Barthel, J; Mayer, J; Urban, K; Dunin-Borkowski, R E; Brown, H G; Forbes, B D; Allen, L J

2017-10-01

This paper addresses a novel approach to atomic resolution elemental mapping, demonstrating a method that produces elemental maps with a similar resolution to the established method of electron energy-loss spectroscopy in scanning transmission electron microscopy. Dubbed energy-filtered imaging scanning transmission electron microscopy (EFISTEM) this mode of imaging is, by the quantum mechanical principle of reciprocity, equivalent to tilting the probe in energy-filtered transmission electron microscopy (EFTEM) through a cone and incoherently averaging the results. In this paper we present a proof-of-principle EFISTEM experimental study on strontium titanate. The present approach, made possible by chromatic aberration correction, has the advantage that it provides elemental maps which are immune to spatial incoherence in the electron source, coherent aberrations in the probe-forming lens and probe jitter. The veracity of the experiment is supported by quantum mechanical image simulations, which provide an insight into the image-forming process. Elemental maps obtained in EFTEM suffer from the effect known as preservation of elastic contrast, which, for example, can lead to a given atomic species appearing to be in atomic columns where it is not to be found. EFISTEM very substantially reduces the preservation of elastic contrast and yields images which show stability of contrast with changing thickness. The experimental application is demonstrated in a proof-of-principle study on strontium titanate. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling, Monitoring and Fault Diagnosis of Spacecraft Air Contaminants

NASA Technical Reports Server (NTRS)

Ramirez, W. Fred; Skliar, Mikhail; Narayan, Anand; Morgenthaler, George W.; Smith, Gerald J.

1996-01-01

Progress and results in the development of an integrated air quality modeling, monitoring, fault detection, and isolation system are presented. The focus was on development of distributed models of the air contaminants transport, the study of air quality monitoring techniques based on the model of transport process and on-line contaminant concentration measurements, and sensor placement. Different approaches to the modeling of spacecraft air contamination are discussed, and a three-dimensional distributed parameter air contaminant dispersion model applicable to both laminar and turbulent transport is proposed. A two-dimensional approximation of a full scale transport model is also proposed based on the spatial averaging of the three dimensional model over the least important space coordinate. A computer implementation of the transport model is considered and a detailed development of two- and three-dimensional models illustrated by contaminant transport simulation results is presented. The use of a well established Kalman filtering approach is suggested as a method for generating on-line contaminant concentration estimates based on both real time measurements and the model of contaminant transport process. It is shown that high computational requirements of the traditional Kalman filter can render difficult its real-time implementation for high-dimensional transport model and a novel implicit Kalman filtering algorithm is proposed which is shown to lead to an order of magnitude faster computer implementation in the case of air quality monitoring.

Age-related macular degeneration changes the processing of visual scenes in the brain.

PubMed

Ramanoël, Stephen; Chokron, Sylvie; Hera, Ruxandra; Kauffmann, Louise; Chiquet, Christophe; Krainik, Alexandre; Peyrin, Carole

2018-01-01

In age-related macular degeneration (AMD), the processing of fine details in a visual scene, based on a high spatial frequency processing, is impaired, while the processing of global shapes, based on a low spatial frequency processing, is relatively well preserved. The present fMRI study aimed to investigate the residual abilities and functional brain changes of spatial frequency processing in visual scenes in AMD patients. AMD patients and normally sighted elderly participants performed a categorization task using large black and white photographs of scenes (indoors vs. outdoors) filtered in low and high spatial frequencies, and nonfiltered. The study also explored the effect of luminance contrast on the processing of high spatial frequencies. The contrast across scenes was either unmodified or equalized using a root-mean-square contrast normalization in order to increase contrast in high-pass filtered scenes. Performance was lower for high-pass filtered scenes than for low-pass and nonfiltered scenes, for both AMD patients and controls. The deficit for processing high spatial frequencies was more pronounced in AMD patients than in controls and was associated with lower activity for patients than controls not only in the occipital areas dedicated to central and peripheral visual fields but also in a distant cerebral region specialized for scene perception, the parahippocampal place area. Increasing the contrast improved the processing of high spatial frequency content and spurred activation of the occipital cortex for AMD patients. These findings may lead to new perspectives for rehabilitation procedures for AMD patients.

Spatial filtering, color constancy, and the color-changing dress.

PubMed

Dixon, Erica L; Shapiro, Arthur G

2017-03-01

The color-changing dress is a 2015 Internet phenomenon in which the colors in a picture of a dress are reported as blue-black by some observers and white-gold by others. The standard explanation is that observers make different inferences about the lighting (is the dress in shadow or bright yellow light?); based on these inferences, observers make a best guess about the reflectance of the dress. The assumption underlying this explanation is that reflectance is the key to color constancy because reflectance alone remains invariant under changes in lighting conditions. Here, we demonstrate an alternative type of invariance across illumination conditions: An object that appears to vary in color under blue, white, or yellow illumination does not change color in the high spatial frequency region. A first approximation to color constancy can therefore be accomplished by a high-pass filter that retains enough low spatial frequency content so as to not to completely desaturate the object. We demonstrate the implications of this idea on the Rubik's cube illusion; on a shirt placed under white, yellow, and blue illuminants; and on spatially filtered images of the dress. We hypothesize that observer perceptions of the dress's color vary because of individual differences in how the visual system extracts high and low spatial frequency color content from the environment, and we demonstrate cross-group differences in average sensitivity to low spatial frequency patterns.

Delineating high-density areas in spatial Poisson fields from strip-transect sampling using indicator geostatistics: application to unexploded ordnance removal.

PubMed

Saito, Hirotaka; McKenna, Sean A

2007-07-01

An approach for delineating high anomaly density areas within a mixture of two or more spatial Poisson fields based on limited sample data collected along strip transects was developed. All sampled anomalies were transformed to anomaly count data and indicator kriging was used to estimate the probability of exceeding a threshold value derived from the cdf of the background homogeneous Poisson field. The threshold value was determined so that the delineation of high-density areas was optimized. Additionally, a low-pass filter was applied to the transect data to enhance such segmentation. Example calculations were completed using a controlled military model site, in which accurate delineation of clusters of unexploded ordnance (UXO) was required for site cleanup.

Forecasting Flare Activity Using Deep Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Hernandez, T.

2017-12-01

Current operational flare forecasting relies on human morphological analysis of active regions and the persistence of solar flare activity through time (i.e. that the Sun will continue to do what it is doing right now: flaring or remaining calm). In this talk we present the results of applying deep Convolutional Neural Networks (CNNs) to the problem of solar flare forecasting. CNNs operate by training a set of tunable spatial filters that, in combination with neural layer interconnectivity, allow CNNs to automatically identify significant spatial structures predictive for classification and regression problems. We will start by discussing the applicability and success rate of the approach, the advantages it has over non-automated forecasts, and how mining our trained neural network provides a fresh look into the mechanisms behind magnetic energy storage and release.

Integration of adaptive guided filtering, deep feature learning, and edge-detection techniques for hyperspectral image classification

NASA Astrophysics Data System (ADS)

Wan, Xiaoqing; Zhao, Chunhui; Gao, Bing

2017-11-01

The integration of an edge-preserving filtering technique in the classification of a hyperspectral image (HSI) has been proven effective in enhancing classification performance. This paper proposes an ensemble strategy for HSI classification using an edge-preserving filter along with a deep learning model and edge detection. First, an adaptive guided filter is applied to the original HSI to reduce the noise in degraded images and to extract powerful spectral-spatial features. Second, the extracted features are fed as input to a stacked sparse autoencoder to adaptively exploit more invariant and deep feature representations; then, a random forest classifier is applied to fine-tune the entire pretrained network and determine the classification output. Third, a Prewitt compass operator is further performed on the HSI to extract the edges of the first principal component after dimension reduction. Moreover, the regional growth rule is applied to the resulting edge logical image to determine the local region for each unlabeled pixel. Finally, the categories of the corresponding neighborhood samples are determined in the original classification map; then, the major voting mechanism is implemented to generate the final output. Extensive experiments proved that the proposed method achieves competitive performance compared with several traditional approaches.

Tumor segmentation of multi-echo MR T2-weighted images with morphological operators

NASA Astrophysics Data System (ADS)

Torres, W.; Martín-Landrove, M.; Paluszny, M.; Figueroa, G.; Padilla, G.

2009-02-01

In the present work an automatic brain tumor segmentation procedure based on mathematical morphology is proposed. The approach considers sequences of eight multi-echo MR T2-weighted images. The relaxation time T2 characterizes the relaxation of water protons in the brain tissue: white matter, gray matter, cerebrospinal fluid (CSF) or pathological tissue. Image data is initially regularized by the application of a log-convex filter in order to adjust its geometrical properties to those of noiseless data, which exhibits monotonously decreasing convex behavior. Finally the regularized data is analyzed by means of an 8-dimensional morphological eccentricity filter. In a first stage, the filter was used for the spatial homogenization of the tissues in the image, replacing each pixel by the most representative pixel within its structuring element, i.e. the one which exhibits the minimum total distance to all members in the structuring element. On the filtered images, the relaxation time T2 is estimated by means of least square regression algorithm and the histogram of T2 is determined. The T2 histogram was partitioned using the watershed morphological operator; relaxation time classes were established and used for tissue classification and segmentation of the image. The method was validated on 15 sets of MRI data with excellent results.

Full complex spatial filtering with a phase mostly DMD. [Deformable Mirror Device

NASA Technical Reports Server (NTRS)

Florence, James M.; Juday, Richard D.

1991-01-01

A new technique for implementing fully complex spatial filters with a phase mostly deformable mirror device (DMD) light modulator is described. The technique combines two or more phase-modulating flexure-beam mirror elements into a single macro-pixel. By manipulating the relative phases of the individual sub-pixels within the macro-pixel, the amplitude and the phase can be independently set for this filtering element. The combination of DMD sub-pixels into a macro-pixel is accomplished by adjusting the optical system resolution, thereby trading off system space bandwidth product for increased filtering flexibility. Volume in the larger dimensioned space, space bandwidth-complex axes count, is conserved. Experimental results are presented mapping out the coupled amplitude and phase characteristics of the individual flexure-beam DMD elements and demonstrating the independent control of amplitude and phase in a combined macro-pixel. This technique is generally applicable for implementation with any type of phase modulating light modulator.

Three-dimensional anisotropic adaptive filtering of projection data for noise reduction in cone beam CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maier, Andreas; Wigstroem, Lars; Hofmann, Hannes G.

2011-11-15

Purpose: The combination of quickly rotating C-arm gantry with digital flat panel has enabled the acquisition of three-dimensional data (3D) in the interventional suite. However, image quality is still somewhat limited since the hardware has not been optimized for CT imaging. Adaptive anisotropic filtering has the ability to improve image quality by reducing the noise level and therewith the radiation dose without introducing noticeable blurring. By applying the filtering prior to 3D reconstruction, noise-induced streak artifacts are reduced as compared to processing in the image domain. Methods: 3D anisotropic adaptive filtering was used to process an ensemble of 2D x-raymore » views acquired along a circular trajectory around an object. After arranging the input data into a 3D space (2D projections + angle), the orientation of structures was estimated using a set of differently oriented filters. The resulting tensor representation of local orientation was utilized to control the anisotropic filtering. Low-pass filtering is applied only along structures to maintain high spatial frequency components perpendicular to these. The evaluation of the proposed algorithm includes numerical simulations, phantom experiments, and in-vivo data which were acquired using an AXIOM Artis dTA C-arm system (Siemens AG, Healthcare Sector, Forchheim, Germany). Spatial resolution and noise levels were compared with and without adaptive filtering. A human observer study was carried out to evaluate low-contrast detectability. Results: The adaptive anisotropic filtering algorithm was found to significantly improve low-contrast detectability by reducing the noise level by half (reduction of the standard deviation in certain areas from 74 to 30 HU). Virtually no degradation of high contrast spatial resolution was observed in the modulation transfer function (MTF) analysis. Although the algorithm is computationally intensive, hardware acceleration using Nvidia's CUDA Interface provided an 8.9-fold speed-up of the processing (from 1336 to 150 s). Conclusions: Adaptive anisotropic filtering has the potential to substantially improve image quality and/or reduce the radiation dose required for obtaining 3D image data using cone beam CT.« less

Performance Evaluation of EnKF-based Hydrogeological Site Characterization using Color Coherent Vectors

NASA Astrophysics Data System (ADS)

Moslehi, M.; de Barros, F.

2017-12-01

Complexity of hydrogeological systems arises from the multi-scale heterogeneity and insufficient measurements of their underlying parameters such as hydraulic conductivity and porosity. An inadequate characterization of hydrogeological properties can significantly decrease the trustworthiness of numerical models that predict groundwater flow and solute transport. Therefore, a variety of data assimilation methods have been proposed in order to estimate hydrogeological parameters from spatially scarce data by incorporating the governing physical models. In this work, we propose a novel framework for evaluating the performance of these estimation methods. We focus on the Ensemble Kalman Filter (EnKF) approach that is a widely used data assimilation technique. It reconciles multiple sources of measurements to sequentially estimate model parameters such as the hydraulic conductivity. Several methods have been used in the literature to quantify the accuracy of the estimations obtained by EnKF, including Rank Histograms, RMSE and Ensemble Spread. However, these commonly used methods do not regard the spatial information and variability of geological formations. This can cause hydraulic conductivity fields with very different spatial structures to have similar histograms or RMSE. We propose a vision-based approach that can quantify the accuracy of estimations by considering the spatial structure embedded in the estimated fields. Our new approach consists of adapting a new metric, Color Coherent Vectors (CCV), to evaluate the accuracy of estimated fields achieved by EnKF. CCV is a histogram-based technique for comparing images that incorporate spatial information. We represent estimated fields as digital three-channel images and use CCV to compare and quantify the accuracy of estimations. The sensitivity of CCV to spatial information makes it a suitable metric for assessing the performance of spatial data assimilation techniques. Under various factors of data assimilation methods such as number, layout, and type of measurements, we compare the performance of CCV with other metrics such as RMSE. By simulating hydrogeological processes using estimated and true fields, we observe that CCV outperforms other existing evaluation metrics.

Knowledge-based iterative model reconstruction: comparative image quality and radiation dose with a pediatric computed tomography phantom.

PubMed

Ryu, Young Jin; Choi, Young Hun; Cheon, Jung-Eun; Ha, Seongmin; Kim, Woo Sun; Kim, In-One

2016-03-01

CT of pediatric phantoms can provide useful guidance to the optimization of knowledge-based iterative reconstruction CT. To compare radiation dose and image quality of CT images obtained at different radiation doses reconstructed with knowledge-based iterative reconstruction, hybrid iterative reconstruction and filtered back-projection. We scanned a 5-year anthropomorphic phantom at seven levels of radiation. We then reconstructed CT data with knowledge-based iterative reconstruction (iterative model reconstruction [IMR] levels 1, 2 and 3; Philips Healthcare, Andover, MA), hybrid iterative reconstruction (iDose(4), levels 3 and 7; Philips Healthcare, Andover, MA) and filtered back-projection. The noise, signal-to-noise ratio and contrast-to-noise ratio were calculated. We evaluated low-contrast resolutions and detectability by low-contrast targets and subjective and objective spatial resolutions by the line pairs and wire. With radiation at 100 peak kVp and 100 mAs (3.64 mSv), the relative doses ranged from 5% (0.19 mSv) to 150% (5.46 mSv). Lower noise and higher signal-to-noise, contrast-to-noise and objective spatial resolution were generally achieved in ascending order of filtered back-projection, iDose(4) levels 3 and 7, and IMR levels 1, 2 and 3, at all radiation dose levels. Compared with filtered back-projection at 100% dose, similar noise levels were obtained on IMR level 2 images at 24% dose and iDose(4) level 3 images at 50% dose, respectively. Regarding low-contrast resolution, low-contrast detectability and objective spatial resolution, IMR level 2 images at 24% dose showed comparable image quality with filtered back-projection at 100% dose. Subjective spatial resolution was not greatly affected by reconstruction algorithm. Reduced-dose IMR obtained at 0.92 mSv (24%) showed similar image quality to routine-dose filtered back-projection obtained at 3.64 mSv (100%), and half-dose iDose(4) obtained at 1.81 mSv.

Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEG.

PubMed

Bai, Ou; Lin, Peter; Vorbach, Sherry; Li, Jiang; Furlani, Steve; Hallett, Mark

2007-12-01

To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroencephalogram (EEG). Twelve naïve subjects performed self-paced movements consisting of three key strokes with either hand. EEG was recorded from 128 channels. The exploration was performed offline on single trial EEG data. We proposed that a successful computational procedure for classification would consist of spatial filtering, temporal filtering, feature selection, and pattern classification. A systematic investigation was performed with combinations of spatial filtering using principal component analysis (PCA), independent component analysis (ICA), common spatial patterns analysis (CSP), and surface Laplacian derivation (SLD); temporal filtering using power spectral density estimation (PSD) and discrete wavelet transform (DWT); pattern classification using linear Mahalanobis distance classifier (LMD), quadratic Mahalanobis distance classifier (QMD), Bayesian classifier (BSC), multi-layer perceptron neural network (MLP), probabilistic neural network (PNN), and support vector machine (SVM). A robust multivariate feature selection strategy using a genetic algorithm was employed. The combinations of spatial filtering using ICA and SLD, temporal filtering using PSD and DWT, and classification methods using LMD, QMD, BSC and SVM provided higher performance than those of other combinations. Utilizing one of the better combinations of ICA, PSD and SVM, the discrimination accuracy was as high as 75%. Further feature analysis showed that beta band EEG activity of the channels over right sensorimotor cortex was most appropriate for discrimination of right and left hand movement intention. Effective combinations of computational methods provide possible classification of human movement intention from single trial EEG. Such a method could be the basis for a potential brain-computer interface based on human natural movement, which might reduce the requirement of long-term training. Effective combinations of computational methods can classify human movement intention from single trial EEG with reasonable accuracy.

Compact OAM microscope for edge enhancement of biomedical and object samples

NASA Astrophysics Data System (ADS)

Gozali, Richard; Nguyen, Thien-An; Bendau, Ethan; Alfano, Robert R.

2017-09-01

The production of orbital angular momentum (OAM) by using a q-plate, which functions as an electrically tunable spatial frequency filter, provides a simple and efficient method of edge contrast in biological and medical sample imaging for histological evaluation of tissue, smears, and PAP smears. An instrument producing OAM, such as a q-plate, situated at the Fourier plane of a 4f lens system, similar to the use of a high-pass spatial filter, allows the passage of high spatial frequencies and enables the production of an image with highly illuminated edges contrasted against a dark background for both opaque and transparent objects. Compared with ordinary spiral phase plates and spatial light modulators, the q-plate has the added advantage of electric control and tunability.

Cross-media color reproduction using the frequency-based spatial gamut mapping algorithm based on human color vision

NASA Astrophysics Data System (ADS)

Wu, Guangyuan; Niu, Shijun; Li, Xiaozhou; Hu, Guichun

2018-04-01

Due to the increasing globalization of printing industry, remoting proofing will become the inevitable development trend. Cross-media color reproduction will occur in different color gamuts using remote proofing technologies, which usually leads to the problem of incompatible color gamut. In this paper, to achieve equivalent color reproduction between a monitor and a printer, a frequency-based spatial gamut mapping algorithm is proposed for decreasing the loss of visual color information. The design of algorithm is based on the contrast sensitivity functions (CSF), which exploited CSF spatial filter to preserve luminance of the high spatial frequencies and chrominance of the low frequencies. First we show a general framework for how to apply CSF spatial filter in retention of relevant visual information. Then we compare the proposed framework with HPMINDE, CUSP, Bala's algorithm. The psychophysical experimental results indicated the good performance of the proposed algorithm.

Spectrometer Baseline Control Via Spatial Filtering

NASA Technical Reports Server (NTRS)

Burleigh, M. R.; Richey, C. R.; Rinehart, S. A.; Quijada, M. A.; Wollack, E. J.

2016-01-01

An absorptive half-moon aperture mask is experimentally explored as a broad-bandwidth means of eliminating spurious spectral features arising from reprocessed radiation in an infrared Fourier transform spectrometer. In the presence of the spatial filter, an order of magnitude improvement in the fidelity of the spectrometer baseline is observed. The method is readily accommodated within the context of commonly employed instrument configurations and leads to a factor of two reduction in optical throughput. A detailed discussion of the underlying mechanism and limitations of the method are provided.

Visual Information Processing Based on Spatial Filters Constrained by Biological Data.

DTIC Science & Technology

1978-12-01

was provided by Pantie and Sekuler ( 19681. They found that the detection (if gratings was affected most by adapting isee Section 6.1. 11 to square...evidence for certain eye scans being directed by spatial information in filtered images is given. Eye scan paths of a portrait of a young girl I Figure 08...multistable objects to more complex objects such as the man- girl figure of Fisher 119681, decision boundaries that are a natural concomitant to any pattern

Least squares restoration of multi-channel images

NASA Technical Reports Server (NTRS)

Chin, Roland T.; Galatsanos, Nikolas P.

1989-01-01

In this paper, a least squares filter for the restoration of multichannel imagery is presented. The restoration filter is based on a linear, space-invariant imaging model and makes use of an iterative matrix inversion algorithm. The restoration utilizes both within-channel (spatial) and cross-channel information as constraints. Experiments using color images (three-channel imagery with red, green, and blue components) were performed to evaluate the filter's performance and to compare it with other monochrome and multichannel filters.

Diffraction phase microscopy realized with an automatic digital pinhole

NASA Astrophysics Data System (ADS)

Zheng, Cheng; Zhou, Renjie; Kuang, Cuifang; Zhao, Guangyuan; Zhang, Zhimin; Liu, Xu

2017-12-01

We report a novel approach to diffraction phase microscopy (DPM) with automatic pinhole alignment. The pinhole, which serves as a spatial low-pass filter to generate a uniform reference beam, is made out of a liquid crystal display (LCD) device that allows for electrical control. We have made DPM more accessible to users, while maintaining high phase measurement sensitivity and accuracy, through exploring low cost optical components and replacing the tedious pinhole alignment process with an automatic pinhole optical alignment procedure. Due to its flexibility in modifying the size and shape, this LCD device serves as a universal filter, requiring no future replacement. Moreover, a graphic user interface for real-time phase imaging has been also developed by using a USB CMOS camera. Experimental results of height maps of beads sample and live red blood cells (RBCs) dynamics are also presented, making this system ready for broad adaption to biological imaging and material metrology.

Use of laser range finders and range image analysis in automated assembly tasks

NASA Technical Reports Server (NTRS)

Alvertos, Nicolas; Dcunha, Ivan

1990-01-01

A proposition to study the effect of filtering processes on range images and to evaluate the performance of two different laser range mappers is made. Median filtering was utilized to remove noise from the range images. First and second order derivatives are then utilized to locate the similarities and dissimilarities between the processed and the original images. Range depth information is converted into spatial coordinates, and a set of coefficients which describe 3-D objects is generated using the algorithm developed in the second phase of this research. Range images of spheres and cylinders are used for experimental purposes. An algorithm was developed to compare the performance of two different laser range mappers based upon the range depth information of surfaces generated by each of the mappers. Furthermore, an approach based on 2-D analytic geometry is also proposed which serves as a basis for the recognition of regular 3-D geometric objects.

Excitation of multiple surface-plasmon-polariton waves using a compound surface-relief grating

NASA Astrophysics Data System (ADS)

Faryad, Muhammad; Lakhtakia, Akhlesh

2012-01-01

The excitation of multiple surface-plasmon-polariton waves, all of the same frequency but different polarization states, phase speeds, spatial profiles and degrees of localization, by a compound surface-relief grating formed by a metal and a rugate filter, both of finite thickness, was studied using the rigorous coupled-wave approach. Each period of the compound surface-relief grating was chosen to have an integral number of periods of two different simple surface-relief gratings. The excitation of different SPP waves was inferred from the absorptance peaks that were independent of the thickness of the rugate filter. The excitation of each SPP wave could be attributed to either a simple surface-relief grating present in the compound surface-relief grating or to the compound surface-relief grating itself. However, the excitation of SPP waves was found to be less efficient with the compound surface-relief grating than with a simple surface-relief grating.

Research on Heads Up and Helmet Mounted Symbology

DTIC Science & Technology

2000-03-30

used to research and develop HUD symbology. 2.2.1 Attention as a filter Broadbent’s (1958) filter model is one of the earliest attentional metaphors...that attention plays a role in favouring or enhancing processing at locations in the visual field. Although the filter model has been modified and...13 2.2 MODELS OF SPATIAL ATTENTION .................................... ~ .. · .. ~·~ ............................... 14

The elimination of zero-order diffraction of 10.6 μm infrared digital holography

NASA Astrophysics Data System (ADS)

Liu, Ning; Yang, Chao

2017-05-01

A new method of eliminating the zero-order diffraction in infrared digital holography has been raised in this paper. Usually in the reconstruction of digital holography, the spatial frequency of the infrared thermal imager, such as microbolometer, cannot be compared to the common visible CCD or CMOS devices. The infrared imager suffers the problems of large pixel size and low spatial resolution, which cause the zero-order diffraction a severe influence of the reconstruction process of digital holograms. The zero-order diffraction has very large energy and occupies the central region in the spectrum domain. In this paper, we design a new filtering strategy to overcome this problem. This filtering strategy contains two kinds of filtering process which are the Gaussian low-frequency filter and the high-pass phase averaging filter. With the correct set of the calculating parameters, these filtering strategies can work effectively on the holograms and fully eliminate the zero-order diffraction, as well as the two crossover bars shown in the spectrum domain. Detailed explanation and discussion about the new method have been proposed in this paper, and the experiment results are also demonstrated to prove the performance of this method.

Interactions of spatial and luminance information in the retina of chickens during myopia development.

PubMed

Feldkaemper, M; Diether, S; Kleine, G; Schaeffel, F

1999-01-01

Degrading the retinal image by frosted eye occluders produces elongated eyes and 'deprivation myopia' in a variety of animal models. The postulated retinal 'deprivation detector' is quite sensitive to even small changes in image contrast or spatial frequency composition. Because psychophysical experiments have shown that a decline in luminance shifts the contrast sensitivity function to lower spatial frequencies, it is likely that only a reduced spatial frequency range is available for image analysis to control eye growth. It is even possible that the compression might be sufficient to promote deprivation myopia. We have tested this hypothesis, using the animal model of the chicken. (1) At an ambient illumination of 550 lux (about 76 cd m-2), neutral density (ND) filters placed in front of the eye with 0.0, 0.5 or 1.0 log unit attenuation did not change refractive development. However, monocularly or binocularly attached filters with 2 log units attenuation produced 5-7 D of myopia relative to normal eyes. Black occluders were not more effective. Frosted eye occluders with little effect on image brightness (about 0.5 log units attenuation) produced much more myopia (about 16 D compared with the controls). (2) The effects of the ND filters on refractive development could not be reproduced if the ambient illumination was reduced by 2 log units. Probably, minor effects on image quality were introduced by optical imperfections of the ND filters which were more critical at low retinal image brightness. (3) In an optomotor experiment (spatial frequency 0.2 cyc deg-1, stripe speed 57 deg sec-1), it was shown that the chickens' contrast sensitivity was severely reduced when the eyes were covered by 2.0 ND filters. (4) Since there is evidence that changes in dopamine release from the retina may be one of the factors affecting the development of myopia, we have tested how selective these changes were for spatial information. It was found that dopamine release was controlled by both spatial and luminance information and that the inputs of both could be scarcely separated. (5) Because the experiments show that the eye becomes more sensitive to image degradation at low light, the human eye may also be more prone to develop myopia if the light levels are low during extended periods of near work. Copyright 1999 Academic Press.

An Effective Post-Filtering Framework for 3-D PET Image Denoising Based on Noise and Sensitivity Characteristics

NASA Astrophysics Data System (ADS)

Kim, Ji Hye; Ahn, Il Jun; Nam, Woo Hyun; Ra, Jong Beom

2015-02-01

Positron emission tomography (PET) images usually suffer from a noticeable amount of statistical noise. In order to reduce this noise, a post-filtering process is usually adopted. However, the performance of this approach is limited because the denoising process is mostly performed on the basis of the Gaussian random noise. It has been reported that in a PET image reconstructed by the expectation-maximization (EM), the noise variance of each voxel depends on its mean value, unlike in the case of Gaussian noise. In addition, we observe that the variance also varies with the spatial sensitivity distribution in a PET system, which reflects both the solid angle determined by a given scanner geometry and the attenuation information of a scanned object. Thus, if a post-filtering process based on the Gaussian random noise is applied to PET images without consideration of the noise characteristics along with the spatial sensitivity distribution, the spatially variant non-Gaussian noise cannot be reduced effectively. In the proposed framework, to effectively reduce the noise in PET images reconstructed by the 3-D ordinary Poisson ordered subset EM (3-D OP-OSEM), we first denormalize an image according to the sensitivity of each voxel so that the voxel mean value can represent its statistical properties reliably. Based on our observation that each noisy denormalized voxel has a linear relationship between the mean and variance, we try to convert this non-Gaussian noise image to a Gaussian noise image. We then apply a block matching 4-D algorithm that is optimized for noise reduction of the Gaussian noise image, and reconvert and renormalize the result to obtain a final denoised image. Using simulated phantom data and clinical patient data, we demonstrate that the proposed framework can effectively suppress the noise over the whole region of a PET image while minimizing degradation of the image resolution.

SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications

NASA Astrophysics Data System (ADS)

Snider, G.; Weagle, C. L.; Martin, R. V.; van Donkelaar, A.; Conrad, K.; Cunningham, D.; Gordon, C.; Zwicker, M.; Akoshile, C.; Artaxo, P.; Anh, N. X.; Brook, J.; Dong, J.; Garland, R. M.; Greenwald, R.; Griffith, D.; He, K.; Holben, B. N.; Kahn, R.; Koren, I.; Lagrosas, N.; Lestari, P.; Ma, Z.; Vanderlei Martins, J.; Quel, E. J.; Rudich, Y.; Salam, A.; Tripathi, S. N.; Yu, C.; Zhang, Q.; Zhang, Y.; Brauer, M.; Cohen, A.; Gibson, M. D.; Liu, Y.

2015-01-01

Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM2.5) at the global scale. Satellite remote sensing offers a promising approach to provide information on both short- and long-term exposure to PM2.5 at local-to-global scales, but there are limitations and outstanding questions about the accuracy and precision with which ground-level aerosol mass concentrations can be inferred from satellite remote sensing alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2.5 and discontinuous satellite observations of columnar aerosol optical depth (AOD). We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health-effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN) includes a global federation of ground-level monitors of hourly PM2.5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2.5 and PM10, are highly autonomous. Hourly PM2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, water-soluble ions, and metals. These measurements provide, in a variety of regions around the world, the key data required to evaluate and enhance satellite-based PM2.5 estimates used for assessing the health effects of aerosols. Mean PM2.5 concentrations across sites vary by more than 1 order of magnitude. Our initial measurements indicate that the ratio of AOD to ground-level PM2.5 is driven temporally and spatially by the vertical profile in aerosol scattering. Spatially this ratio is also strongly influenced by the mass scattering efficiency.

Need for speed: An optimized gridding approach for spatially explicit disease simulations.

PubMed

Sellman, Stefan; Tsao, Kimberly; Tildesley, Michael J; Brommesson, Peter; Webb, Colleen T; Wennergren, Uno; Keeling, Matt J; Lindström, Tom

2018-04-01

Numerical models for simulating outbreaks of infectious diseases are powerful tools for informing surveillance and control strategy decisions. However, large-scale spatially explicit models can be limited by the amount of computational resources they require, which poses a problem when multiple scenarios need to be explored to provide policy recommendations. We introduce an easily implemented method that can reduce computation time in a standard Susceptible-Exposed-Infectious-Removed (SEIR) model without introducing any further approximations or truncations. It is based on a hierarchical infection process that operates on entire groups of spatially related nodes (cells in a grid) in order to efficiently filter out large volumes of susceptible nodes that would otherwise have required expensive calculations. After the filtering of the cells, only a subset of the nodes that were originally at risk are then evaluated for actual infection. The increase in efficiency is sensitive to the exact configuration of the grid, and we describe a simple method to find an estimate of the optimal configuration of a given landscape as well as a method to partition the landscape into a grid configuration. To investigate its efficiency, we compare the introduced methods to other algorithms and evaluate computation time, focusing on simulated outbreaks of foot-and-mouth disease (FMD) on the farm population of the USA, the UK and Sweden, as well as on three randomly generated populations with varying degree of clustering. The introduced method provided up to 500 times faster calculations than pairwise computation, and consistently performed as well or better than other available methods. This enables large scale, spatially explicit simulations such as for the entire continental USA without sacrificing realism or predictive power.

Need for speed: An optimized gridding approach for spatially explicit disease simulations

PubMed Central

Tildesley, Michael J.; Brommesson, Peter; Webb, Colleen T.; Wennergren, Uno; Lindström, Tom

2018-01-01

Numerical models for simulating outbreaks of infectious diseases are powerful tools for informing surveillance and control strategy decisions. However, large-scale spatially explicit models can be limited by the amount of computational resources they require, which poses a problem when multiple scenarios need to be explored to provide policy recommendations. We introduce an easily implemented method that can reduce computation time in a standard Susceptible-Exposed-Infectious-Removed (SEIR) model without introducing any further approximations or truncations. It is based on a hierarchical infection process that operates on entire groups of spatially related nodes (cells in a grid) in order to efficiently filter out large volumes of susceptible nodes that would otherwise have required expensive calculations. After the filtering of the cells, only a subset of the nodes that were originally at risk are then evaluated for actual infection. The increase in efficiency is sensitive to the exact configuration of the grid, and we describe a simple method to find an estimate of the optimal configuration of a given landscape as well as a method to partition the landscape into a grid configuration. To investigate its efficiency, we compare the introduced methods to other algorithms and evaluate computation time, focusing on simulated outbreaks of foot-and-mouth disease (FMD) on the farm population of the USA, the UK and Sweden, as well as on three randomly generated populations with varying degree of clustering. The introduced method provided up to 500 times faster calculations than pairwise computation, and consistently performed as well or better than other available methods. This enables large scale, spatially explicit simulations such as for the entire continental USA without sacrificing realism or predictive power. PMID:29624574

Spatial sound field synthesis and upmixing based on the equivalent source method.

PubMed

Bai, Mingsian R; Hsu, Hoshen; Wen, Jheng-Ciang

2014-01-01

Given scarce number of recorded signals, spatial sound field synthesis with an extended sweet spot is a challenging problem in acoustic array signal processing. To address the problem, a synthesis and upmixing approach inspired by the equivalent source method (ESM) is proposed. The synthesis procedure is based on the pressure signals recorded by a microphone array and requires no source model. The array geometry can also be arbitrary. Four upmixing strategies are adopted to enhance the resolution of the reproduced sound field when there are more channels of loudspeakers than the microphones. Multi-channel inverse filtering with regularization is exploited to deal with the ill-posedness in the reconstruction process. The distance between the microphone and loudspeaker arrays is optimized to achieve the best synthesis quality. To validate the proposed system, numerical simulations and subjective listening experiments are performed. The results demonstrated that all upmixing methods improved the quality of reproduced target sound field over the original reproduction. In particular, the underdetermined ESM interpolation method yielded the best spatial sound field synthesis in terms of the reproduction error, timbral quality, and spatial quality.

Quantitative comparison between full-spectrum and filter-based imaging in hyperspectral fluorescence microscopy

PubMed Central

GAO, L.; HAGEN, N.; TKACZYK, T.S.

2012-01-01

Summary We implement a filterless illumination scheme on a hyperspectral fluorescence microscope to achieve full-range spectral imaging. The microscope employs polarisation filtering, spatial filtering and spectral unmixing filtering to replace the role of traditional filters. Quantitative comparisons between full-spectrum and filter-based microscopy are provided in the context of signal dynamic range and accuracy of measured fluorophores’ emission spectra. To show potential applications, a five-colour cell immunofluorescence imaging experiment is theoretically simulated. Simulation results indicate that the use of proposed full-spectrum imaging technique may result in three times improvement in signal dynamic range compared to that can be achieved in the filter-based imaging. PMID:22356127

A Comparison Between Three IMUs for Strapdown Airborne Gravimetry

NASA Astrophysics Data System (ADS)

Ayres-Sampaio, Diogo; Deurloo, Richard; Bos, Machiel; Magalhães, Américo; Bastos, Luísa

2015-07-01

Strapdown airborne gravimetry relies on the combination of an inertial measuring unit (IMU) and a global navigation satellite system (GNSS) to measure the Earth's gravity field. Early results with navigation-grade IMUs showed similar accuracies to those obtained with scalar gravimetric systems in the down component. This paper investigates the accuracy of three IMUs used for strapdown airborne gravimetry under the same flight conditions. The three systems considered were navigation-grade IMUs, iXSea AIRINS and iMAR iNAV-FMS, and a tactical-grade Litton LN-200. The data were collected in 2010 over the Island of Madeira, Portugal, in the scope of GEOid over MADeira campaign. The coordinates and orientation of the aircraft were computed using an extended Kalman filter based on the inertial navigation approach. GNSS position and velocity observations were used to update the filter, and the gravity disturbance was considered to be a stochastic process and was part of the state vector. A new crossover point-based serial tuning was introduced to deal with the uncertainty of choosing the filter's a priori information. The results show that with the iXSea accuracies of 2.1 and 1.6 mGal can be obtained for 1.7 and 5.0 km of spatial resolution (half-wavelength), respectively. iMAR's results were significantly affected by a nonlinear drift, which led to lower accuracies of 4.1-5.5 mGal. Remarkably, Litton showed very consistent results and achieved an accuracy of about 4.5 mGal at 5 km of spatial resolution (half-wavelength).

Genetic particle filter application to land surface temperature downscaling

NASA Astrophysics Data System (ADS)

Mechri, Rihab; Ottlé, Catherine; Pannekoucke, Olivier; Kallel, Abdelaziz

2014-03-01

Thermal infrared data are widely used for surface flux estimation giving the possibility to assess water and energy budgets through land surface temperature (LST). Many applications require both high spatial resolution (HSR) and high temporal resolution (HTR), which are not presently available from space. It is therefore necessary to develop methodologies to use the coarse spatial/high temporal resolutions LST remote-sensing products for a better monitoring of fluxes at appropriate scales. For that purpose, a data assimilation method was developed to downscale LST based on particle filtering. The basic tenet of our approach is to constrain LST dynamics simulated at both HSR and HTR, through the optimization of aggregated temperatures at the coarse observation scale. Thus, a genetic particle filter (GPF) data assimilation scheme was implemented and applied to a land surface model which simulates prior subpixel temperatures. First, the GPF downscaling scheme was tested on pseudoobservations generated in the framework of the study area landscape (Crau-Camargue, France) and climate for the year 2006. The GPF performances were evaluated against observation errors and temporal sampling. Results show that GPF outperforms prior model estimations. Finally, the GPF method was applied on Spinning Enhanced Visible and InfraRed Imager time series and evaluated against HSR data provided by an Advanced Spaceborne Thermal Emission and Reflection Radiometer image acquired on 26 July 2006. The temperatures of seven land cover classes present in the study area were estimated with root-mean-square errors less than 2.4 K which is a very promising result for downscaling LST satellite products.

Enhancing Auditory Selective Attention Using a Visually Guided Hearing Aid.

PubMed

Kidd, Gerald

2017-10-17

Listeners with hearing loss, as well as many listeners with clinically normal hearing, often experience great difficulty segregating talkers in a multiple-talker sound field and selectively attending to the desired "target" talker while ignoring the speech from unwanted "masker" talkers and other sources of sound. This listening situation forms the classic "cocktail party problem" described by Cherry (1953) that has received a great deal of study over the past few decades. In this article, a new approach to improving sound source segregation and enhancing auditory selective attention is described. The conceptual design, current implementation, and results obtained to date are reviewed and discussed in this article. This approach, embodied in a prototype "visually guided hearing aid" (VGHA) currently used for research, employs acoustic beamforming steered by eye gaze as a means for improving the ability of listeners to segregate and attend to one sound source in the presence of competing sound sources. The results from several studies demonstrate that listeners with normal hearing are able to use an attention-based "spatial filter" operating primarily on binaural cues to selectively attend to one source among competing spatially distributed sources. Furthermore, listeners with sensorineural hearing loss generally are less able to use this spatial filter as effectively as are listeners with normal hearing especially in conditions high in "informational masking." The VGHA enhances auditory spatial attention for speech-on-speech masking and improves signal-to-noise ratio for conditions high in "energetic masking." Visual steering of the beamformer supports the coordinated actions of vision and audition in selective attention and facilitates following sound source transitions in complex listening situations. Both listeners with normal hearing and with sensorineural hearing loss may benefit from the acoustic beamforming implemented by the VGHA, especially for nearby sources in less reverberant sound fields. Moreover, guiding the beam using eye gaze can be an effective means of sound source enhancement for listening conditions where the target source changes frequently over time as often occurs during turn-taking in a conversation. http://cred.pubs.asha.org/article.aspx?articleid=2601621.

Development of adaptive noise reduction filter algorithm for pediatric body images in a multi-detector CT

NASA Astrophysics Data System (ADS)

Nishimaru, Eiji; Ichikawa, Katsuhiro; Okita, Izumi; Ninomiya, Yuuji; Tomoshige, Yukihiro; Kurokawa, Takehiro; Ono, Yutaka; Nakamura, Yuko; Suzuki, Masayuki

2008-03-01

Recently, several kinds of post-processing image filters which reduce the noise of computed tomography (CT) images have been proposed. However, these image filters are mostly for adults. Because these are not very effective in small (< 20 cm) display fields of view (FOV), we cannot use them for pediatric body images (e.g., premature babies and infant children). We have developed a new noise reduction filter algorithm for pediatric body CT images. This algorithm is based on a 3D post-processing in which the output pixel values are calculated by nonlinear interpolation in z-directions on original volumetric-data-sets. This algorithm does not need the in-plane (axial plane) processing, so the spatial resolution does not change. From the phantom studies, our algorithm could reduce SD up to 40% without affecting the spatial resolution of x-y plane and z-axis, and improved the CNR up to 30%. This newly developed filter algorithm will be useful for the diagnosis and radiation dose reduction of the pediatric body CT images.

Improved Spatial Registration and Target Tracking Method for Sensors on Multiple Missiles.

PubMed

Lu, Xiaodong; Xie, Yuting; Zhou, Jun

2018-05-27

Inspired by the problem that the current spatial registration methods are unsuitable for three-dimensional (3-D) sensor on high-dynamic platform, this paper focuses on the estimation for the registration errors of cooperative missiles and motion states of maneuvering target. There are two types of errors being discussed: sensor measurement biases and attitude biases. Firstly, an improved Kalman Filter on Earth-Centered Earth-Fixed (ECEF-KF) coordinate algorithm is proposed to estimate the deviations mentioned above, from which the outcomes are furtherly compensated to the error terms. Secondly, the Pseudo Linear Kalman Filter (PLKF) and the nonlinear scheme the Unscented Kalman Filter (UKF) with modified inputs are employed for target tracking. The convergence of filtering results are monitored by a position-judgement logic, and a low-pass first order filter is selectively introduced before compensation to inhibit the jitter of estimations. In the simulation, the ECEF-KF enhancement is proven to improve the accuracy and robustness of the space alignment, while the conditional-compensation-based PLKF method is demonstrated to be the optimal performance in target tracking.

Image restoration by Wiener filtering in the presence of signal-dependent noise.

PubMed

Kondo, K; Ichioka, Y; Suzuki, T

1977-09-01

An optimum filter to restore the degraded image due to blurring and the signal-dependent noise is obtained on the basis of the theory of Wiener filtering. Computer simulations of image restoration using signal-dependent noise models are carried out. It becomes clear that the optimum filter, which makes use of a priori information on the signal-dependent nature of the noise and the spectral density of the signal and the noise showing significant spatial correlation, is potentially advantageous.

Density and distribution of nitrifying guilds in rapid sand filters for drinking water production: Dominance of Nitrospira spp.

PubMed

Tatari, Karolina; Musovic, Sanin; Gülay, Arda; Dechesne, Arnaud; Albrechtsen, Hans-Jørgen; Smets, Barth F

2017-12-15

We investigated the density and distribution of total bacteria, canonical Ammonia Oxidizing Bacteria (AOB) (Nitrosomonas plus Nitrosospira), Ammonia Oxidizing Archaea (AOA), as well as Nitrobacter and Nitrospira in rapid sand filters used for groundwater treatment. To investigate the spatial distribution of these guilds, filter material was sampled at four drinking water treatment plants (DWTPs) in parallel filters of the pre- and after-filtration stages at different locations and depths. The target guilds were quantified by qPCR targeting 16S rRNA and amoA genes. Total bacterial densities (ignoring 16S rRNA gene copy number variation) were high and ranged from 10 9 to 10 10 per gram (10 15 to 10 16 per m 3 ) of filter material. All examined guilds, except AOA, were stratified at only one of the four DWTPs. Densities varied spatially within filter (intra-filter variation) at two of the DWTPs and in parallel filters (inter-filter variation) at one of the DWTPs. Variation analysis revealed random sampling as the most efficient strategy to yield accurate mean density estimates, with collection of at least 7 samples suggested to obtain an acceptable (below half order of magnitude) density precision. Nitrospira was consistently the most dominant guild (5-10% of total community), and was generally up to 4 orders of magnitude more abundant than Nitrobacter and up to 2 orders of magnitude more abundant than canonical AOBs. These results, supplemented with further analysis of the previously reported diversity of Nitrospira in the studied DWTPs based on 16S rRNA and nxrB gene phylogeny (Gülay et al., 2016; Palomo et al., 2016), indicate that the high Nitrospira abundance is due to their comammox (complete ammonia oxidation) physiology. AOA densities were lower than AOB densities, except in the highly stratified filters, where they were of similar abundance. In conclusion, rapid sand filters are microbially dense, with varying degrees of spatial heterogeneity, which requires replicate sampling for a sufficiently precise determination of total microbial community and specific population densities. A consistently high Nitrospira to bacterial and archaeal AOB density ratio suggests that non-canonical pathways for nitrification may dominate the examined RSFs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Filter bank common spatial patterns in mental workload estimation.

PubMed

Arvaneh, Mahnaz; Umilta, Alberto; Robertson, Ian H

2015-01-01

EEG-based workload estimation technology provides a real time means of assessing mental workload. Such technology can effectively enhance the performance of the human-machine interaction and the learning process. When designing workload estimation algorithms, a crucial signal processing component is the feature extraction step. Despite several studies on this field, the spatial properties of the EEG signals were mostly neglected. Since EEG inherently has a poor spacial resolution, features extracted individually from each EEG channel may not be sufficiently efficient. This problem becomes more pronounced when we use low-cost but convenient EEG sensors with limited stability which is the case in practical scenarios. To address this issue, in this paper, we introduce a filter bank common spatial patterns algorithm combined with a feature selection method to extract spatio-spectral features discriminating different mental workload levels. To evaluate the proposed algorithm, we carry out a comparative analysis between two representative types of working memory tasks using data recorded from an Emotiv EPOC headset which is a mobile low-cost EEG recording device. The experimental results showed that the proposed spatial filtering algorithm outperformed the state-of-the algorithms in terms of the classification accuracy.

Evaluating a Local Ensemble Transform Kalman Filter snow cover data assimilation method to estimate SWE within a high-resolution hydrologic modeling framework across Western US mountainous regions

NASA Astrophysics Data System (ADS)

Oaida, C. M.; Andreadis, K.; Reager, J. T., II; Famiglietti, J. S.; Levoe, S.

2017-12-01

Accurately estimating how much snow water equivalent (SWE) is stored in mountainous regions characterized by complex terrain and snowmelt-driven hydrologic cycles is not only greatly desirable, but also a big challenge. Mountain snowpack exhibits high spatial variability across a broad range of spatial and temporal scales due to a multitude of physical and climatic factors, making it difficult to observe or estimate in its entirety. Combing remotely sensed data and high resolution hydrologic modeling through data assimilation (DA) has the potential to provide a spatially and temporally continuous SWE dataset at horizontal scales that capture sub-grid snow spatial variability and are also relevant to stakeholders such as water resource managers. Here, we present the evaluation of a new snow DA approach that uses a Local Ensemble Transform Kalman Filter (LETKF) in tandem with the Variable Infiltration Capacity macro-scale hydrologic model across the Western United States, at a daily temporal resolution, and a horizontal resolution of 1.75 km x 1.75 km. The LETKF is chosen for its relative simplicity, ease of implementation, and computational efficiency and scalability. The modeling/DA system assimilates daily MODIS Snow Covered Area and Grain Size (MODSCAG) fractional snow cover over, and has been developed to efficiently calculate SWE estimates over extended periods of time and covering large regional-scale areas at relatively high spatial resolution, ultimately producing a snow reanalysis-type dataset. Here we focus on the assessment of SWE produced by the DA scheme over several basins in California's Sierra Nevada Mountain range where Airborne Snow Observatory data is available, during the last five water years (2013-2017), which include both one of the driest and one of the wettest years. Comparison against such a spatially distributed SWE observational product provides a greater understanding of the model's ability to estimate SWE and SWE spatial variability, and highlights under which conditions snow cover DA can add value in estimating SWE.

Achromatic self-referencing interferometer

DOEpatents

Feldman, M.

1994-04-19

A self-referencing Mach-Zehnder interferometer is described for accurately measuring laser wavefronts over a broad wavelength range (for example, 600 nm to 900 nm). The apparatus directs a reference portion of an input beam to a reference arm and a measurement portion of the input beam to a measurement arm, recombines the output beams from the reference and measurement arms, and registers the resulting interference pattern ([open quotes]first[close quotes] interferogram) at a first detector. Optionally, subportions of the measurement portion are diverted to second and third detectors, which respectively register intensity and interferogram signals which can be processed to reduce the first interferogram's sensitivity to input noise. The reference arm includes a spatial filter producing a high quality spherical beam from the reference portion, a tilted wedge plate compensating for off-axis aberrations in the spatial filter output, and mirror collimating the radiation transmitted through the tilted wedge plate. The apparatus includes a thermally and mechanically stable baseplate which supports all reference arm optics, or at least the spatial filter, tilted wedge plate, and the collimator. The tilted wedge plate is mounted adjustably with respect to the spatial filter and collimator, so that it can be maintained in an orientation in which it does not introduce significant wave front errors into the beam propagating through the reference arm. The apparatus is polarization insensitive and has an equal path length configuration enabling measurement of radiation from broadband as well as closely spaced laser line sources. 3 figures.

High spatial resolution upgrade of the electron cyclotron emission radiometer for the DIII-D tokamak.

PubMed

Truong, D D; Austin, M E

2014-11-01

The 40-channel DIII-D electron cyclotron emission (ECE) radiometer provides measurements of Te(r,t) at the tokamak midplane from optically thick, second harmonic X-mode emission over a frequency range of 83-130 GHz. The frequency spacing of the radiometer's channels results in a spatial resolution of ∼1-3 cm, depending on local magnetic field and electron temperature. A new high resolution subsystem has been added to the DIII-D ECE radiometer to make sub-centimeter (0.6-0.8 cm) resolution Te measurements. The high resolution subsystem branches off from the regular channels' IF bands and consists of a microwave switch to toggle between IF bands, a switched filter bank for frequency selectivity, an adjustable local oscillator and mixer for further frequency down-conversion, and a set of eight microwave filters in the 2-4 GHz range. Higher spatial resolution is achieved through the use of a narrower (200 MHz) filter bandwidth and closer spacing between the filters' center frequencies (250 MHz). This configuration allows for full coverage of the 83-130 GHz frequency range in 2 GHz bands. Depending on the local magnetic field, this translates into a "zoomed-in" analysis of a ∼2-4 cm radial region. Expected uses of these channels include mapping the spatial dependence of Alfven eigenmodes, geodesic acoustic modes, and externally applied magnetic perturbations. Initial Te measurements, which demonstrate that the desired resolution is achieved, are presented.

Orientation masking and cross-orientation suppression (XOS): implications for estimates of filter bandwidth.

PubMed

Meese, Tim S; Holmes, David J

2010-10-01

Most contemporary models of spatial vision include a cross-oriented route to suppression (masking from a broadly tuned inhibitory pool), which is most potent at low spatial and high temporal frequencies (T. S. Meese & D. J. Holmes, 2007). The influence of this pathway can elevate orientation-masking functions without exciting the target mechanism, and because early psychophysical estimates of filter bandwidth did not accommodate this, it is likely that they have been overestimated for this corner of stimulus space. Here we show that a transient 40% contrast mask causes substantial binocular threshold elevation for a transient vertical target, and this declines from a mask orientation of 0° to about 40° (indicating tuning), and then more gently to 90°, where it remains at a factor of ∼4. We also confirm that cross-orientation masking is diminished or abolished at high spatial frequencies and for sustained temporal modulation. We fitted a simple model of pedestal masking and cross-orientation suppression (XOS) to our data and those of G. C. Phillips and H. R. Wilson (1984) and found the dependency of orientation bandwidth on spatial frequency to be much less than previously supposed. An extension of our linear spatial pooling model of contrast gain control and dilution masking (T. S. Meese & R. J. Summers, 2007) is also shown to be consistent with our results using filter bandwidths of ±20°. Both models include tightly and broadly tuned components of divisive suppression. More generally, because XOS and/or dilution masking can affect the shape of orientation-masking curves, we caution that variations in bandwidth estimates might reflect variations in processes that have nothing to do with filter bandwidth.

Faster processing of multiple spatially-heterodyned direct to digital holograms

DOEpatents

Hanson, Gregory R.; Bingham, Philip R.

2006-10-03

Systems and methods are described for faster processing of multiple spatially-heterodyned direct to digital holograms. A method includes of obtaining multiple spatially-heterodyned holograms, includes: digitally recording a first spatially-heterodyned hologram including spatial heterodyne fringes for Fourier analysis; digitally recording a second spatially-heterodyned hologram including spatial heterodyne fringes for Fourier analysis; Fourier analyzing the recorded first spatially-heterodyned hologram by shifting a first original origin of the recorded first spatially-heterodyned hologram including spatial heterodyne fringes in Fourier space to sit on top of a spatial-heterodyne carrier frequency defined as a first angle between a first reference beam and a first, object beam; applying a first digital filter to cut off signals around the first original origin and performing an inverse Fourier transform on the result; Fourier analyzing the recorded second spatially-heterodyned hologram by shifting a second original origin of the recorded second spatially-heterodyned hologram including spatial heterodyne fringes in Fourier space to sit on top of a spatial-heterodyne carrier frequency defined as a second angle between a second reference beam and a second object beam; and applying a second digital filter to cut off signals around the second original origin and performing an inverse Fourier transform on the result, wherein digitally recording the first spatially-heterodyned hologram is completed before digitally recording the second spatially-heterodyned hologram and a single digital image includes both the first spatially-heterodyned hologram and the second spatially-heterodyned hologram.

Faster processing of multiple spatially-heterodyned direct to digital holograms

DOEpatents

Hanson, Gregory R [Clinton, TN; Bingham, Philip R [Knoxville, TN

2008-09-09

Systems and methods are described for faster processing of multiple spatially-heterodyned direct to digital holograms. A method includes of obtaining multiple spatially-heterodyned holograms, includes: digitally recording a first spatially-heterodyned hologram including spatial heterodyne fringes for Fourier analysis; digitally recording a second spatially-heterodyned hologram including spatial heterodyne fringes for Fourier analysis; Fourier analyzing the recorded first spatially-heterodyned hologram by shifting a first original origin of the recorded first spatially-heterodyned hologram including spatial heterodyne fringes in Fourier space to sit on top of a spatial-heterodyne carrier frequency defined as a first angle between a first reference beam and a first object beam; applying a first digital filter to cut off signals around the first original origin and performing an inverse Fourier transform on the result; Fourier analyzing the recorded second spatially-heterodyned hologram by shifting a second original origin of the recorded second spatially-heterodyned hologram including spatial heterodyne fringes in Fourier space to sit on top of a spatial-heterodyne carrier frequency defined as a second angle between a second reference beam and a second object beam; and applying a second digital filter to cut off signals around the second original origin and performing an inverse Fourier transform on the result, wherein digitally recording the first spatially-heterodyned hologram is completed before digitally recording the second spatially-heterodyned hologram and a single digital image includes both the first spatially-heterodyned hologram and the second spatially-heterodyned hologram.

Time course based artifact identification for independent components of resting-state FMRI.

PubMed

Rummel, Christian; Verma, Rajeev Kumar; Schöpf, Veronika; Abela, Eugenio; Hauf, Martinus; Berruecos, José Fernando Zapata; Wiest, Roland

2013-01-01

In functional magnetic resonance imaging (fMRI) coherent oscillations of the blood oxygen level-dependent (BOLD) signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting-state networks (RSN). Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA) and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting-state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82, and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting-state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting-state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

Spatiotemporal video deinterlacing using control grid interpolation

NASA Astrophysics Data System (ADS)

Venkatesan, Ragav; Zwart, Christine M.; Frakes, David H.; Li, Baoxin

2015-03-01

With the advent of progressive format display and broadcast technologies, video deinterlacing has become an important video-processing technique. Numerous approaches exist in the literature to accomplish deinterlacing. While most earlier methods were simple linear filtering-based approaches, the emergence of faster computing technologies and even dedicated video-processing hardware in display units has allowed higher quality but also more computationally intense deinterlacing algorithms to become practical. Most modern approaches analyze motion and content in video to select different deinterlacing methods for various spatiotemporal regions. We introduce a family of deinterlacers that employs spectral residue to choose between and weight control grid interpolation based spatial and temporal deinterlacing methods. The proposed approaches perform better than the prior state-of-the-art based on peak signal-to-noise ratio, other visual quality metrics, and simple perception-based subjective evaluations conducted by human viewers. We further study the advantages of using soft and hard decision thresholds on the visual performance.

A morphological filter for removing 'Cirrus-like' emission from far-infrared extragalactic IRAS fields

NASA Technical Reports Server (NTRS)

Appleton, P. N.; Siqueira, P. R.; Basart, J. P.

1993-01-01

The presence of diffuse extended IR emission from the Galaxy in the form of the so called 'Galactic Cirrus' emission has hampered the exploration of the extragalactic sky at long IR wavelengths. We describe the development of a filter based on mathematical morphology which appears to be a promising approach to the problem of cirrus removal. The method of Greyscale Morphology was applied to a 100 micron IRAS image of the M81 group of galaxies. This is an extragalactic field which suffers from serious contamination from foreground Galactic 'cirrus'. Using a technique called 'sieving', it was found that the cirrus emission has a characteristic behavior which can be quantified in terms of an average spatial structure spectrum or growth function. This function was then used to attempt to remove 'cirrus' from the entire image. The result was a significant reduction of cirrus emission by an intensity factor of 15 compared with the original input image. The method appears to preserve extended emission in the spatially extended IR disks of M81 and M82 as well as distinguishing fainter galaxies within bright regions of galactic cirrus. The techniques may also be applicable to IR databases obtained with the Cosmic Background Explorer.

Neural-network-directed alignment of optical systems using the laser-beam spatial filter as an example

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Krasowski, Michael J.; Weiland, Kenneth E.

1993-01-01

This report describes an effort at NASA Lewis Research Center to use artificial neural networks to automate the alignment and control of optical measurement systems. Specifically, it addresses the use of commercially available neural network software and hardware to direct alignments of the common laser-beam-smoothing spatial filter. The report presents a general approach for designing alignment records and combining these into training sets to teach optical alignment functions to neural networks and discusses the use of these training sets to train several types of neural networks. Neural network configurations used include the adaptive resonance network, the back-propagation-trained network, and the counter-propagation network. This work shows that neural networks can be used to produce robust sequencers. These sequencers can learn by example to execute the step-by-step procedures of optical alignment and also can learn adaptively to correct for environmentally induced misalignment. The long-range objective is to use neural networks to automate the alignment and operation of optical measurement systems in remote, harsh, or dangerous aerospace environments. This work also shows that when neural networks are trained by a human operator, training sets should be recorded, training should be executed, and testing should be done in a manner that does not depend on intellectual judgments of the human operator.

Precise Aperture-Dependent Motion Compensation with Frequency Domain Fast Back-Projection Algorithm.

PubMed

Zhang, Man; Wang, Guanyong; Zhang, Lei

2017-10-26

Precise azimuth-variant motion compensation (MOCO) is an essential and difficult task for high-resolution synthetic aperture radar (SAR) imagery. In conventional post-filtering approaches, residual azimuth-variant motion errors are generally compensated through a set of spatial post-filters, where the coarse-focused image is segmented into overlapped blocks concerning the azimuth-dependent residual errors. However, image domain post-filtering approaches, such as precise topography- and aperture-dependent motion compensation algorithm (PTA), have difficulty of robustness in declining, when strong motion errors are involved in the coarse-focused image. In this case, in order to capture the complete motion blurring function within each image block, both the block size and the overlapped part need necessary extension leading to degeneration of efficiency and robustness inevitably. Herein, a frequency domain fast back-projection algorithm (FDFBPA) is introduced to deal with strong azimuth-variant motion errors. FDFBPA disposes of the azimuth-variant motion errors based on a precise azimuth spectrum expression in the azimuth wavenumber domain. First, a wavenumber domain sub-aperture processing strategy is introduced to accelerate computation. After that, the azimuth wavenumber spectrum is partitioned into a set of wavenumber blocks, and each block is formed into a sub-aperture coarse resolution image via the back-projection integral. Then, the sub-aperture images are straightforwardly fused together in azimuth wavenumber domain to obtain a full resolution image. Moreover, chirp-Z transform (CZT) is also introduced to implement the sub-aperture back-projection integral, increasing the efficiency of the algorithm. By disusing the image domain post-filtering strategy, robustness of the proposed algorithm is improved. Both simulation and real-measured data experiments demonstrate the effectiveness and superiority of the proposal.

An embedded implementation based on adaptive filter bank for brain-computer interface systems.

PubMed

Belwafi, Kais; Romain, Olivier; Gannouni, Sofien; Ghaffari, Fakhreddine; Djemal, Ridha; Ouni, Bouraoui

2018-07-15

Brain-computer interface (BCI) is a new communication pathway for users with neurological deficiencies. The implementation of a BCI system requires complex electroencephalography (EEG) signal processing including filtering, feature extraction and classification algorithms. Most of current BCI systems are implemented on personal computers. Therefore, there is a great interest in implementing BCI on embedded platforms to meet system specifications in terms of time response, cost effectiveness, power consumption, and accuracy. This article presents an embedded-BCI (EBCI) system based on a Stratix-IV field programmable gate array. The proposed system relays on the weighted overlap-add (WOLA) algorithm to perform dynamic filtering of EEG-signals by analyzing the event-related desynchronization/synchronization (ERD/ERS). The EEG-signals are classified, using the linear discriminant analysis algorithm, based on their spatial features. The proposed system performs fast classification within a time delay of 0.430 s/trial, achieving an average accuracy of 76.80% according to an offline approach and 80.25% using our own recording. The estimated power consumption of the prototype is approximately 0.7 W. Results show that the proposed EBCI system reduces the overall classification error rate for the three datasets of the BCI-competition by 5% compared to other similar implementations. Moreover, experiment shows that the proposed system maintains a high accuracy rate with a short processing time, a low power consumption, and a low cost. Performing dynamic filtering of EEG-signals using WOLA increases the recognition rate of ERD/ERS patterns of motor imagery brain activity. This approach allows to develop a complete prototype of a EBCI system that achieves excellent accuracy rates. Copyright © 2018 Elsevier B.V. All rights reserved.

The role of spatial attention in visual word processing

NASA Technical Reports Server (NTRS)

Mccann, Robert S.; Folk, Charles L.; Johnston, James C.

1992-01-01

Subjects made lexical decisions on a target letter string presented above or below fixation. In Experiments 1 and 2, target location was cued 100 ms in advance of target onset. Responses were faster on validly than on invalidly cued trials. In Experiment 3, the target was sometimes accompanied by irrelevant stimuli on the other side of fixation; in such cases, responses were slowed (a spatial filtering effect). Both cuing and filtering effects on response time were additive with effects of word frequency and lexical status (words vs. nonwords). These findings are difficult to reconcile with claims that spatial attention is less involved in processing familiar words than in unfamiliar words and nonwords. The results can be reconciled with a late-selection locus of spatial attention only with difficulty, but are easily explained by early-selection models.

Low-Rank Linear Dynamical Systems for Motor Imagery EEG.

PubMed

Zhang, Wenchang; Sun, Fuchun; Tan, Chuanqi; Liu, Shaobo

2016-01-01

The common spatial pattern (CSP) and other spatiospectral feature extraction methods have become the most effective and successful approaches to solve the problem of motor imagery electroencephalography (MI-EEG) pattern recognition from multichannel neural activity in recent years. However, these methods need a lot of preprocessing and postprocessing such as filtering, demean, and spatiospectral feature fusion, which influence the classification accuracy easily. In this paper, we utilize linear dynamical systems (LDSs) for EEG signals feature extraction and classification. LDSs model has lots of advantages such as simultaneous spatial and temporal feature matrix generation, free of preprocessing or postprocessing, and low cost. Furthermore, a low-rank matrix decomposition approach is introduced to get rid of noise and resting state component in order to improve the robustness of the system. Then, we propose a low-rank LDSs algorithm to decompose feature subspace of LDSs on finite Grassmannian and obtain a better performance. Extensive experiments are carried out on public dataset from "BCI Competition III Dataset IVa" and "BCI Competition IV Database 2a." The results show that our proposed three methods yield higher accuracies compared with prevailing approaches such as CSP and CSSP.

Microarray image analysis: background estimation using quantile and morphological filters.

PubMed

Bengtsson, Anders; Bengtsson, Henrik

2006-02-28

In a microarray experiment the difference in expression between genes on the same slide is up to 103 fold or more. At low expression, even a small error in the estimate will have great influence on the final test and reference ratios. In addition to the true spot intensity the scanned signal consists of different kinds of noise referred to as background. In order to assess the true spot intensity background must be subtracted. The standard approach to estimate background intensities is to assume they are equal to the intensity levels between spots. In the literature, morphological opening is suggested to be one of the best methods for estimating background this way. This paper examines fundamental properties of rank and quantile filters, which include morphological filters at the extremes, with focus on their ability to estimate between-spot intensity levels. The bias and variance of these filter estimates are driven by the number of background pixels used and their distributions. A new rank-filter algorithm is implemented and compared to methods available in Spot by CSIRO and GenePix Pro by Axon Instruments. Spot's morphological opening has a mean bias between -47 and -248 compared to a bias between 2 and -2 for the rank filter and the variability of the morphological opening estimate is 3 times higher than for the rank filter. The mean bias of Spot's second method, morph.close.open, is between -5 and -16 and the variability is approximately the same as for morphological opening. The variability of GenePix Pro's region-based estimate is more than ten times higher than the variability of the rank-filter estimate and with slightly more bias. The large variability is because the size of the background window changes with spot size. To overcome this, a non-adaptive region-based method is implemented. Its bias and variability are comparable to that of the rank filter. The performance of more advanced rank filters is equal to the best region-based methods. However, in order to get unbiased estimates these filters have to be implemented with great care. The performance of morphological opening is in general poor with a substantial spatial-dependent bias.

Dynamic laser speckle angiography achieved by eigen-decomposition filtering.

PubMed

Li, Chenxi; Wang, Ruikang

2017-06-01

A new approach is proposed for statistically analysis of laser speckle signals emerged from a living biological tissue based on eigen-decomposition to separate the dynamic speckle signals due to moving blood cells from the static speckle signals due to static tissue components, upon which to achieve angiography of the interrogated tissue in vivo. The proposed approach is tested by imaging mouse ear pinna in vivo, demonstrating its capability of providing detailed microvascular networks with high contrast, and high temporal and spatial resolutions. It is expected to provide further opportunities for laser speckle imaging in the biomedical and clinical applications where microvascular response to certain stimulus or tissue injury is of interest. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

High-resolution hyperspectral ground mapping for robotic vision

NASA Astrophysics Data System (ADS)

Neuhaus, Frank; Fuchs, Christian; Paulus, Dietrich

2018-04-01

Recently released hyperspectral cameras use large, mosaiced filter patterns to capture different ranges of the light's spectrum in each of the camera's pixels. Spectral information is sparse, as it is not fully available in each location. We propose an online method that avoids explicit demosaicing of camera images by fusing raw, unprocessed, hyperspectral camera frames inside an ego-centric ground surface map. It is represented as a multilayer heightmap data structure, whose geometry is estimated by combining a visual odometry system with either dense 3D reconstruction or 3D laser data. We use a publicly available dataset to show that our approach is capable of constructing an accurate hyperspectral representation of the surface surrounding the vehicle. We show that in many cases our approach increases spatial resolution over a demosaicing approach, while providing the same amount of spectral information.

A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface.

PubMed

Zhou, Bangyan; Wu, Xiaopei; Lv, Zhao; Zhang, Lei; Guo, Xiaojin

2016-01-01

Independent component analysis (ICA) as a promising spatial filtering method can separate motor-related independent components (MRICs) from the multichannel electroencephalogram (EEG) signals. However, the unpredictable burst interferences may significantly degrade the performance of ICA-based brain-computer interface (BCI) system. In this study, we proposed a new algorithm frame to address this issue by combining the single-trial-based ICA filter with zero-training classifier. We developed a two-round data selection method to identify automatically the badly corrupted EEG trials in the training set. The "high quality" training trials were utilized to optimize the ICA filter. In addition, we proposed an accuracy-matrix method to locate the artifact data segments within a single trial and investigated which types of artifacts can influence the performance of the ICA-based MIBCIs. Twenty-six EEG datasets of three-class motor imagery were used to validate the proposed methods, and the classification accuracies were compared with that obtained by frequently used common spatial pattern (CSP) spatial filtering algorithm. The experimental results demonstrated that the proposed optimizing strategy could effectively improve the stability, practicality and classification performance of ICA-based MIBCI. The study revealed that rational use of ICA method may be crucial in building a practical ICA-based MIBCI system.

Fuzzy Filtering Method for Color Videos Corrupted by Additive Noise

PubMed Central

Ponomaryov, Volodymyr I.; Montenegro-Monroy, Hector; Nino-de-Rivera, Luis

2014-01-01

A novel method for the denoising of color videos corrupted by additive noise is presented in this paper. The proposed technique consists of three principal filtering steps: spatial, spatiotemporal, and spatial postprocessing. In contrast to other state-of-the-art algorithms, during the first spatial step, the eight gradient values in different directions for pixels located in the vicinity of a central pixel as well as the R, G, and B channel correlation between the analogous pixels in different color bands are taken into account. These gradient values give the information about the level of contamination then the designed fuzzy rules are used to preserve the image features (textures, edges, sharpness, chromatic properties, etc.). In the second step, two neighboring video frames are processed together. Possible local motions between neighboring frames are estimated using block matching procedure in eight directions to perform interframe filtering. In the final step, the edges and smoothed regions in a current frame are distinguished for final postprocessing filtering. Numerous simulation results confirm that this novel 3D fuzzy method performs better than other state-of-the-art techniques in terms of objective criteria (PSNR, MAE, NCD, and SSIM) as well as subjective perception via the human vision system in the different color videos. PMID:24688428

The significance of retinal image contrast and spatial frequency composition for eye growth modulation in young chicks

PubMed Central

Tran, Nina; Chiu, Sara; Tian, Yibin; Wildsoet, Christine F.

2009-01-01

Purpose This study sought further insight into the stimulus dependence of form deprivation myopia, a common response to retinal image degradation in young animals. Methods Each of 4 Bangerter diffusing filters (0.6, 0.1, <0.1, and LP (light perception only)) combined with clear plano lenses, as well as plano lenses alone, were fitted monocularly to 4-day-old chicks. Axial ocular dimensions and refractive errors were monitored over a 14-day treatment period, using high frequency A-scan ultrasonography and an autorefractor, respectively. Results Only the <0.1 and LP filters induced significant form deprivation myopia; these filters induced similarly large myopic shifts in refractive error (mean interocular differences ±SEM: -9.92 ±1.99, -7.26 ± 1.60 D respectively), coupled to significant increases in both vitreous chamber depths and optical axial lengths (p<0.001). The other 3 groups showed comparable, small changes in their ocular dimensions (p>0.05), and only small myopic shifts in refraction (<3.00 D). The myopia-inducing filters eliminated mid-and-high spatial frequency information. Conclusions Our results are consistent with emmetropization being tuned to mid-spatial frequencies. They also imply that form deprivation is not a graded phenomenon. PMID:18533221

Optical design of the lightning imager for MTG

NASA Astrophysics Data System (ADS)

Lorenzini, S.; Bardazzi, R.; Di Giampietro, M.; Feresin, F.; Taccola, M.; Cuevas, L. P.

2017-11-01

The Lightning Imager for Meteosat Third Generation is an optical payload with on-board data processing for the detection of lightning. The instrument will provide a global monitoring of lightning events over the full Earth disk from geostationary orbit and will operate in day and night conditions. The requirements of the large field of view together with the high detection efficiency with small and weak optical pulses superimposed to a much brighter and highly spatial and temporal variable background (full operation during day and night conditions, seasonal variations and different albedos between clouds oceans and lands) are driving the design of the optical instrument. The main challenge is to distinguish a true lightning from false events generated by random noise (e.g. background shot noise) or sun glints diffusion or signal variations originated by microvibrations. This can be achieved thanks to a `multi-dimensional' filtering, simultaneously working on the spectral, spatial and temporal domains. The spectral filtering is achieved with a very narrowband filter centred on the bright lightning O2 triplet line (777.4 nm +/- 0.17 nm). The spatial filtering is achieved with a ground sampling distance significantly smaller (between 4 and 5 km at sub satellite pointing) than the dimensions of a typical lightning pulse. The temporal filtering is achieved by sampling continuously the Earth disk within a period close to 1 ms. This paper presents the status of the optical design addressing the trade-off between different configurations and detailing the design and the analyses of the current baseline. Emphasis is given to the discussion of the design drivers and the solutions implemented in particular concerning the spectral filtering and the optimisation of the signal to noise ratio.

Laser system using regenerative amplifier

DOEpatents

Emmett, John L. [Pleasanton, CA

1980-03-04

High energy laser system using a regenerative amplifier, which relaxes all constraints on laser components other than the intrinsic damage level of matter, so as to enable use of available laser system components. This can be accomplished by use of segmented components, spatial filters, at least one amplifier using solid state or gaseous media, and separated reflector members providing a long round trip time through the regenerative cavity, thereby allowing slower switching and adequate time to clear the spatial filters, etc. The laser system simplifies component requirements and reduces component cost while providing high energy output.

Automating "Word of Mouth" to Recommend Classes to Students: An Application of Social Information Filtering Algorithms

ERIC Educational Resources Information Center

Booker, Queen Esther

2009-01-01

An approach used to tackle the problem of helping online students find the classes they want and need is a filtering technique called "social information filtering," a general approach to personalized information filtering. Social information filtering essentially automates the process of "word-of-mouth" recommendations: items are recommended to a…

The effect of Bangerter filters on binocular function in observers with amblyopia.

PubMed

Chen, Zidong; Li, Jinrong; Thompson, Benjamin; Deng, Daming; Yuan, Junpeng; Chan, Lily; Hess, Robert F; Yu, Minbin

2014-10-28

We assessed whether partial occlusion of the nonamblyopic eye with Bangerter filters can immediately reduce suppression and promote binocular summation of contrast in observers with amblyopia. In Experiment 1, suppression was measured for 22 observers (mean age, 20 years; range, 14-32 years; 10 females) with strabismic or anisometropic amblyopia and 10 controls using our previously established "balance point" protocol. Measurements were made at baseline and with 0.6-, 0.4-, and 0.2-strength Bangerter filters placed over the nonamblyopic/dominant eye. In Experiment 2, psychophysical measurements of contrast sensitivity were made under binocular and monocular viewing conditions for 25 observers with anisometropic amblyopia (mean age, 17 years; range, 11-28 years; 14 females) and 22 controls (mean age, 24 years; range, 22-27; 12 female). Measurements were made at baseline, and with 0.4- and 0.2-strength Bangerter filters placed over the nonamblyopic/dominant eye. Binocular summation ratios (BSRs) were calculated at baseline and with Bangerter filters in place. Experiment 1: Bangerter filters reduced suppression in observers with amblyopia and induced suppression in controls (P = 0.025). The 0.2-strength filter eliminated suppression in observers with amblyopia and this was not a visual acuity effect. Experiment 2: Bangerter filters were able to induce normal levels of binocular contrast summation in the group of observers with anisometropic amblyopia for a stimulus with a spatial frequency of 3 cycles per degree (cpd, P = 0.006). The filters reduced binocular summation in controls. Bangerter filters can immediately reduce suppression and promote binocular summation for mid/low spatial frequencies in observers with amblyopia. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

[Study on the Spectral Characteristics of the Narrow-Band Filter in SHS].

PubMed

Luo, Hai-yan; Shi, Hai-liang; Li, Zhi-wei; Li, Shuang; Xiong, Wei; Hong, Jin

2015-04-01

The spectral response of spatial heterodyne spectroscopy (SHS) is determined by the spectrum property of narrow-band filter. As discussed in previous studies, the symmetric heterodyned interferogram of high frequency waves modulated by SHS and lack of sample lead to spectral confusion, which is associated with the true and ghost spectra. Because of the deviation from theoretical index of narrow-band filter in the process of coating, the boarded spectral response and middle wave shift are presented, and conditions in the theoretical Littrow wavelength made the effective wavelength range of SHS reduced. According to the measured curve of filter, a new wavenumber of zero spatial frequency can be reset by tunable laser, and it is easy for SHS to improve the spectral aliasing distortion. The results show that it is utilized to the maximum extent of the effective bandwidth by adjusting the grating angle of rotation to change the Littrow wavelength of the basic frequency, and the spectral region increased to 14.9 nm from original 12.9 nm.

Multimodal Medical Image Fusion by Adaptive Manifold Filter.

PubMed

Geng, Peng; Liu, Shuaiqi; Zhuang, Shanna

2015-01-01

Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. The modified local contrast information is proposed to fuse multimodal medical images. Firstly, the adaptive manifold filter is introduced into filtering source images as the low-frequency part in the modified local contrast. Secondly, the modified spatial frequency of the source images is adopted as the high-frequency part in the modified local contrast. Finally, the pixel with larger modified local contrast is selected into the fused image. The presented scheme outperforms the guided filter method in spatial domain, the dual-tree complex wavelet transform-based method, nonsubsampled contourlet transform-based method, and four classic fusion methods in terms of visual quality. Furthermore, the mutual information values by the presented method are averagely 55%, 41%, and 62% higher than the three methods and those values of edge based similarity measure by the presented method are averagely 13%, 33%, and 14% higher than the three methods for the six pairs of source images.

Isolating Flow-field Discontinuities while Preserving Monotonicity and High-order Accuracy on Cartesian Meshes

DTIC Science & Technology

2017-01-09

2017 Distribution A – Approved for public release; Distribution Unlimited. PA Clearance 17030 Introduction • Filtering schemes offer a less...dissipative alternative to the standard artificial dissipation operators when applied to high- order spatial/temporal schemes • Limiting Fact: Filters impart...systems require a preconditioned dual-time framework to be solved efficiently • Limiting Fact: Filtering cannot be applied only at the physical- time

Detecting Weak Spectral Lines in Interferometric Data through Matched Filtering

NASA Astrophysics Data System (ADS)

Loomis, Ryan A.; Öberg, Karin I.; Andrews, Sean M.; Walsh, Catherine; Czekala, Ian; Huang, Jane; Rosenfeld, Katherine A.

2018-04-01

Modern radio interferometers enable observations of spectral lines with unprecedented spatial resolution and sensitivity. In spite of these technical advances, many lines of interest are still at best weakly detected and therefore necessitate detection and analysis techniques specialized for the low signal-to-noise ratio (S/N) regime. Matched filters can leverage knowledge of the source structure and kinematics to increase sensitivity of spectral line observations. Application of the filter in the native Fourier domain improves S/N while simultaneously avoiding the computational cost and ambiguities associated with imaging, making matched filtering a fast and robust method for weak spectral line detection. We demonstrate how an approximate matched filter can be constructed from a previously observed line or from a model of the source, and we show how this filter can be used to robustly infer a detection significance for weak spectral lines. When applied to ALMA Cycle 2 observations of CH3OH in the protoplanetary disk around TW Hya, the technique yields a ≈53% S/N boost over aperture-based spectral extraction methods, and we show that an even higher boost will be achieved for observations at higher spatial resolution. A Python-based open-source implementation of this technique is available under the MIT license at http://github.com/AstroChem/VISIBLE.

The Interplay between Environmental Filtering and Spatial Processes in Structuring Communities: The Case of Neotropical Snake Communities

PubMed Central

Cavalheri, Hamanda; Both, Camila; Martins, Marcio

2015-01-01

Both habitat filters and spatial processes can influence community structure. Space alone affects species immigration from the regional species pool, whereas habitat filters affect species distribution and inter-specific interactions. This study aimed to understand how the interplay between environmental and geographical processes influenced the structure of Neotropical snake communities in different habitat types. We selected six studies that sampled snakes in forests, four conducted in savannas and two in grasslands (the latter two are grouped in a non-forest category). We used the net relatedness and nearest taxon indices to assess phylogenetic structure within forest and non-forest areas. We also used the phylogenetic fuzzy-weighting algorithm to characterize phylogenetic structure across communities and the relation of phylogenetic composition patterns to habitat type, structure, and latitude. Finally, we tested for morphological trait convergence and phylogenetic niche conservatism using four forest and four non-forest areas for which morphological data were available. Community phylogenetic composition changed across forest and non-forest areas suggesting that environmental filtering influences community structure. Species traits were affected by habitat type, indicating convergence at the metacommunity level. Tail length, robustness, and number of ventral scales maximized community convergence among forest and non-forest areas. The observed patterns suggested environmental filtering, indicating that less vertically structured habitats represent a strong filter. Despite the fact that phylogenetic structure was not detected individually for each community, we observed a trend towards communities composed by more closely related species in higher latitudes and more overdispersed compositions in lower latitudes. Such pattern suggests that the limited distribution of major snake lineages constrained species distributions. Structure indices for each community were also related to habitat type, showing that communities from non-forest areas tend to be more clustered. Our study showed that both environmental filtering and spatial gradients play important roles in shaping the composition of Neotropical snake communities. PMID:26061038

The Interplay between Environmental Filtering and Spatial Processes in Structuring Communities: The Case of Neotropical Snake Communities.

PubMed

Cavalheri, Hamanda; Both, Camila; Martins, Marcio

2015-01-01

Both habitat filters and spatial processes can influence community structure. Space alone affects species immigration from the regional species pool, whereas habitat filters affect species distribution and inter-specific interactions. This study aimed to understand how the interplay between environmental and geographical processes influenced the structure of Neotropical snake communities in different habitat types. We selected six studies that sampled snakes in forests, four conducted in savannas and two in grasslands (the latter two are grouped in a non-forest category). We used the net relatedness and nearest taxon indices to assess phylogenetic structure within forest and non-forest areas. We also used the phylogenetic fuzzy-weighting algorithm to characterize phylogenetic structure across communities and the relation of phylogenetic composition patterns to habitat type, structure, and latitude. Finally, we tested for morphological trait convergence and phylogenetic niche conservatism using four forest and four non-forest areas for which morphological data were available. Community phylogenetic composition changed across forest and non-forest areas suggesting that environmental filtering influences community structure. Species traits were affected by habitat type, indicating convergence at the metacommunity level. Tail length, robustness, and number of ventral scales maximized community convergence among forest and non-forest areas. The observed patterns suggested environmental filtering, indicating that less vertically structured habitats represent a strong filter. Despite the fact that phylogenetic structure was not detected individually for each community, we observed a trend towards communities composed by more closely related species in higher latitudes and more overdispersed compositions in lower latitudes. Such pattern suggests that the limited distribution of major snake lineages constrained species distributions. Structure indices for each community were also related to habitat type, showing that communities from non-forest areas tend to be more clustered. Our study showed that both environmental filtering and spatial gradients play important roles in shaping the composition of Neotropical snake communities.

Improved Cloud and Snow Screening in MAIAC Aerosol Retrievals Using Spectral and Spatial Analysis

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Laszlo, I.; Kokrkin, S.

2012-01-01

An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.

Reading with filtered fixations: adult age differences in the effectiveness of low-level properties of text within central vision.

PubMed

Jordan, Timothy R; McGowan, Victoria A; Paterson, Kevin B

2014-06-01

When reading, low-level visual properties of text are acquired from central vision during brief fixational pauses, but the effectiveness of these properties may differ in older age. To investigate, a filtering technique displayed the low, medium, or high spatial frequencies of text falling within central vision as young (18-28 years) and older (65+ years) adults read. Reading times for normal text did not differ across age groups, but striking differences in the effectiveness of spatial frequencies were observed. Consequently, even when young and older adults read equally well, the effectiveness of spatial frequencies in central vision differs markedly in older age. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Physics-based coastal current tomographic tracking using a Kalman filter.

PubMed

Wang, Tongchen; Zhang, Ying; Yang, T C; Chen, Huifang; Xu, Wen

2018-05-01

Ocean acoustic tomography can be used based on measurements of two-way travel-time differences between the nodes deployed on the perimeter of the surveying area to invert/map the ocean current inside the area. Data at different times can be related using a Kalman filter, and given an ocean circulation model, one can in principle now cast and even forecast current distribution given an initial distribution and/or the travel-time difference data on the boundary. However, an ocean circulation model requires many inputs (many of them often not available) and is unpractical for estimation of the current field. A simplified form of the discretized Navier-Stokes equation is used to show that the future velocity state is just a weighted spatial average of the current state. These weights could be obtained from an ocean circulation model, but here in a data driven approach, auto-regressive methods are used to obtain the time and space dependent weights from the data. It is shown, based on simulated data, that the current field tracked using a Kalman filter (with an arbitrary initial condition) is more accurate than that estimated by the standard methods where data at different times are treated independently. Real data are also examined.

Confocal filtering in cathodoluminescence microscopy of nanostructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Narváez, Angela C., E-mail: a.c.narvaez@tudelft.nl, E-mail: j.p.hoogenboom@tudelft.nl; Weppelman, I. Gerward C.; Moerland, Robert J.

2014-06-23

Cathodoluminescence (CL) microscopy allows optical characterization of nanostructures at high spatial resolution. At the nanoscale, a main challenge of the technique is related to the background CL generated within the sample substrate. Here, we implement confocal detection of the CL signal to minimize the background contribution to the measurement. Nano-phosphors were used as point sources to evaluate the filtering capabilities of our confocal CL system, obtaining an axial intensity profile with 2.7 μm full width at half maximum for the central peak, in good correspondence with theoretical expectations. Considering the electron interaction volume, we found that the confocal filter becomes effectivemore » for electron energies above 20 keV, when using a 25 μm pinhole (0.86 Airy units). To illustrate our approach, we present confocal CL imaging of gold nanowires and triangular shaped plates deposited on an indium-tin oxide covered glass substrate, comparing the images with those obtained in standard unfiltered CL detection. The results show that confocal CL microscopy is a valuable tool for the investigation of nanostructures on highly cathodoluminescent substrates, widely used in biological and optical applications.« less

Bacterial carbon utilization in vertical subsurface flow constructed wetlands.

PubMed

Tietz, Alexandra; Langergraber, Günter; Watzinger, Andrea; Haberl, Raimund; Kirschner, Alexander K T

2008-03-01

Subsurface vertical flow constructed wetlands with intermittent loading are considered as state of the art and can comply with stringent effluent requirements. It is usually assumed that microbial activity in the filter body of constructed wetlands, responsible for the removal of carbon and nitrogen, relies mainly on bacterially mediated transformations. However, little quantitative information is available on the distribution of bacterial biomass and production in the "black-box" constructed wetland. The spatial distribution of bacterial carbon utilization, based on bacterial (14)C-leucine incorporation measurements, was investigated for the filter body of planted and unplanted indoor pilot-scale constructed wetlands, as well as for a planted outdoor constructed wetland. A simple mass-balance approach was applied to explain the bacterially catalysed organic matter degradation in this system by comparing estimated bacterial carbon utilization rates with simultaneously measured carbon reduction values. The pilot-scale constructed wetlands proved to be a suitable model system for investigating microbial carbon utilization in constructed wetlands. Under an ideal operating mode, the bulk of bacterial productivity occurred within the first 10cm of the filter body. Plants seemed to have no significant influence on productivity and biomass of bacteria, as well as on wastewater total organic carbon removal.

Comparative evaluation of topographical data of dental implant surfaces applying optical interferometry and scanning electron microscopy.

PubMed

Kournetas, N; Spintzyk, S; Schweizer, E; Sawada, T; Said, F; Schmid, P; Geis-Gerstorfer, J; Eliades, G; Rupp, F

2017-08-01

Comparability of topographical data of implant surfaces in literature is low and their clinical relevance often equivocal. The aim of this study was to investigate the ability of scanning electron microscopy and optical interferometry to assess statistically similar 3-dimensional roughness parameter results and to evaluate these data based on predefined criteria regarded relevant for a favorable biological response. Four different commercial dental screw-type implants (NanoTite Certain Prevail, TiUnite Brånemark Mk III, XiVE S Plus and SLA Standard Plus) were analyzed by stereo scanning electron microscopy and white light interferometry. Surface height, spatial and hybrid roughness parameters (Sa, Sz, Ssk, Sku, Sal, Str, Sdr) were assessed from raw and filtered data (Gaussian 50μm and 5μm cut-off-filters), respectively. Data were statistically compared by one-way ANOVA and Tukey-Kramer post-hoc test. For a clinically relevant interpretation, a categorizing evaluation approach was used based on predefined threshold criteria for each roughness parameter. The two methods exhibited predominantly statistical differences. Dependent on roughness parameters and filter settings, both methods showed variations in rankings of the implant surfaces and differed in their ability to discriminate the different topographies. Overall, the analyses revealed scale-dependent roughness data. Compared to the pure statistical approach, the categorizing evaluation resulted in much more similarities between the two methods. This study suggests to reconsider current approaches for the topographical evaluation of implant surfaces and to further seek after proper experimental settings. Furthermore, the specific role of different roughness parameters for the bioresponse has to be studied in detail in order to better define clinically relevant, scale-dependent and parameter-specific thresholds and ranges. Copyright © 2017 The Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Bayesian Approaches for Model and Multi-mission Satellites Data Fusion

NASA Astrophysics Data System (ADS)

Khaki, M., , Dr; Forootan, E.; Awange, J.; Kuhn, M.

2017-12-01

Traditionally, data assimilation is formulated as a Bayesian approach that allows one to update model simulations using new incoming observations. This integration is necessary due to the uncertainty in model outputs, which mainly is the result of several drawbacks, e.g., limitations in accounting for the complexity of real-world processes, uncertainties of (unknown) empirical model parameters, and the absence of high resolution (both spatially and temporally) data. Data assimilation, however, requires knowledge of the physical process of a model, which may be either poorly described or entirely unavailable. Therefore, an alternative method is required to avoid this dependency. In this study we present a novel approach which can be used in hydrological applications. A non-parametric framework based on Kalman filtering technique is proposed to improve hydrological model estimates without using a model dynamics. Particularly, we assesse Kalman-Taken formulations that take advantage of the delay coordinate method to reconstruct nonlinear dynamics in the absence of the physical process. This empirical relationship is then used instead of model equations to integrate satellite products with model outputs. We use water storage variables from World-Wide Water Resources Assessment (W3RA) simulations and update them using data known as the Gravity Recovery And Climate Experiment (GRACE) terrestrial water storage (TWS) and also surface soil moisture data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) over Australia for the period of 2003 to 2011. The performance of the proposed integration method is compared with data obtained from the more traditional assimilation scheme using the Ensemble Square-Root Filter (EnSRF) filtering technique (Khaki et al., 2017), as well as by evaluating them against ground-based soil moisture and groundwater observations within the Murray-Darling Basin.

Sequential estimation of surface water mass changes from daily satellite gravimetry data

NASA Astrophysics Data System (ADS)

Ramillien, G. L.; Frappart, F.; Gratton, S.; Vasseur, X.

2015-03-01

We propose a recursive Kalman filtering approach to map regional spatio-temporal variations of terrestrial water mass over large continental areas, such as South America. Instead of correcting hydrology model outputs by the GRACE observations using a Kalman filter estimation strategy, regional 2-by-2 degree water mass solutions are constructed by integration of daily potential differences deduced from GRACE K-band range rate (KBRR) measurements. Recovery of regional water mass anomaly averages obtained by accumulation of information of daily noise-free simulated GRACE data shows that convergence is relatively fast and yields accurate solutions. In the case of cumulating real GRACE KBRR data contaminated by observational noise, the sequential method of step-by-step integration provides estimates of water mass variation for the period 2004-2011 by considering a set of suitable a priori error uncertainty parameters to stabilize the inversion. Spatial and temporal averages of the Kalman filter solutions over river basin surfaces are consistent with the ones computed using global monthly/10-day GRACE solutions from official providers CSR, GFZ and JPL. They are also highly correlated to in situ records of river discharges (70-95 %), especially for the Obidos station where the total outflow of the Amazon River is measured. The sparse daily coverage of the GRACE satellite tracks limits the time resolution of the regional Kalman filter solutions, and thus the detection of short-term hydrological events.

Spatial Angular Compounding Technique for H-Scan Ultrasound Imaging.

PubMed

Khairalseed, Mawia; Xiong, Fangyuan; Kim, Jung-Whan; Mattrey, Robert F; Parker, Kevin J; Hoyt, Kenneth

2018-01-01

H-Scan is a new ultrasound imaging technique that relies on matching a model of pulse-echo formation to the mathematics of a class of Gaussian-weighted Hermite polynomials. This technique may be beneficial in the measurement of relative scatterer sizes and in cancer therapy, particularly for early response to drug treatment. Because current H-scan techniques use focused ultrasound data acquisitions, spatial resolution degrades away from the focal region and inherently affects relative scatterer size estimation. Although the resolution of ultrasound plane wave imaging can be inferior to that of traditional focused ultrasound approaches, the former exhibits a homogeneous spatial resolution throughout the image plane. The purpose of this study was to implement H-scan using plane wave imaging and investigate the impact of spatial angular compounding on H-scan image quality. Parallel convolution filters using two different Gaussian-weighted Hermite polynomials that describe ultrasound scattering events are applied to the radiofrequency data. The H-scan processing is done on each radiofrequency image plane before averaging to get the angular compounded image. The relative strength from each convolution is color-coded to represent relative scatterer size. Given results from a series of phantom materials, H-scan imaging with spatial angular compounding more accurately reflects the true scatterer size caused by reductions in the system point spread function and improved signal-to-noise ratio. Preliminary in vivo H-scan imaging of tumor-bearing animals suggests this modality may be useful for monitoring early response to chemotherapeutic treatment. Overall, H-scan imaging using ultrasound plane waves and spatial angular compounding is a promising approach for visualizing the relative size and distribution of acoustic scattering sources. Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

Power spectrum weighted edge analysis for straight edge detection in images

NASA Astrophysics Data System (ADS)

Karvir, Hrishikesh V.; Skipper, Julie A.

2007-04-01

Most man-made objects provide characteristic straight line edges and, therefore, edge extraction is a commonly used target detection tool. However, noisy images often yield broken edges that lead to missed detections, and extraneous edges that may contribute to false target detections. We present a sliding-block approach for target detection using weighted power spectral analysis. In general, straight line edges appearing at a given frequency are represented as a peak in the Fourier domain at a radius corresponding to that frequency, and a direction corresponding to the orientation of the edges in the spatial domain. Knowing the edge width and spacing between the edges, a band-pass filter is designed to extract the Fourier peaks corresponding to the target edges and suppress image noise. These peaks are then detected by amplitude thresholding. The frequency band width and the subsequent spatial filter mask size are variable parameters to facilitate detection of target objects of different sizes under known imaging geometries. Many military objects, such as trucks, tanks and missile launchers, produce definite signatures with parallel lines and the algorithm proves to be ideal for detecting such objects. Moreover, shadow-casting objects generally provide sharp edges and are readily detected. The block operation procedure offers advantages of significant reduction in noise influence, improved edge detection, faster processing speed and versatility to detect diverse objects of different sizes in the image. With Scud missile launcher replicas as target objects, the method has been successfully tested on terrain board test images under different backgrounds, illumination and imaging geometries with cameras of differing spatial resolution and bit-depth.

Call sign intelligibility improvement using a spatial auditory display

NASA Technical Reports Server (NTRS)

Begault, Durand R.

1994-01-01

A spatial auditory display was designed for separating the multiple communication channels usually heard over one ear to different virtual auditory positions. The single 19 foot rack mount device utilizes digital filtering algorithms to separate up to four communication channels. The filters use four different binaural transfer functions, synthesized from actual outer ear measurements, to impose localization cues on the incoming sound. Hardware design features include 'fail-safe' operation in the case of power loss, and microphone/headset interfaces to the mobile launch communication system in use at KSC. An experiment designed to verify the intelligibility advantage of the display used 130 different call signs taken from the communications protocol used at NASA KSC. A 6 to 7 dB intelligibility advantage was found when multiple channels were spatially displayed, compared to monaural listening. The findings suggest that the use of a spatial auditory display could enhance both occupational and operational safety and efficiency of NASA operations.

Intensity inhomogeneity compensation and tissue segmentation for magnetic resonance imaging with noise-suppressed multiplicative intrinsic component optimization

NASA Astrophysics Data System (ADS)

Dong, Huaipeng; Zhang, Qi; Shi, Jun

2017-12-01

Magnetic resonance (MR) images suffer from intensity inhomogeneity. Segmentation-based approaches can simultaneously achieve both intensity inhomogeneity compensation (IIC) and tissue segmentation for MR images with little noise, but they often fail for images polluted by severe noise. Here, we propose a noise-robust algorithm named noise-suppressed multiplicative intrinsic component optimization (NSMICO) for simultaneous IIC and tissue segmentation. Considering the spatial characteristics in an image, an adaptive nonlocal means filtering term is incorporated into the objective function of NSMICO to decrease image deterioration due to noise. Then, a fuzzy local factor term utilizing the spatial and gray-level relationship among local pixels is embedded into the objective function to reach a balance between noise suppression and detail preservation. Experimental results on synthetic natural and MR images with various levels of intensity inhomogeneity and noise, as well as in vivo clinical MR images, have demonstrated the effectiveness of the NSMICO and its superiority to three competing approaches. The NSMICO could be potentially valuable for MR image IIC and tissue segmentation.

Stimulus Type, Level of Categorization, and Spatial-Frequencies Utilization: Implications for Perceptual Categorization Hierarchies

ERIC Educational Resources Information Center

Harel, Assaf; Bentin, Shlomo

2009-01-01

The type of visual information needed for categorizing faces and nonface objects was investigated by manipulating spatial frequency scales available in the image during a category verification task addressing basic and subordinate levels. Spatial filtering had opposite effects on faces and airplanes that were modulated by categorization level. The…

The Role of Low-Spatial Frequencies in Lexical Decision and Masked Priming

ERIC Educational Resources Information Center

Boden, C.; Giaschi, D.

2009-01-01

Spatial frequency filtering was used to test the hypotheses that low-spatial frequency information in printed text can: (1) lead to a rapid lexical decision or (2) facilitate word recognition. Adult proficient readers made lexical decisions in unprimed and masked repetition priming experiments with unfiltered, low-pass, high-pass and notch…

Generating a taxonomy of spatially cued attention for visual discrimination: Effects of judgment precision and set size on attention

PubMed Central

Hetley, Richard; Dosher, Barbara Anne; Lu, Zhong-Lin

2014-01-01

Attention precues improve the performance of perceptual tasks in many but not all circumstances. These spatial attention effects may depend upon display set size or workload, and have been variously attributed to external noise filtering, stimulus enhancement, contrast gain, or response gain, or to uncertainty or other decision effects. In this study, we document systematically different effects of spatial attention in low- and high-precision judgments, with and without external noise, and in different set sizes in order to contribute to the development of a taxonomy of spatial attention. An elaborated perceptual template model (ePTM) provides an integrated account of a complex set of effects of spatial attention with just two attention factors: a set-size dependent exclusion or filtering of external noise and a narrowing of the perceptual template to focus on the signal stimulus. These results are related to the previous literature by classifying the judgment precision and presence of external noise masks in those experiments, suggesting a taxonomy of spatially cued attention in discrimination accuracy. PMID:24939234

Generating a taxonomy of spatially cued attention for visual discrimination: effects of judgment precision and set size on attention.

PubMed

Hetley, Richard; Dosher, Barbara Anne; Lu, Zhong-Lin

2014-11-01

Attention precues improve the performance of perceptual tasks in many but not all circumstances. These spatial attention effects may depend upon display set size or workload, and have been variously attributed to external noise filtering, stimulus enhancement, contrast gain, or response gain, or to uncertainty or other decision effects. In this study, we document systematically different effects of spatial attention in low- and high-precision judgments, with and without external noise, and in different set sizes in order to contribute to the development of a taxonomy of spatial attention. An elaborated perceptual template model (ePTM) provides an integrated account of a complex set of effects of spatial attention with just two attention factors: a set-size dependent exclusion or filtering of external noise and a narrowing of the perceptual template to focus on the signal stimulus. These results are related to the previous literature by classifying the judgment precision and presence of external noise masks in those experiments, suggesting a taxonomy of spatially cued attention in discrimination accuracy.

Optical high-resolution analysis of rotational movement: testing circular spatial filter velocimetry (CSFV) with rotating biological cells

NASA Astrophysics Data System (ADS)

Schaeper, M.; Schmidt, R.; Kostbade, R.; Damaschke, N.; Gimsa, J.

2016-07-01

Circular spatial filtering velocimetry (CSFV) was tested during the microscopic registration of the individual rotations of baker’s yeast cells. Their frequency-dependent rotation (electrorotation; ER) was induced in rotating electric fields, which were generated in a glass chip chamber with four electrodes (600 μm tip-to-tip distance). The electrodes were driven with sinusoidal quadrature signals of 5 or 8 V PP with frequencies up to 3 MHz. The observed cell rotation was of the order of 1-100 s per revolution. At each measuring frequency, the independent rotations of up to 20 cells were simultaneously recorded with a high-speed camera. CSFV was software-implemented using circular spatial filters with harmonic gratings. ER was proportional to the phase shift between the values of the spatial filtering signal of consecutive frames. ER spectra obtained by CSFV from the rotation velocities at different ER-field frequencies agreed well with manual measurements and theoretical spectra. Oscillations in the rotation velocity of a single cell in the elliptically polarized field near an electrode, which were resolved by CSFV, could not be visually discerned. ER step responses after field-on were recorded at 2500 frames per second. Analysis proved the high temporal resolution of CSFV and revealed a largely linear torque-friction relation during the acceleration phase of ER. Future applications of CSFV will allow for the simple and cheap automated high-resolution analysis of rotational movements where mechanical detection has too low a resolution or is not possible, e.g. in polluted environments or for gas and fluid vortices, microscopic objects, etc.

Three filters for visualization of phase objects with large variations of phase gradients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sagan, Arkadiusz; Antosiewicz, Tomasz J.; Szoplik, Tomasz

2009-02-20

We propose three amplitude filters for visualization of phase objects. They interact with the spectra of pure-phase objects in the frequency plane and are based on tangent and error functions as well as antisymmetric combination of square roots. The error function is a normalized form of the Gaussian function. The antisymmetric square-root filter is composed of two square-root filters to widen its spatial frequency spectral range. Their advantage over other known amplitude frequency-domain filters, such as linear or square-root graded ones, is that they allow high-contrast visualization of objects with large variations of phase gradients.

Symmetric Phase-Only Filtering in Particle-Image Velocimetry

NASA Technical Reports Server (NTRS)

Wemet, Mark P.

2008-01-01

Symmetrical phase-only filtering (SPOF) can be exploited to obtain substantial improvements in the results of data processing in particle-image velocimetry (PIV). In comparison with traditional PIV data processing, SPOF PIV data processing yields narrower and larger amplitude correlation peaks, thereby providing more-accurate velocity estimates. The higher signal-to-noise ratios associated with the higher amplitude correlation peaks afford greater robustness and reliability of processing. SPOF also affords superior performance in the presence of surface flare light and/or background light. SPOF algorithms can readily be incorporated into pre-existing algorithms used to process digitized image data in PIV, without significantly increasing processing times. A summary of PIV and traditional PIV data processing is prerequisite to a meaningful description of SPOF PIV processing. In PIV, a pulsed laser is used to illuminate a substantially planar region of a flowing fluid in which particles are entrained. An electronic camera records digital images of the particles at two instants of time. The components of velocity of the fluid in the illuminated plane can be obtained by determining the displacements of particles between the two illumination pulses. The objective in PIV data processing is to compute the particle displacements from the digital image data. In traditional PIV data processing, to which the present innovation applies, the two images are divided into a grid of subregions and the displacements determined from cross-correlations between the corresponding sub-regions in the first and second images. The cross-correlation process begins with the calculation of the Fourier transforms (or fast Fourier transforms) of the subregion portions of the images. The Fourier transforms from the corresponding subregions are multiplied, and this product is inverse Fourier transformed, yielding the cross-correlation intensity distribution. The average displacement of the particles across a subregion results in a displacement of the correlation peak from the center of the correlation plane. The velocity is then computed from the displacement of the correlation peak and the time between the recording of the two images. The process as described thus far is performed for all the subregions. The resulting set of velocities in grid cells amounts to a velocity vector map of the flow field recorded on the image plane. In traditional PIV processing, surface flare light and bright background light give rise to a large, broad correlation peak, at the center of the correlation plane, that can overwhelm the true particle- displacement correlation peak. This has made it necessary to resort to tedious image-masking and background-subtraction procedures to recover the relatively small amplitude particle-displacement correlation peak. SPOF is a variant of phase-only filtering (POF), which, in turn, is a variant of matched spatial filtering (MSF). In MSF, one projects a first image (denoted the input image) onto a second image (denoted the filter) as part of a computation to determine how much and what part of the filter is present in the input image. MSF is equivalent to cross-correlation. In POF, the frequency-domain content of the MSF filter is modified to produce a unitamplitude (phase-only) object. POF is implemented by normalizing the Fourier transform of the filter by its magnitude. The advantage of POFs is that they yield correlation peaks that are sharper and have higher signal-to-noise ratios than those obtained through traditional MSF. In the SPOF, these benefits of POF can be extended to PIV data processing. The SPOF yields even better performance than the POF approach, which is uniquely applicable to PIV type image data. In SPOF as now applied to PIV data processing, a subregion of the first image is treated as the input image and the corresponding subregion of the second image is treated as the filter. The Fourier transforms from both the firs and second- image subregions are normalized by the square roots of their respective magnitudes. This scheme yields optimal performance because the amounts of normalization applied to the spatial-frequency contents of the input and filter scenes are just enough to enhance their high-spatial-frequency contents while reducing their spurious low-spatial-frequency content. As a result, in SPOF PIV processing, particle-displacement correlation peaks can readily be detected above spurious background peaks, without need for masking or background subtraction.

Recording multiple spatially-heterodyned direct to digital holograms in one digital image

DOEpatents

Hanson, Gregory R [Clinton, TN; Bingham, Philip R [Knoxville, TN

2008-03-25

Systems and methods are described for recording multiple spatially-heterodyned direct to digital holograms in one digital image. A method includes digitally recording, at a first reference beam-object beam angle, a first spatially-heterodyned hologram including spatial heterodyne fringes for Fourier analysis; Fourier analyzing the recorded first spatially-heterodyned hologram by shifting a first original origin of the recorded first spatially-heterodyned hologram to sit on top of a first spatial-heterodyne carrier frequency defined by the first reference beam-object beam angle; digitally recording, at a second reference beam-object beam angle, a second spatially-heterodyned hologram including spatial heterodyne fringes for Fourier analysis; Fourier analyzing the recorded second spatially-heterodyned hologram by shifting a second original origin of the recorded second spatially-heterodyned hologram to sit on top of a second spatial-heterodyne carrier frequency defined by the second reference beam-object beam angle; applying a first digital filter to cut off signals around the first original origin and define a first result; performing a first inverse Fourier transform on the first result; applying a second digital filter to cut off signals around the second original origin and define a second result; and performing a second inverse Fourier transform on the second result, wherein the first reference beam-object beam angle is not equal to the second reference beam-object beam angle and a single digital image includes both the first spatially-heterodyned hologram and the second spatially-heterodyned hologram.

Early and Late Retrieval of the ALN Removable Vena Cava Filter: Results from a Multicenter Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pellerin, O., E-mail: olivier.pellerin@egp.aphp.f; Barral, F. G.; Lions, C.

Retrieval of removable inferior vena cava (IVC) filters in selected patients is widely practiced. The purpose of this multicenter study was to evaluate the feasibility and results of percutaneous removal of the ALN removable filter in a large patient cohort. Between November 2003 and June 2006, 123 consecutive patients were referred for percutaneous extraction of the ALN filter at three centers. The ALN filter is a removable filter that can be implanted through a femoral/jugular vein approach and extracted by the jugular vein approach. Filter removal was attempted after an implantation period of 93 {+-} 15 days (range, 6-722 days)more » through the right internal jugular vein approach using the dedicated extraction kit after control inferior vena cavography. Following filter removal, vena cavograms were obtained in all patients. Successful extraction was achieved in all but one case. Among these successful retrievals, additional manipulation using a femoral approach was needed when the apex of the filter was close to the IVC wall in two patients. No immediate IVC complications were observed according to the postimplantation cavography. Neither technical nor clinical differences between early and late filter retrieval were noticed. Our data confirm the safety of ALN filter retrieval up to 722 days after implantation. In infrequent cases, additional endovenous filter manipulation is needed to facilitate extraction.« less

A Hybrid Circuit for Spoof Surface Plasmons and Spatial Waveguide Modes to Reach Controllable Band-Pass Filters

PubMed Central

Zhang, Qian; Zhang, Hao Chi; Wu, Han; Cui, Tie Jun

2015-01-01

We propose a hybrid circuit for spoof surface plasmon polaritons (SPPs) and spatial waveguide modes to develop new microwave devices. The hybrid circuit includes a spoof SPP waveguide made of two anti-symmetric corrugated metallic strips and a traditional substrate integrated waveguide (SIW). From dispersion relations, we show that the electromagnetic waves only can propagate through the hybrid circuit when the operating frequency is less than the cut-off frequency of the SPP waveguide and greater than the cut-off frequency of SIW, generating efficient band-pass filters. We demonstrate that the pass band is controllable in a large range by designing the geometrical parameters of SPP waveguide and SIW. Full-wave simulations are provided to show the large adjustability of filters, including ultra wideband and narrowband filters. We fabricate a sample of the new hybrid device in the microwave frequencies, and measurement results have excellent agreements to numerical simulations, demonstrating excellent filtering characteristics such as low loss, high efficiency, and good square ratio. The proposed hybrid circuit gives important potential to accelerate the development of plasmonic integrated functional devices and circuits in both microwave and terahertz frequencies. PMID:26552584

A Hybrid Circuit for Spoof Surface Plasmons and Spatial Waveguide Modes to Reach Controllable Band-Pass Filters.

PubMed

Zhang, Qian; Zhang, Hao Chi; Wu, Han; Cui, Tie Jun

2015-11-10

We propose a hybrid circuit for spoof surface plasmon polaritons (SPPs) and spatial waveguide modes to develop new microwave devices. The hybrid circuit includes a spoof SPP waveguide made of two anti-symmetric corrugated metallic strips and a traditional substrate integrated waveguide (SIW). From dispersion relations, we show that the electromagnetic waves only can propagate through the hybrid circuit when the operating frequency is less than the cut-off frequency of the SPP waveguide and greater than the cut-off frequency of SIW, generating efficient band-pass filters. We demonstrate that the pass band is controllable in a large range by designing the geometrical parameters of SPP waveguide and SIW. Full-wave simulations are provided to show the large adjustability of filters, including ultra wideband and narrowband filters. We fabricate a sample of the new hybrid device in the microwave frequencies, and measurement results have excellent agreements to numerical simulations, demonstrating excellent filtering characteristics such as low loss, high efficiency, and good square ratio. The proposed hybrid circuit gives important potential to accelerate the development of plasmonic integrated functional devices and circuits in both microwave and terahertz frequencies.

Spatio-spectral color filter array design for optimal image recovery.

PubMed

Hirakawa, Keigo; Wolfe, Patrick J

2008-10-01

In digital imaging applications, data are typically obtained via a spatial subsampling procedure implemented as a color filter array-a physical construction whereby only a single color value is measured at each pixel location. Owing to the growing ubiquity of color imaging and display devices, much recent work has focused on the implications of such arrays for subsequent digital processing, including in particular the canonical demosaicking task of reconstructing a full color image from spatially subsampled and incomplete color data acquired under a particular choice of array pattern. In contrast to the majority of the demosaicking literature, we consider here the problem of color filter array design and its implications for spatial reconstruction quality. We pose this problem formally as one of simultaneously maximizing the spectral radii of luminance and chrominance channels subject to perfect reconstruction, and-after proving sub-optimality of a wide class of existing array patterns-provide a constructive method for its solution that yields robust, new panchromatic designs implementable as subtractive colors. Empirical evaluations on multiple color image test sets support our theoretical results, and indicate the potential of these patterns to increase spatial resolution for fixed sensor size, and to contribute to improved reconstruction fidelity as well as significantly reduced hardware complexity.

Online EEG artifact removal for BCI applications by adaptive spatial filtering.

PubMed

Guarnieri, Roberto; Marino, Marco; Barban, Federico; Ganzetti, Marco; Mantini, Dante

2018-06-28

The performance of brain computer interfaces (BCIs) based on electroencephalography (EEG) data strongly depends on the effective attenuation of artifacts that are mixed in the recordings. To address this problem, we have developed a novel online EEG artifact removal method for BCI applications, which combines blind source separation (BSS) and regression (REG) analysis. The BSS-REG method relies on the availability of a calibration dataset of limited duration for the initialization of a spatial filter using BSS. Online artifact removal is implemented by dynamically adjusting the spatial filter in the actual experiment, based on a linear regression technique. Our results showed that the BSS-REG method is capable of attenuating different kinds of artifacts, including ocular and muscular, while preserving true neural activity. Thanks to its low computational requirements, BSS-REG can be applied to low-density as well as high-density EEG data. We argue that BSS-REG may enable the development of novel BCI applications requiring high-density recordings, such as source-based neurofeedback and closed-loop neuromodulation. © 2018 IOP Publishing Ltd.

Three-dimensional imaging in degraded visual field

NASA Astrophysics Data System (ADS)

Oran, A.; Ozharar, S.; Ozdur, I.

2016-04-01

Imaging at degraded visual environments is one of the biggest challenges in today’s imaging technologies. Especially military and commercial rotary wing aviation is suffering from impaired visual field in sandy, dusty, marine and snowy environments. For example during landing the rotor churns up the particles and creates dense clouds of highly scattering medium, which limits the vision of the pilot and may result in an uncontrolled landing. The vision in such environments is limited because of the high ratio of scattered photons over the ballistic photons which have the image information. We propose to use optical spatial filtering (OSF) method in order to eliminate the scattered photons and only collect the ballistic photons at the receiver. OSF is widely used in microscopy, to the best of our knowledge this will be the first application of OSF for macroscopic imaging. Our experimental results show that most of the scattered photons are eliminated using the spatial filtering in a highly scattering impaired visual field. The results are compared with a standard broad area photo detector which shows the effectiveness of spatial filtering.

Studies on spatio-temporal filtering of GNSS-derived coordinates

NASA Astrophysics Data System (ADS)

Gruszczynski, Maciej; Bogusz, Janusz; Kłos, Anna; Figurski, Mariusz

2015-04-01

The information about lithospheric deformations may be obtained nowadays by analysis of velocity field derived from permanent GNSS (Global Navigation Satellite System) observations. Despite developing more and more reliable models, the permanent stations residuals must still be considered as coloured noise. Meeting the GGOS (Global Geodetic Observing System) requirements, we are obliged to investigate the correlations between residuals, which are the result of common mode error (CME). This type of error may arise from mismodelling of: satellite orbits, the Earth Orientation Parameters, satellite antenna phase centre variations or unmodelling of large scale atmospheric effects. The above described together cause correlations between stochastic parts of coordinate time series obtained at stations located of even few thousands kilometres from each other. Permanent stations that meet the aforementioned terms form the regional (EPN - EUREF Permanent Network) or local sub-networks of global (IGS - International GNSS Service) network. Other authors (Wdowinski et al., 1997; Dong et al., 2006) dealt with spatio-temporal filtering and indicated three major regional filtering approaches: the stacking, the Principal Component Analysis (PCA) based on the empirical orthogonal function and the Karhunen-Loeve expansion. The need for spatio-temporal filtering is evident today, but the question whether the size of the network affects the accuracy of station's position and its velocity still remains unanswered. With the aim to determine the network's size, for which the assumption of spatial uniform distribution of CME is retained, we used stacking approach. We analyzed time series of IGS stations with daily network solutions processed by the Military University of Technology EPN Local Analysis Centre in Bernese 5.0 software and compared it with the JPL (Jet Propulsion Laboratory) PPP (Precice Point Positioning). The method we propose is based on the division of local GNSS networks into concentric ring-shaped areas. Such an approach allows us to specify the maximum size of the network, where the evident uniform spatial response can be still noticed. In terms of reliable CMEs extraction, the local networks have to be up to 500-600 kilometres extent depending on its character (location). In this study we examined three approaches of spatio-temporal filtering based on stacking procedure. First was based on non-weighted (Wdowinski et. al., 1997) and second on weighted average formula, where the weights are formed by the RMS of individual station position in the corresponding epoch (Nikolaidis, 2002). The third stacking approach, proposed here, was previously unused. It combines the weighted stacking together with the distance between the station and network barycentre into one approach. The analysis allowed to determine the optimal size of local GNSS network and to select the appropriate stacking method for obtaining the most stable solutions for e.g. geodynamical studies. The values of L1 and L2 norms, RMS values of time series (describing stability of the time series) and Pearson correlation coefficients were calculated for the North, East and Up components from more than 200 permanent stations twice: before performing the filtration and after weighted stacking approach. We showed the improvement in the quality of time series analysis using MLE (Maximum Likelihood Estimation) to estimate noise parameters. We demonstrated that the relative RMS improvement of 10, 20 and 30% reduces the noise amplitudes of about 20, 35 and 45%, respectively, what causes the velocity uncertainty to be reduced of 0.3 mm/yr (for the assumption of 7-years of data and flicker noise). The relative decrement of spectral index kappa is 25, 35 and 45%, what means lower velocity uncertainty of even 0.2 mm/yr (when assuming 7 years of data and noise amplitude of 15 mm/yr^-kappa/4) . These results refer to the growing demands on the stability of the series due to their use to realize the kinematic reference frames and for geodynamical studies.

Regional climate model sensitivity to domain size

NASA Astrophysics Data System (ADS)

Leduc, Martin; Laprise, René

2009-05-01

Regional climate models are increasingly used to add small-scale features that are not present in their lateral boundary conditions (LBC). It is well known that the limited area over which a model is integrated must be large enough to allow the full development of small-scale features. On the other hand, integrations on very large domains have shown important departures from the driving data, unless large scale nudging is applied. The issue of domain size is studied here by using the “perfect model” approach. This method consists first of generating a high-resolution climatic simulation, nicknamed big brother (BB), over a large domain of integration. The next step is to degrade this dataset with a low-pass filter emulating the usual coarse-resolution LBC. The filtered nesting data (FBB) are hence used to drive a set of four simulations (LBs for Little Brothers), with the same model, but on progressively smaller domain sizes. The LB statistics for a climate sample of four winter months are compared with BB over a common region. The time average (stationary) and transient-eddy standard deviation patterns of the LB atmospheric fields generally improve in terms of spatial correlation with the reference (BB) when domain gets smaller. The extraction of the small-scale features by using a spectral filter allows detecting important underestimations of the transient-eddy variability in the vicinity of the inflow boundary, which can penalize the use of small domains (less than 100 × 100 grid points). The permanent “spatial spin-up” corresponds to the characteristic distance that the large-scale flow needs to travel before developing small-scale features. The spin-up distance tends to grow in size at higher levels in the atmosphere.

Absorbed dose-to-water protocol applied to synchrotron-generated x-rays at very high dose rates

NASA Astrophysics Data System (ADS)

Fournier, P.; Crosbie, J. C.; Cornelius, I.; Berkvens, P.; Donzelli, M.; Clavel, A. H.; Rosenfeld, A. B.; Petasecca, M.; Lerch, M. L. F.; Bräuer-Krisch, E.

2016-07-01

Microbeam radiation therapy (MRT) is a new radiation treatment modality in the pre-clinical stage of development at the ID17 Biomedical Beamline of the European synchrotron radiation facility (ESRF) in Grenoble, France. MRT exploits the dose volume effect that is made possible through the spatial fractionation of the high dose rate synchrotron-generated x-ray beam into an array of microbeams. As an important step towards the development of a dosimetry protocol for MRT, we have applied the International Atomic Energy Agency’s TRS 398 absorbed dose-to-water protocol to the synchrotron x-ray beam in the case of the broad beam irradiation geometry (i.e. prior to spatial fractionation into microbeams). The very high dose rates observed here mean the ion recombination correction factor, k s , is the most challenging to quantify of all the necessary corrections to apply for ionization chamber based absolute dosimetry. In the course of this study, we have developed a new method, the so called ‘current ramping’ method, to determine k s for the specific irradiation and filtering conditions typically utilized throughout the development of MRT. Using the new approach we deduced an ion recombination correction factor of 1.047 for the maximum ESRF storage ring current (200 mA) under typical beam spectral filtering conditions in MRT. MRT trials are currently underway with veterinary patients at the ESRF that require additional filtering, and we have estimated a correction factor of 1.025 for these filtration conditions for the same ESRF storage ring current. The protocol described herein provides reference dosimetry data for the associated Treatment Planning System utilized in the current veterinary trials and anticipated future human clinical trials.

Weighted hybrid technique for recommender system

NASA Astrophysics Data System (ADS)

Suriati, S.; Dwiastuti, Meisyarah; Tulus, T.

2017-12-01

Recommender system becomes very popular and has important role in an information system or webpages nowadays. A recommender system tries to make a prediction of which item a user may like based on his activity on the system. There are some familiar techniques to build a recommender system, such as content-based filtering and collaborative filtering. Content-based filtering does not involve opinions from human to make the prediction, while collaborative filtering does, so collaborative filtering can predict more accurately. However, collaborative filtering cannot give prediction to items which have never been rated by any user. In order to cover the drawbacks of each approach with the advantages of other approach, both approaches can be combined with an approach known as hybrid technique. Hybrid technique used in this work is weighted technique in which the prediction score is combination linear of scores gained by techniques that are combined.The purpose of this work is to show how an approach of weighted hybrid technique combining content-based filtering and item-based collaborative filtering can work in a movie recommender system and to show the performance comparison when both approachare combined and when each approach works alone. There are three experiments done in this work, combining both techniques with different parameters. The result shows that the weighted hybrid technique that is done in this work does not really boost the performance up, but it helps to give prediction score for unrated movies that are impossible to be recommended by only using collaborative filtering.

Least-mean-square spatial filter for IR sensors.

PubMed

Takken, E H; Friedman, D; Milton, A F; Nitzberg, R

1979-12-15

A new least-mean-square filter is defined for signal-detection problems. The technique is proposed for scanning IR surveillance systems operating in poorly characterized but primarily low-frequency clutter interference. Near-optimal detection of point-source targets is predicted both for continuous-time and sampled-data systems.

Acousto-Optic Tunable Filter Hyperspectral Microscope Imaging Method for Characterizing Spectra from Foodborne Pathogens.

USDA-ARS?s Scientific Manuscript database

Hyperspectral microscope imaging (HMI) method, which provides both spatial and spectral characteristics of samples, can be effective for foodborne pathogen detection. The acousto-optic tunable filter (AOTF)-based HMI method can be used to characterize spectral properties of biofilms formed by Salmon...

Three dimensional empirical mode decomposition analysis apparatus, method and article manufacture

NASA Technical Reports Server (NTRS)

Gloersen, Per (Inventor)

2004-01-01

An apparatus and method of analysis for three-dimensional (3D) physical phenomena. The physical phenomena may include any varying 3D phenomena such as time varying polar ice flows. A repesentation of the 3D phenomena is passed through a Hilbert transform to convert the data into complex form. A spatial variable is separated from the complex representation by producing a time based covariance matrix. The temporal parts of the principal components are produced by applying Singular Value Decomposition (SVD). Based on the rapidity with which the eigenvalues decay, the first 3-10 complex principal components (CPC) are selected for Empirical Mode Decomposition into intrinsic modes. The intrinsic modes produced are filtered in order to reconstruct the spatial part of the CPC. Finally, a filtered time series may be reconstructed from the first 3-10 filtered complex principal components.

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Realisation of video-frequency filters on the basis of a new mode of operation of an acousto-optical correlator with spatial integration

NASA Astrophysics Data System (ADS)

Ushakov, V. N.

1995-10-01

A video-frequency acousto-optical correlator with spatial integration, which widens the functional capabilities of correlation-type acousto-optical processors, is described. The correlator is based on a two-dimensional reference transparency and it can filter arbitrary video signals of spectral width limited by the pass band of an acousto-optical modulator. The calculated pulse characteristic is governed by the structure of the reference transparency. A procedure for the synthesis of this transparency is considered and experimental results are reported.

Bistatic passive radar simulator with spatial filtering subsystem

NASA Astrophysics Data System (ADS)

Hossa, Robert; Szlachetko, Boguslaw; Lewandowski, Andrzej; Górski, Maksymilian

2009-06-01

The purpose of this paper is to briefly introduce the structure and features of the developed virtual passive FM radar implemented in Matlab system of numerical computations and to present many alternative ways of its performance. An idea of the proposed solution is based on analytic representation of transmitted direct signals and reflected echo signals. As a spatial filtering subsystem a beamforming network of ULA and UCA dipole configuration dedicated to bistatic radar concept is considered and computationally efficient procedures are presented in details. Finally, exemplary results of the computer simulations of the elaborated virtual simulator are provided and discussed.

Laser system using regenerative amplifier

DOEpatents

Emmett, J.L.

1980-03-04

High energy laser system is disclosed using a regenerative amplifier, which relaxes all constraints on laser components other than the intrinsic damage level of matter, so as to enable use of available laser system components. This can be accomplished by use of segmented components, spatial filters, at least one amplifier using solid state or gaseous media, and separated reflector members providing a long round trip time through the regenerative cavity, thereby allowing slower switching and adequate time to clear the spatial filters, etc. The laser system simplifies component requirements and reduces component cost while providing high energy output. 10 figs.

Predicting the potential distribution of the amphibian pathogen Batrachochytrium dendrobatidis in East and Southeast Asia.

PubMed

Moriguchi, Sachiko; Tominaga, Atsushi; Irwin, Kelly J; Freake, Michael J; Suzuki, Kazutaka; Goka, Koichi

2015-04-08

Batrachochytrium dendrobatidis (Bd) is the pathogen responsible for chytridiomycosis, a disease that is associated with a worldwide amphibian population decline. In this study, we predicted the potential distribution of Bd in East and Southeast Asia based on limited occurrence data. Our goal was to design an effective survey area where efforts to detect the pathogen can be focused. We generated ecological niche models using the maximum-entropy approach, with alleviation of multicollinearity and spatial autocorrelation. We applied eigenvector-based spatial filters as independent variables, in addition to environmental variables, to resolve spatial autocorrelation, and compared the model's accuracy and the degree of spatial autocorrelation with those of a model estimated using only environmental variables. We were able to identify areas of high suitability for Bd with accuracy. Among the environmental variables, factors related to temperature and precipitation were more effective in predicting the potential distribution of Bd than factors related to land use and cover type. Our study successfully predicted the potential distribution of Bd in East and Southeast Asia. This information should now be used to prioritize survey areas and generate a surveillance program to detect the pathogen.

Ionospheric Correction of InSAR for Accurate Ice Motion Mapping at High Latitudes

NASA Astrophysics Data System (ADS)

Liao, H.; Meyer, F. J.

2016-12-01

Monitoring the motion of the large ice sheets is of great importance for determining ice mass balance and its contribution to sea level rise. Recently the first comprehensive ice motion of the Greenland and the Antarctica have been generated with InSAR. However, these studies have indicated that the performance of InSAR-based ice motion mapping is limited by the presence of the ionosphere. This is particularly true at high latitudes and for low-frequency SAR data. Filter-based and empirical methods (e.g., removing polynomials), which have often been used to mitigate ionospheric effects, are often ineffective in these areas due to the typically strong spatial variability of ionospheric phase delay in high latitudes and due to the risk of removing true deformation signals from the observations. In this study, we will first present an outline of our split-spectrum InSAR-based ionospheric correction approach and particularly highlight how our method improves upon published techniques, such as the multiple sub-band approach to boost estimation accuracy as well as advanced error correction and filtering algorithms. We applied our work flow to a large number of ionosphere-affected dataset over the large ice sheets to estimate the benefit of ionospheric correction on ice motion mapping accuracy. Appropriate test sites over Greenland and the Antarctic have been chosen through cooperation with authors (UW, Ian Joughin) of previous ice motion studies. To demonstrate the magnitude of ionospheric noise and to showcase the performance of ionospheric correction, we will show examples of ionospheric-affected InSAR data and our ionosphere corrected result for comparison in visual. We also compared the corrected phase data to known ice velocity fields quantitatively for the analyzed areas from experts in ice velocity mapping. From our studies we found that ionospheric correction significantly reduces biases in ice velocity estimates and boosts accuracy by a factor that depends on a set of system (range bandwidth, temporal and spatial baseline) and processing parameters (e.g., filtering strength and sub-band configuration). A case study in Greenland is attached below.

Consistency and similarity of MEG- and fMRI-signal time courses during movie viewing.

PubMed

Lankinen, Kaisu; Saari, Jukka; Hlushchuk, Yevhen; Tikka, Pia; Parkkonen, Lauri; Hari, Riitta; Koskinen, Miika

2018-06-01

Movie viewing allows human perception and cognition to be studied in complex, real-life-like situations in a brain-imaging laboratory. Previous studies with functional magnetic resonance imaging (fMRI) and with magneto- and electroencephalography (MEG and EEG) have demonstrated consistent temporal dynamics of brain activity across movie viewers. However, little is known about the similarities and differences of fMRI and MEG or EEG dynamics during such naturalistic situations. We thus compared MEG and fMRI responses to the same 15-min black-and-white movie in the same eight subjects who watched the movie twice during both MEG and fMRI recordings. We analyzed intra- and intersubject voxel-wise correlations within each imaging modality as well as the correlation of the MEG envelopes and fMRI signals. The fMRI signals showed voxel-wise within- and between-subjects correlations up to r = 0.66 and r = 0.37, respectively, whereas these correlations were clearly weaker for the envelopes of band-pass filtered (7 frequency bands below 100 Hz) MEG signals (within-subjects correlation r < 0.14 and between-subjects r < 0.05). Direct MEG-fMRI voxel-wise correlations were unreliable. Notably, applying a spatial-filtering approach to the MEG data uncovered consistent canonical variates that showed considerably stronger (up to r = 0.25) between-subjects correlations than the univariate voxel-wise analysis. Furthermore, the envelopes of the time courses of these variates up to about 10 Hz showed association with fMRI signals in a general linear model. Similarities between envelopes of MEG canonical variates and fMRI voxel time-courses were seen mostly in occipital, but also in temporal and frontal brain regions, whereas intra- and intersubject correlations for MEG and fMRI separately were strongest only in the occipital areas. In contrast to the conventional univariate analysis, the spatial-filtering approach was able to uncover associations between the MEG envelopes and fMRI time courses, shedding light on the similarities of hemodynamic and electromagnetic brain activities during movie viewing. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.