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

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.

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.

SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

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

Iliopoulos, AS; Sun, X; Floros, D

Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well asmore » histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial signal/noise variations. An efficient multi-scale computational mechanism is developed to curtail processing latency. Spatially adaptive filtering may impact subsequent processing tasks such as reconstruction and numerical gradient computations for deformable registration. NIH Grant No. R01-184173.« less

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.

High-Speed Incoming Infrared Target Detection by Fusion of Spatial and Temporal Detectors

PubMed Central

Kim, Sungho

2015-01-01

This paper presents a method for detecting high-speed incoming targets by the fusion of spatial and temporal detectors to achieve a high detection rate for an active protection system (APS). The incoming targets have different image velocities according to the target-camera geometry. Therefore, single-target detector-based approaches, such as a 1D temporal filter, 2D spatial filter and 3D matched filter, cannot provide a high detection rate with moderate false alarms. The target speed variation was analyzed according to the incoming angle and target velocity. The speed of the distant target at the firing time is almost stationary and increases slowly. The speed varying targets are detected stably by fusing the spatial and temporal filters. The stationary target detector is activated by an almost zero temporal contrast filter (TCF) and identifies targets using a spatial filter called the modified mean subtraction filter (M-MSF). A small motion (sub-pixel velocity) target detector is activated by a small TCF value and finds targets using the same spatial filter. A large motion (pixel-velocity) target detector works when the TCF value is high. The final target detection is terminated by fusing the three detectors based on the threat priority. The experimental results of the various target sequences show that the proposed fusion-based target detector produces the highest detection rate with an acceptable false alarm rate. PMID:25815448

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.

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.

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

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.

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.

Time-Domain Filtering for Spatial Large-Eddy Simulation

NASA Technical Reports Server (NTRS)

Pruett, C. David

1997-01-01

An approach to large-eddy simulation (LES) is developed whose subgrid-scale model incorporates filtering in the time domain, in contrast to conventional approaches, which exploit spatial filtering. The method is demonstrated in the simulation of a heated, compressible, axisymmetric jet, and results are compared with those obtained from fully resolved direct numerical simulation. The present approach was, in fact, motivated by the jet-flow problem and the desire to manipulate the flow by localized (point) sources for the purposes of noise suppression. Time-domain filtering appears to be more consistent with the modeling of point sources; moreover, time-domain filtering may resolve some fundamental inconsistencies associated with conventional space-filtered LES approaches.

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

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.

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.

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.

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.

Development of an adaptive bilateral filter for evaluating color image difference

NASA Astrophysics Data System (ADS)

Wang, Zhaohui; Hardeberg, Jon Yngve

2012-04-01

Spatial filtering, which aims to mimic the contrast sensitivity function (CSF) of the human visual system (HVS), has previously been combined with color difference formulae for measuring color image reproduction errors. These spatial filters attenuate imperceptible information in images, unfortunately including high frequency edges, which are believed to be crucial in the process of scene analysis by the HVS. The adaptive bilateral filter represents a novel approach, which avoids the undesirable loss of edge information introduced by CSF-based filtering. The bilateral filter employs two Gaussian smoothing filters in different domains, i.e., spatial domain and intensity domain. We propose a method to decide the parameters, which are designed to be adaptive to the corresponding viewing conditions, and the quantity and homogeneity of information contained in an image. Experiments and discussions are given to support the proposal. A series of perceptual experiments were conducted to evaluate the performance of our approach. The experimental sample images were reproduced with variations in six image attributes: lightness, chroma, hue, compression, noise, and sharpness/blurriness. The Pearson's correlation values between the model-predicted image difference and the observed difference were employed to evaluate the performance, and compare it with that of spatial CIELAB and image appearance model.

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.

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...

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.

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.

Generation of hollow Gaussian beams by spatial filtering

NASA Astrophysics Data System (ADS)

Liu, Zhengjun; Zhao, Haifa; Liu, Jianlong; Lin, Jie; Ashfaq Ahmad, Muhammad; Liu, Shutian

2007-08-01

We demonstrate that hollow Gaussian beams can be obtained from Fourier transform of the differentials of a Gaussian beam, and thus they can be generated by spatial filtering in the Fourier domain with spatial filters that consist of binomial combinations of even-order Hermite polynomials. A typical 4f optical system and a Michelson interferometer type system are proposed to implement the proposed scheme. Numerical results have proved the validity and effectiveness of this method. Furthermore, other polynomial Gaussian beams can also be generated by using this scheme. This approach is simple and may find significant applications in generating the dark hollow beams for nanophotonic technology.

Generation of hollow Gaussian beams by spatial filtering.

PubMed

Liu, Zhengjun; Zhao, Haifa; Liu, Jianlong; Lin, Jie; Ahmad, Muhammad Ashfaq; Liu, Shutian

2007-08-01

We demonstrate that hollow Gaussian beams can be obtained from Fourier transform of the differentials of a Gaussian beam, and thus they can be generated by spatial filtering in the Fourier domain with spatial filters that consist of binomial combinations of even-order Hermite polynomials. A typical 4f optical system and a Michelson interferometer type system are proposed to implement the proposed scheme. Numerical results have proved the validity and effectiveness of this method. Furthermore, other polynomial Gaussian beams can also be generated by using this scheme. This approach is simple and may find significant applications in generating the dark hollow beams for nanophotonic technology.

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.

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.

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.

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

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.

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.

On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure.

PubMed

Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Bao, Qiao

2017-05-11

Structural health monitoring (SHM) of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF) based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT) sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures.

On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure

PubMed Central

Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Bao, Qiao

2017-01-01

Structural health monitoring (SHM) of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF) based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT) sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures. PMID:28772879

Guided filter and principal component analysis hybrid method for hyperspectral pansharpening

NASA Astrophysics Data System (ADS)

Qu, Jiahui; Li, Yunsong; Dong, Wenqian

2018-01-01

Hyperspectral (HS) pansharpening aims to generate a fused HS image with high spectral and spatial resolution through integrating an HS image with a panchromatic (PAN) image. A guided filter (GF) and principal component analysis (PCA) hybrid HS pansharpening method is proposed. First, the HS image is interpolated and the PCA transformation is performed on the interpolated HS image. The first principal component (PC1) channel concentrates on the spatial information of the HS image. Different from the traditional PCA method, the proposed method sharpens the PAN image and utilizes the GF to obtain the spatial information difference between the HS image and the enhanced PAN image. Then, in order to reduce spectral and spatial distortion, an appropriate tradeoff parameter is defined and the spatial information difference is injected into the PC1 channel through multiplying by this tradeoff parameter. Once the new PC1 channel is obtained, the fused image is finally generated by the inverse PCA transformation. Experiments performed on both synthetic and real datasets show that the proposed method outperforms other several state-of-the-art HS pansharpening methods in both subjective and objective evaluations.

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.

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.

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.

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.

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.

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.

Classification of Hyperspectral Data Based on Guided Filtering and Random Forest

NASA Astrophysics Data System (ADS)

Ma, H.; Feng, W.; Cao, X.; Wang, L.

2017-09-01

Hyperspectral images usually consist of more than one hundred spectral bands, which have potentials to provide rich spatial and spectral information. However, the application of hyperspectral data is still challengeable due to "the curse of dimensionality". In this context, many techniques, which aim to make full use of both the spatial and spectral information, are investigated. In order to preserve the geometrical information, meanwhile, with less spectral bands, we propose a novel method, which combines principal components analysis (PCA), guided image filtering and the random forest classifier (RF). In detail, PCA is firstly employed to reduce the dimension of spectral bands. Secondly, the guided image filtering technique is introduced to smooth land object, meanwhile preserving the edge of objects. Finally, the features are fed into RF classifier. To illustrate the effectiveness of the method, we carry out experiments over the popular Indian Pines data set, which is collected by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. By comparing the proposed method with the method of only using PCA or guided image filter, we find that effect of the proposed method is better.

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.

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

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.

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.

Satellite image fusion based on principal component analysis and high-pass filtering.

PubMed

Metwalli, Mohamed R; Nasr, Ayman H; Allah, Osama S Farag; El-Rabaie, S; Abd El-Samie, Fathi E

2010-06-01

This paper presents an integrated method for the fusion of satellite images. Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution or simply high-resolution (HR) panchromatic (pan) images and low-resolution (LR) multi-spectral (MS) images. Image fusion methods are therefore required to integrate a high-spectral-resolution MS image with a high-spatial-resolution pan image to produce a pan-sharpened image with high spectral and spatial resolutions. Some image fusion methods such as the intensity, hue, and saturation (IHS) method, the principal component analysis (PCA) method, and the Brovey transform (BT) method provide HR MS images, but with low spectral quality. Another family of image fusion methods, such as the high-pass-filtering (HPF) method, operates on the basis of the injection of high frequency components from the HR pan image into the MS image. This family of methods provides less spectral distortion. In this paper, we propose the integration of the PCA method and the HPF method to provide a pan-sharpened MS image with superior spatial resolution and less spectral distortion. The experimental results show that the proposed fusion method retains the spectral characteristics of the MS image and, at the same time, improves the spatial resolution of the pan-sharpened image.

Crosstalk elimination in the detection of dual-beam optical tweezers by spatial filtering

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

Ott, Dino; Oddershede, Lene B., E-mail: oddershede@nbi.dk; Reihani, S. Nader S.

2014-05-15

In dual-beam optical tweezers, the accuracy of position and force measurements is often compromised by crosstalk between the two detected signals, this crosstalk leading to systematic and significant errors on the measured forces and distances. This is true both for dual-beam optical traps where the splitting of the two traps is done by polarization optics and for dual optical traps constructed by other methods, e.g., holographic tweezers. If the two traps are orthogonally polarized, most often crosstalk is minimized by inserting polarization optics in front of the detector; however, this method is not perfect because of the de-polarization of themore » trapping beam introduced by the required high numerical aperture optics. Here we present a simple and easy-to-implement method to efficiently eliminate crosstalk. The method is based on spatial filtering by simply inserting a pinhole at the correct position and is highly compatible with standard back focal plane photodiode based detection of position and force. Our spatial filtering method reduces crosstalk up to five times better than polarization filtering alone. The effectiveness is dependent on pinhole size and distance between the traps and is here quantified experimentally and reproduced by theoretical modeling. The method here proposed will improve the accuracy of force-distance measurements, e.g., of single molecules, performed by dual-beam optical traps and hence give much more scientific value for the experimental efforts.« less

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.

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

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.

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.

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.

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

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.

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.

A target detection multi-layer matched filter for color and hyperspectral cameras

NASA Astrophysics Data System (ADS)

Miyanishi, Tomoya; Preece, Bradley L.; Reynolds, Joseph P.

2018-05-01

In this article, a method for applying matched filters to a 3-dimentional hyperspectral data cube is discussed. In many applications, color visible cameras or hyperspectral cameras are used for target detection where the color or spectral optical properties of the imaged materials are partially known in advance. Therefore, the use of matched filtering with spectral data along with shape data is an effective method for detecting certain targets. Since many methods for 2D image filtering have been researched, we propose a multi-layer filter where ordinary spatially matched filters are used before the spectral filters. We discuss a way to layer the spectral filters for a 3D hyperspectral data cube, accompanied by a detectability metric for calculating the SNR of the filter. This method is appropriate for visible color cameras and hyperspectral cameras. We also demonstrate an analysis using the Night Vision Integrated Performance Model (NV-IPM) and a Monte Carlo simulation in order to confirm the effectiveness of the filtering in providing a higher output SNR and a lower false alarm rate.

Integrated narrowband optical filter based on embedded subwavelength resonant grating structures

DOEpatents

Grann, Eric B.; Sitter, Jr., David N.

2000-01-01

A resonant grating structure in a waveguide and methods of tuning the performance of the grating structure are described. An apparatus includes a waveguide; and a subwavelength resonant grating structure embedded in the waveguide. The systems and methods provide advantages including narrowband filtering capabilities, minimal sideband reflections, spatial control, high packing density, and tunability.

Compression of head-related transfer function using autoregressive-moving-average models and Legendre polynomials.

PubMed

Shekarchi, Sayedali; Hallam, John; Christensen-Dalsgaard, Jakob

2013-11-01

Head-related transfer functions (HRTFs) are generally large datasets, which can be an important constraint for embedded real-time applications. A method is proposed here to reduce redundancy and compress the datasets. In this method, HRTFs are first compressed by conversion into autoregressive-moving-average (ARMA) filters whose coefficients are calculated using Prony's method. Such filters are specified by a few coefficients which can generate the full head-related impulse responses (HRIRs). Next, Legendre polynomials (LPs) are used to compress the ARMA filter coefficients. LPs are derived on the sphere and form an orthonormal basis set for spherical functions. Higher-order LPs capture increasingly fine spatial details. The number of LPs needed to represent an HRTF, therefore, is indicative of its spatial complexity. The results indicate that compression ratios can exceed 98% while maintaining a spectral error of less than 4 dB in the recovered HRTFs.

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.

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

PubMed

Abu-Alqumsan, Mohammad; Peer, Angelika

2016-06-01

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. 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. 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. 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.

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.

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

Low-dose cone-beam CT via raw counts domain low-signal correction schemes: Performance assessment and task-based parameter optimization (Part II. Task-based parameter optimization).

PubMed

Gomez-Cardona, Daniel; Hayes, John W; Zhang, Ran; Li, Ke; Cruz-Bastida, Juan Pablo; Chen, Guang-Hong

2018-05-01

Different low-signal correction (LSC) methods have been shown to efficiently reduce noise streaks and noise level in CT to provide acceptable images at low-radiation dose levels. These methods usually result in CT images with highly shift-variant and anisotropic spatial resolution and noise, which makes the parameter optimization process highly nontrivial. The purpose of this work was to develop a local task-based parameter optimization framework for LSC methods. Two well-known LSC methods, the adaptive trimmed mean (ATM) filter and the anisotropic diffusion (AD) filter, were used as examples to demonstrate how to use the task-based framework to optimize filter parameter selection. Two parameters, denoted by the set P, for each LSC method were included in the optimization problem. For the ATM filter, these parameters are the low- and high-signal threshold levels p l and p h ; for the AD filter, the parameters are the exponents δ and γ in the brightness gradient function. The detectability index d' under the non-prewhitening (NPW) mathematical observer model was selected as the metric for parameter optimization. The optimization problem was formulated as an unconstrained optimization problem that consisted of maximizing an objective function d'(P), where i and j correspond to the i-th imaging task and j-th spatial location, respectively. Since there is no explicit mathematical function to describe the dependence of d' on the set of parameters P for each LSC method, the optimization problem was solved via an experimentally measured d' map over a densely sampled parameter space. In this work, three high-contrast-high-frequency discrimination imaging tasks were defined to explore the parameter space of each of the LSC methods: a vertical bar pattern (task I), a horizontal bar pattern (task II), and a multidirectional feature (task III). Two spatial locations were considered for the analysis, a posterior region-of-interest (ROI) located within the noise streaks region and an anterior ROI, located further from the noise streaks region. Optimal results derived from the task-based detectability index metric were compared to other operating points in the parameter space with different noise and spatial resolution trade-offs. The optimal operating points determined through the d' metric depended on the interplay between the major spatial frequency components of each imaging task and the highly shift-variant and anisotropic noise and spatial resolution properties associated with each operating point in the LSC parameter space. This interplay influenced imaging performance the most when the major spatial frequency component of a given imaging task coincided with the direction of spatial resolution loss or with the dominant noise spatial frequency component; this was the case of imaging task II. The performance of imaging tasks I and III was influenced by this interplay in a smaller scale than imaging task II, since the major frequency component of task I was perpendicular to imaging task II, and because imaging task III did not have strong directional dependence. For both LSC methods, there was a strong dependence of the overall d' magnitude and shape of the contours on the spatial location within the phantom, particularly for imaging tasks II and III. The d' value obtained at the optimal operating point for each spatial location and imaging task was similar when comparing the LSC methods studied in this work. A local task-based detectability framework to optimize the selection of parameters for LSC methods was developed. The framework takes into account the potential shift-variant and anisotropic spatial resolution and noise properties to maximize the imaging performance of the CT system. Optimal parameters for a given LSC method depend strongly on the spatial location within the image object. © 2018 American Association of Physicists in Medicine.

Reconstructing Spectral Scenes Using Statistical Estimation to Enhance Space Situational Awareness

DTIC Science & Technology

2006-12-01

simultane- ously spatially and spectrally deblur the images collected from ASIS. The algorithms are based on proven estimation theories and do not...collected with any system using a filtering technology known as Electronic Tunable Filters (ETFs). Previous methods to deblur spectral images collected...spectrally deblurring then the previously investigated methods. This algorithm expands on a method used for increasing the spectral resolution in gamma-ray

Interactions between pre-processing and classification methods for event-related-potential classification: best-practice guidelines for brain-computer interfacing.

PubMed

Farquhar, J; Hill, N J

2013-04-01

Detecting event related potentials (ERPs) from single trials is critical to the operation of many stimulus-driven brain computer interface (BCI) systems. The low strength of the ERP signal compared to the noise (due to artifacts and BCI irrelevant brain processes) makes this a challenging signal detection problem. Previous work has tended to focus on how best to detect a single ERP type (such as the visual oddball response). However, the underlying ERP detection problem is essentially the same regardless of stimulus modality (e.g., visual or tactile), ERP component (e.g., P300 oddball response, or the error-potential), measurement system or electrode layout. To investigate whether a single ERP detection method might work for a wider range of ERP BCIs we compare detection performance over a large corpus of more than 50 ERP BCI datasets whilst systematically varying the electrode montage, spectral filter, spatial filter and classifier training methods. We identify an interesting interaction between spatial whitening and regularised classification which made detection performance independent of the choice of spectral filter low-pass frequency. Our results show that pipeline consisting of spectral filtering, spatial whitening, and regularised classification gives near maximal performance in all cases. Importantly, this pipeline is simple to implement and completely automatic with no expert feature selection or parameter tuning required. Thus, we recommend this combination as a "best-practice" method for ERP detection problems.

MRI-guided brain PET image filtering and partial volume correction

NASA Astrophysics Data System (ADS)

Yan, Jianhua; Chu-Shern Lim, Jason; Townsend, David W.

2015-02-01

Positron emission tomography (PET) image quantification is a challenging problem due to limited spatial resolution of acquired data and the resulting partial volume effects (PVE), which depend on the size of the structure studied in relation to the spatial resolution and which may lead to over or underestimation of the true tissue tracer concentration. In addition, it is usually necessary to perform image smoothing either during image reconstruction or afterwards to achieve a reasonable signal-to-noise ratio. Typically, an isotropic Gaussian filtering (GF) is used for this purpose. However, the noise suppression is at the cost of deteriorating spatial resolution. As hybrid imaging devices such as PET/MRI have become available, the complementary information derived from high definition morphologic images could be used to improve the quality of PET images. In this study, first of all, we propose an MRI-guided PET filtering method by adapting a recently proposed local linear model and then incorporate PVE into the model to get a new partial volume correction (PVC) method without parcellation of MRI. In addition, both the new filtering and PVC are voxel-wise non-iterative methods. The performance of the proposed methods were investigated with simulated dynamic FDG brain dataset and 18F-FDG brain data of a cervical cancer patient acquired with a simultaneous hybrid PET/MR scanner. The initial simulation results demonstrated that MRI-guided PET image filtering can produce less noisy images than traditional GF and bias and coefficient of variation can be further reduced by MRI-guided PET PVC. Moreover, structures can be much better delineated in MRI-guided PET PVC for real brain data.

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.

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

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

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.

Preconditioner-free Wiener filtering with a dense noise matrix

NASA Astrophysics Data System (ADS)

Huffenberger, Kevin M.

2018-05-01

This work extends the Elsner & Wandelt (2013) iterative method for efficient, preconditioner-free Wiener filtering to cases in which the noise covariance matrix is dense, but can be decomposed into a sum whose parts are sparse in convenient bases. The new method, which uses multiple messenger fields, reproduces Wiener-filter solutions for test problems, and we apply it to a case beyond the reach of the Elsner & Wandelt (2013) method. We compute the Wiener-filter solution for a simulated Cosmic Microwave Background (CMB) map that contains spatially varying, uncorrelated noise, isotropic 1/f noise, and large-scale horizontal stripes (like those caused by atmospheric noise). We discuss simple extensions that can filter contaminated modes or inverse-noise-filter the data. These techniques help to address complications in the noise properties of maps from current and future generations of ground-based Microwave Background experiments, like Advanced ACTPol, Simons Observatory, and CMB-S4.

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

PubMed

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

2016-12-01

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. 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. 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. 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.

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.

Nonlinear spatio-temporal filtering of dynamic PET data using a four-dimensional Gaussian filter and expectation-maximization deconvolution

NASA Astrophysics Data System (ADS)

Floberg, J. M.; Holden, J. E.

2013-02-01

We introduce a method for denoising dynamic PET data, spatio-temporal expectation-maximization (STEM) filtering, that combines four-dimensional Gaussian filtering with EM deconvolution. The initial Gaussian filter suppresses noise at a broad range of spatial and temporal frequencies and EM deconvolution quickly restores the frequencies most important to the signal. We aim to demonstrate that STEM filtering can improve variance in both individual time frames and in parametric images without introducing significant bias. We evaluate STEM filtering with a dynamic phantom study, and with simulated and human dynamic PET studies of a tracer with reversible binding behaviour, [C-11]raclopride, and a tracer with irreversible binding behaviour, [F-18]FDOPA. STEM filtering is compared to a number of established three and four-dimensional denoising methods. STEM filtering provides substantial improvements in variance in both individual time frames and in parametric images generated with a number of kinetic analysis techniques while introducing little bias. STEM filtering does bias early frames, but this does not affect quantitative parameter estimates. STEM filtering is shown to be superior to the other simple denoising methods studied. STEM filtering is a simple and effective denoising method that could be valuable for a wide range of dynamic PET applications.

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.

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

Superpixel-based spatial amplitude and phase modulation using a digital micromirror device.

PubMed

Goorden, Sebastianus A; Bertolotti, Jacopo; Mosk, Allard P

2014-07-28

We present a superpixel method for full spatial phase and amplitude control of a light beam using a digital micromirror device (DMD) combined with a spatial filter. We combine square regions of nearby micromirrors into superpixels by low pass filtering in a Fourier plane of the DMD. At each superpixel we are able to independently modulate the phase and the amplitude of light, while retaining a high resolution and the very high speed of a DMD. The method achieves a measured fidelity F = 0.98 for a target field with fully independent phase and amplitude at a resolution of 8 × 8 pixels per diffraction limited spot. For the LG10 orbital angular momentum mode the calculated fidelity is F = 0.99993, using 768 × 768 DMD pixels. The superpixel method reduces the errors when compared to the state of the art Lee holography method for these test fields by 50% and 18%, with a comparable light efficiency of around 5%. Our control software is publicly available.

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.

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 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

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.

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.

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.

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.

Two dimensional wavefront retrieval using lateral shearing interferometry

NASA Astrophysics Data System (ADS)

Mancilla-Escobar, B.; Malacara-Hernández, Z.; Malacara-Hernández, D.

2018-06-01

A new zonal two-dimensional method for wavefront retrieval from a surface under test using lateral shearing interferometry is presented. A modified Saunders method and phase shifting techniques are combined to generate a method for wavefront reconstruction. The result is a wavefront with an error below 0.7 λ and without any global high frequency filtering. A zonal analysis over square cells along the surfaces is made, obtaining a polynomial expression for the wavefront deformations over each cell. The main advantage of this method over previously published methods is that a global filtering of high spatial frequencies is not present. Thus, a global smoothing of the wavefront deformations is avoided, allowing the detection of deformations with relatively small extensions, that is, with high spatial frequencies. Additionally, local curvature and low order aberration coefficients are obtained in each cell.

Estimation of the vortex length scale and intensity from two-dimensional samples

NASA Technical Reports Server (NTRS)

Reuss, D. L.; Cheng, W. P.

1992-01-01

A method is proposed for estimating flow features that influence flame wrinkling in reciprocating internal combustion engines, where traditional statistical measures of turbulence are suspect. Candidate methods were tested in a computed channel flow where traditional turbulence measures are valid and performance can be rationally evaluated. Two concepts are tested. First, spatial filtering is applied to the two-dimensional velocity distribution and found to reveal structures corresponding to the vorticity field. Decreasing the spatial-frequency cutoff of the filter locally changes the character and size of the flow structures that are revealed by the filter. Second, vortex length scale and intensity is estimated by computing the ensemble-average velocity distribution conditionally sampled on the vorticity peaks. The resulting conditionally sampled 'average vortex' has a peak velocity less than half the rms velocity and a size approximately equal to the two-point-correlation integral-length scale.

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

Using spatiotemporal source separation to identify prominent features in multichannel data without sinusoidal filters.

PubMed

Cohen, Michael X

2017-09-27

The number of simultaneously recorded electrodes in neuroscience is steadily increasing, providing new opportunities for understanding brain function, but also new challenges for appropriately dealing with the increase in dimensionality. Multivariate source separation analysis methods have been particularly effective at improving signal-to-noise ratio while reducing the dimensionality of the data and are widely used for cleaning, classifying and source-localizing multichannel neural time series data. Most source separation methods produce a spatial component (that is, a weighted combination of channels to produce one time series); here, this is extended to apply source separation to a time series, with the idea of obtaining a weighted combination of successive time points, such that the weights are optimized to satisfy some criteria. This is achieved via a two-stage source separation procedure, in which an optimal spatial filter is first constructed and then its optimal temporal basis function is computed. This second stage is achieved with a time-delay-embedding matrix, in which additional rows of a matrix are created from time-delayed versions of existing rows. The optimal spatial and temporal weights can be obtained by solving a generalized eigendecomposition of covariance matrices. The method is demonstrated in simulated data and in an empirical electroencephalogram study on theta-band activity during response conflict. Spatiotemporal source separation has several advantages, including defining empirical filters without the need to apply sinusoidal narrowband filters. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Experimental verification of multilevel spatial pattern generation from binary data page with four-step phase pattern (Conference Presentation)

NASA Astrophysics Data System (ADS)

Barada, Daisuke; Yatagai, Toyohiko

2016-09-01

Holographic memory is expected for cold storage because of the features of huge data capacity, high data transfer rate, and long life time. In holographic memory, a signal beam is modulated by a spatial light modulator according to data pages. The recording density is dependent on information amount per pixel in a data page. However, a binary spatial light modulator is used to realize high data transfer rate in general. In our previous study, an optical conversion method from binary data to multilevel data has been proposed. In this paper, the principle of the method is experimentally verified. In the proposed method, a data page consists of symbols with 2x2 pixels and a four-step phase mask is used. Then, the complex amplitudes of four pixels in a symbol become positive real, positive imaginary, negative real, and negative imaginary values, respectively. A square pixel pattern is spread by spatial frequency filtering with a square aperture in a Fourier plane. When the aperture size is too small, the complex amplitude of four pixels in a symbol is superposed and a symbol is regarded as a pixel with a complex number. In this work, a data page pattern with a four-step phase pattern was generated by using a computer-generated circular polarization hologram (CGCPH). The CGCPH was prepared by electron beam lithography. The page data pattern is Fourier transformed by a lens and spatially filtered by a variable rectangular aperture. The complex amplitude of the spatial filtered data page pattern was measured by digital holography and the principle was experimentally verified.

Cascaded K-means convolutional feature learner and its application to face recognition

NASA Astrophysics Data System (ADS)

Zhou, Daoxiang; Yang, Dan; Zhang, Xiaohong; Huang, Sheng; Feng, Shu

2017-09-01

Currently, considerable efforts have been devoted to devise image representation. However, handcrafted methods need strong domain knowledge and show low generalization ability, and conventional feature learning methods require enormous training data and rich parameters tuning experience. A lightened feature learner is presented to solve these problems with application to face recognition, which shares similar topology architecture as a convolutional neural network. Our model is divided into three components: cascaded convolution filters bank learning layer, nonlinear processing layer, and feature pooling layer. Specifically, in the filters learning layer, we use K-means to learn convolution filters. Features are extracted via convoluting images with the learned filters. Afterward, in the nonlinear processing layer, hyperbolic tangent is employed to capture the nonlinear feature. In the feature pooling layer, to remove the redundancy information and incorporate the spatial layout, we exploit multilevel spatial pyramid second-order pooling technique to pool the features in subregions and concatenate them together as the final representation. Extensive experiments on four representative datasets demonstrate the effectiveness and robustness of our model to various variations, yielding competitive recognition results on extended Yale B and FERET. In addition, our method achieves the best identification performance on AR and labeled faces in the wild datasets among the comparative methods.

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.

CSP-TSM: Optimizing the performance of Riemannian tangent space mapping using common spatial pattern for MI-BCI.

PubMed

Kumar, Shiu; Mamun, Kabir; Sharma, Alok

2017-12-01

Classification of electroencephalography (EEG) signals for motor imagery based brain computer interface (MI-BCI) is an exigent task and common spatial pattern (CSP) has been extensively explored for this purpose. In this work, we focused on developing a new framework for classification of EEG signals for MI-BCI. We propose a single band CSP framework for MI-BCI that utilizes the concept of tangent space mapping (TSM) in the manifold of covariance matrices. The proposed method is named CSP-TSM. Spatial filtering is performed on the bandpass filtered MI EEG signal. Riemannian tangent space is utilized for extracting features from the spatial filtered signal. The TSM features are then fused with the CSP variance based features and feature selection is performed using Lasso. Linear discriminant analysis (LDA) is then applied to the selected features and finally classification is done using support vector machine (SVM) classifier. The proposed framework gives improved performance for MI EEG signal classification in comparison with several competing methods. Experiments conducted shows that the proposed framework reduces the overall classification error rate for MI-BCI by 3.16%, 5.10% and 1.70% (for BCI Competition III dataset IVa, BCI Competition IV Dataset I and BCI Competition IV Dataset IIb, respectively) compared to the conventional CSP method under the same experimental settings. The proposed CSP-TSM method produces promising results when compared with several competing methods in this paper. In addition, the computational complexity is less compared to that of TSM method. Our proposed CSP-TSM framework can be potentially used for developing improved MI-BCI systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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.

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1985-01-01

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

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.

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.

Multiple feature extraction by using simultaneous wavelet transforms

NASA Astrophysics Data System (ADS)

Mazzaferri, Javier; Ledesma, Silvia; Iemmi, Claudio

2003-07-01

We propose here a method to optically perform multiple feature extraction by using wavelet transforms. The method is based on obtaining the optical correlation by means of a Vander Lugt architecture, where the scene and the filter are displayed on spatial light modulators (SLMs). Multiple phase filters containing the information about the features that we are interested in extracting are designed and then displayed on an SLM working in phase mostly mode. We have designed filters to simultaneously detect edges and corners or different characteristic frequencies contained in the input scene. Simulated and experimental results are shown.

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.

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.

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.

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.

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.

Spatiotemporal filtering of MR-temperature artifacts arising from bowel motion during transurethral MR-HIFU

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

Schmitt, Alain, E-mail: aschmitt@sri.utoronto.ca; Mougenot, Charles; Chopra, Rajiv

2014-11-01

Purpose: Transurethral MR-HIFU is a minimally invasive image-guided treatment for localized prostate cancer that enables precise targeting of tissue within the gland. The treatment is performed within a clinical MRI to obtain real-time MR thermometry used as an active feedback to control the spatial heating pattern in the prostate and to monitor for potential damage to surrounding tissues. This requires that the MR thermometry measurements are an accurate representation of the true tissue temperature. The proton resonance frequency shift thermometry method used is sensitive to tissue motion and changes in the local magnetic susceptibility that can be caused by themore » motion of air bubbles in the rectum, which can impact the performance of transurethral MR-HIFU in these regions of the gland. Methods: A method is proposed for filtering of temperature artifacts based on the temporal variance of the temperature, using empirical and dynamic positional knowledge of the ultrasonic heating beam, and an estimation of the measurement noise. A two-step correction strategy is introduced which eliminates artifact-detected temperature variations while keeping the noise level low through spatial averaging. Results: The filter has been evaluated by postprocessing data from five human transurethral ultrasound treatments. The two-step correction process led to reduced final temperature standard deviation in the prostate and rectum areas where the artifact was located, without negatively affecting areas distal to the artifact. The performance of the filter was also found to be consistent across all six of the data sets evaluated. The evaluation of the detection criterion parameter M determined that a value of M = 3 achieves a conservative filter with minimal loss of spatial resolution during the process. Conclusions: The filter was able to remove most artifacts due to the presence of moving air bubbles in the rectum during transurethral MR-HIFU. A quantitative estimation of the filter capabilities shows a systematic improvement in the standard deviation of the corrected temperature maps in the rectum zone as well as in the entire acquired slice.« less

Adaptive wiener image restoration kernel

DOEpatents

Yuan, Ding [Henderson, NV

2007-06-05

A method and device for restoration of electro-optical image data using an adaptive Wiener filter begins with constructing imaging system Optical Transfer Function, and the Fourier Transformations of the noise and the image. A spatial representation of the imaged object is restored by spatial convolution of the image using a Wiener restoration kernel.

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.

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.

High-dynamic-range scene compression in humans

NASA Astrophysics Data System (ADS)

McCann, John J.

2006-02-01

Single pixel dynamic-range compression alters a particular input value to a unique output value - a look-up table. It is used in chemical and most digital photographic systems having S-shaped transforms to render high-range scenes onto low-range media. Post-receptor neural processing is spatial, as shown by the physiological experiments of Dowling, Barlow, Kuffler, and Hubel & Wiesel. Human vision does not render a particular receptor-quanta catch as a unique response. Instead, because of spatial processing, the response to a particular quanta catch can be any color. Visual response is scene dependent. Stockham proposed an approach to model human range compression using low-spatial frequency filters. Campbell, Ginsberg, Wilson, Watson, Daly and many others have developed spatial-frequency channel models. This paper describes experiments measuring the properties of desirable spatial-frequency filters for a variety of scenes. Given the radiances of each pixel in the scene and the observed appearances of objects in the image, one can calculate the visual mask for that individual image. Here, visual mask is the spatial pattern of changes made by the visual system in processing the input image. It is the spatial signature of human vision. Low-dynamic range images with many white areas need no spatial filtering. High-dynamic-range images with many blacks, or deep shadows, require strong spatial filtering. Sun on the right and shade on the left requires directional filters. These experiments show that variable scene- scenedependent filters are necessary to mimic human vision. Although spatial-frequency filters can model human dependent appearances, the problem still remains that an analysis of the scene is still needed to calculate the scene-dependent strengths of each of the filters for each frequency.

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.

Geostatistics for spatial genetic structures: study of wild populations of perennial ryegrass.

PubMed

Monestiez, P; Goulard, M; Charmet, G

1994-04-01

Methods based on geostatistics were applied to quantitative traits of agricultural interest measured on a collection of 547 wild populations of perennial ryegrass in France. The mathematical background of these methods, which resembles spatial autocorrelation analysis, is briefly described. When a single variable is studied, the spatial structure analysis is similar to spatial autocorrelation analysis, and a spatial prediction method, called "kriging", gives a filtered map of the spatial pattern over all the sampled area. When complex interactions of agronomic traits with different evaluation sites define a multivariate structure for the spatial analysis, geostatistical methods allow the spatial variations to be broken down into two main spatial structures with ranges of 120 km and 300 km, respectively. The predicted maps that corresponded to each range were interpreted as a result of the isolation-by-distance model and as a consequence of selection by environmental factors. Practical collecting methodology for breeders may be derived from such spatial structures.

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.

Dual Adaptive Filtering by Optimal Projection Applied to Filter Muscle Artifacts on EEG and Comparative Study

PubMed Central

Peyrodie, Laurent; Szurhaj, William; Bolo, Nicolas; Pinti, Antonio; Gallois, Philippe

2014-01-01

Muscle artifacts constitute one of the major problems in electroencephalogram (EEG) examinations, particularly for the diagnosis of epilepsy, where pathological rhythms occur within the same frequency bands as those of artifacts. This paper proposes to use the method dual adaptive filtering by optimal projection (DAFOP) to automatically remove artifacts while preserving true cerebral signals. DAFOP is a two-step method. The first step consists in applying the common spatial pattern (CSP) method to two frequency windows to identify the slowest components which will be considered as cerebral sources. The two frequency windows are defined by optimizing convolutional filters. The second step consists in using a regression method to reconstruct the signal independently within various frequency windows. This method was evaluated by two neurologists on a selection of 114 pages with muscle artifacts, from 20 clinical recordings of awake and sleeping adults, subject to pathological signals and epileptic seizures. A blind comparison was then conducted with the canonical correlation analysis (CCA) method and conventional low-pass filtering at 30 Hz. The filtering rate was 84.3% for muscle artifacts with a 6.4% reduction of cerebral signals even for the fastest waves. DAFOP was found to be significantly more efficient than CCA and 30 Hz filters. The DAFOP method is fast and automatic and can be easily used in clinical EEG recordings. PMID:25298967

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.

Spatial-heterodyne interferometry for transmission (SHIFT) measurements

DOEpatents

Bingham, Philip R.; Hanson, Gregory R.; Tobin, Ken W.

2006-10-10

Systems and methods are described for spatial-heterodyne interferometry for transmission (SHIFT) measurements. A method includes digitally recording a spatially-heterodyned hologram including spatial heterodyne fringes for Fourier analysis using a reference beam, and an object beam that is transmitted through an object that is at least partially translucent; Fourier analyzing the digitally recorded spatially-heterodyned hologram, by shifting an original origin of the digitally recorded spatially-heterodyned hologram to sit on top of a spatial-heterodyne carrier frequency defined by an angle between the reference beam and the object beam, to define an analyzed image; digitally filtering the analyzed image to cut off signals around the original origin to define a result; and performing an inverse Fourier transform on the result.

Flat-topped broadband rugate filters.

PubMed

Imenes, Anne G; McKenzie, David R

2006-10-20

A method of creating rugate interference filters that have flat-topped reflectance across an extended spectral region is presented. The method applies known relations from the classical coupled wave theory to develop a set of equations that gives the spatial frequency distribution of rugate cycles to achieve constant reflectance across a given spectral region. Two examples of the application of this method are discussed: a highly reflective coating for eye protection against harmful laser radiation incident from normal to 45 degrees , and a spectral beam splitter for efficient solar power conversion.

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.

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.

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.

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.

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)

Filter Bank Regularized Common Spatial Pattern Ensemble for Small Sample Motor Imagery Classification.

PubMed

Park, Sang-Hoon; Lee, David; Lee, Sang-Goog

2018-02-01

For the last few years, many feature extraction methods have been proposed based on biological signals. Among these, the brain signals have the advantage that they can be obtained, even by people with peripheral nervous system damage. Motor imagery electroencephalograms (EEG) are inexpensive to measure, offer a high temporal resolution, and are intuitive. Therefore, these have received a significant amount of attention in various fields, including signal processing, cognitive science, and medicine. The common spatial pattern (CSP) algorithm is a useful method for feature extraction from motor imagery EEG. However, performance degradation occurs in a small-sample setting (SSS), because the CSP depends on sample-based covariance. Since the active frequency range is different for each subject, it is also inconvenient to set the frequency range to be different every time. In this paper, we propose the feature extraction method based on a filter bank to solve these problems. The proposed method consists of five steps. First, motor imagery EEG is divided by a using filter bank. Second, the regularized CSP (R-CSP) is applied to the divided EEG. Third, we select the features according to mutual information based on the individual feature algorithm. Fourth, parameter sets are selected for the ensemble. Finally, we classify using ensemble based on features. The brain-computer interface competition III data set IVa is used to evaluate the performance of the proposed method. The proposed method improves the mean classification accuracy by 12.34%, 11.57%, 9%, 4.95%, and 4.47% compared with CSP, SR-CSP, R-CSP, filter bank CSP (FBCSP), and SR-FBCSP. Compared with the filter bank R-CSP ( , ), which is a parameter selection version of the proposed method, the classification accuracy is improved by 3.49%. In particular, the proposed method shows a large improvement in performance in the SSS.

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.

Spatial filtering of audible sound with acoustic landscapes

NASA Astrophysics Data System (ADS)

Wang, Shuping; Tao, Jiancheng; Qiu, Xiaojun; Cheng, Jianchun

2017-07-01

Acoustic metasurfaces manipulate waves with specially designed structures and achieve properties that natural materials cannot offer. Similar surfaces work in audio frequency range as well and lead to marvelous acoustic phenomena that can be perceived by human ears. Being intrigued by the famous Maoshan Bugle phenomenon, we investigate large scale metasurfaces consisting of periodic steps of sizes comparable to the wavelength of audio frequency in both time and space domains. We propose a theoretical method to calculate the scattered sound field and find that periodic corrugated surfaces work as spatial filters and the frequency selective character can only be observed at the same side as the incident wave. The Maoshan Bugle phenomenon can be well explained with the method. Finally, we demonstrate that the proposed method can be used to design acoustical landscapes, which transform impulsive sound into famous trumpet solos or other melodious sound.

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...

Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar.

PubMed

Long, Teng; Zhang, Honggang; Zeng, Tao; Chen, Xinliang; Liu, Quanhua; Zheng, Le

2016-09-09

Distributed array radar can improve radar detection capability and measurement accuracy. However, it will suffer cyclic ambiguity in its angle estimates according to the spatial Nyquist sampling theorem since the large sparse array is undersampling. Consequently, the state estimation accuracy and track validity probability degrades when the ambiguous angles are directly used for target tracking. This paper proposes a second probability data association filter (SePDAF)-based tracking method for distributed array radar. Firstly, the target motion model and radar measurement model is built. Secondly, the fusion result of each radar's estimation is employed to the extended Kalman filter (EKF) to finish the first filtering. Thirdly, taking this result as prior knowledge, and associating with the array-processed ambiguous angles, the SePDAF is applied to accomplish the second filtering, and then achieving a high accuracy and stable trajectory with relatively low computational complexity. Moreover, the azimuth filtering accuracy will be promoted dramatically and the position filtering accuracy will also improve. Finally, simulations illustrate the effectiveness of the proposed method.

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.

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.

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.

Effect of filters and reconstruction algorithms on I-124 PET in Siemens Inveon PET scanner

NASA Astrophysics Data System (ADS)

Ram Yu, A.; Kim, Jin Su

2015-10-01

Purpose: To assess the effects of filtering and reconstruction on Siemens I-124 PET data. Methods: A Siemens Inveon PET was used. Spatial resolution of I-124 was measured to a transverse offset of 50 mm from the center FBP, 2D ordered subset expectation maximization (OSEM2D), 3D re-projection algorithm (3DRP), and maximum a posteriori (MAP) methods were tested. Non-uniformity (NU), recovery coefficient (RC), and spillover ratio (SOR) parameterized image quality. Mini deluxe phantom data of I-124 was also assessed. Results: Volumetric resolution was 7.3 mm3 from the transverse FOV center when FBP reconstruction algorithms with ramp filter was used. MAP yielded minimal NU with β =1.5. OSEM2D yielded maximal RC. SOR was below 4% for FBP with ramp, Hamming, Hanning, or Shepp-Logan filters. Based on the mini deluxe phantom results, an FBP with Hanning or Parzen filters, or a 3DRP with Hanning filter yielded feasible I-124 PET data.Conclusions: Reconstruction algorithms and filters were compared. FBP with Hanning or Parzen filters, or 3DRP with Hanning filter yielded feasible data for quantifying I-124 PET.

An accelerated non-Gaussianity based multichannel predictive deconvolution method with the limited supporting region of filters

NASA Astrophysics Data System (ADS)

Li, Zhong-xiao; Li, Zhen-chun

2016-09-01

The multichannel predictive deconvolution can be conducted in overlapping temporal and spatial data windows to solve the 2D predictive filter for multiple removal. Generally, the 2D predictive filter can better remove multiples at the cost of more computation time compared with the 1D predictive filter. In this paper we first use the cross-correlation strategy to determine the limited supporting region of filters where the coefficients play a major role for multiple removal in the filter coefficient space. To solve the 2D predictive filter the traditional multichannel predictive deconvolution uses the least squares (LS) algorithm, which requires primaries and multiples are orthogonal. To relax the orthogonality assumption the iterative reweighted least squares (IRLS) algorithm and the fast iterative shrinkage thresholding (FIST) algorithm have been used to solve the 2D predictive filter in the multichannel predictive deconvolution with the non-Gaussian maximization (L1 norm minimization) constraint of primaries. The FIST algorithm has been demonstrated as a faster alternative to the IRLS algorithm. In this paper we introduce the FIST algorithm to solve the filter coefficients in the limited supporting region of filters. Compared with the FIST based multichannel predictive deconvolution without the limited supporting region of filters the proposed method can reduce the computation burden effectively while achieving a similar accuracy. Additionally, the proposed method can better balance multiple removal and primary preservation than the traditional LS based multichannel predictive deconvolution and FIST based single channel predictive deconvolution. Synthetic and field data sets demonstrate the effectiveness of the proposed method.

An efficient implementation of a high-order filter for a cubed-sphere spectral element model

NASA Astrophysics Data System (ADS)

Kang, Hyun-Gyu; Cheong, Hyeong-Bin

2017-03-01

A parallel-scalable, isotropic, scale-selective spatial filter was developed for the cubed-sphere spectral element model on the sphere. The filter equation is a high-order elliptic (Helmholtz) equation based on the spherical Laplacian operator, which is transformed into cubed-sphere local coordinates. The Laplacian operator is discretized on the computational domain, i.e., on each cell, by the spectral element method with Gauss-Lobatto Lagrange interpolating polynomials (GLLIPs) as the orthogonal basis functions. On the global domain, the discrete filter equation yielded a linear system represented by a highly sparse matrix. The density of this matrix increases quadratically (linearly) with the order of GLLIP (order of the filter), and the linear system is solved in only O (Ng) operations, where Ng is the total number of grid points. The solution, obtained by a row reduction method, demonstrated the typical accuracy and convergence rate of the cubed-sphere spectral element method. To achieve computational efficiency on parallel computers, the linear system was treated by an inverse matrix method (a sparse matrix-vector multiplication). The density of the inverse matrix was lowered to only a few times of the original sparse matrix without degrading the accuracy of the solution. For better computational efficiency, a local-domain high-order filter was introduced: The filter equation is applied to multiple cells, and then the central cell was only used to reconstruct the filtered field. The parallel efficiency of applying the inverse matrix method to the global- and local-domain filter was evaluated by the scalability on a distributed-memory parallel computer. The scale-selective performance of the filter was demonstrated on Earth topography. The usefulness of the filter as a hyper-viscosity for the vorticity equation was also demonstrated.

Angle-Beam Shear Wave Scattering from Buried Crack-like Defects in Bonded Specimens (Postprint)

DTIC Science & Technology

2017-02-01

wavenumber filtering and spatial windowing is proposed and implemented as an alternative approach to quantify scattering from damage. 15. SUBJECT...TERMS Backscattering . Ultrasonography . Spatial filtering . Ultrasonic scattering . Scattering measurement 16. SECURITY CLASSIFICATION OF: 17...of frequency- wavenumber filtering and spatial windowing is proposed and implemented as an alternative approach to quantify scattering from damage

Relaxation method of compensation in an optical correlator

NASA Technical Reports Server (NTRS)

Juday, Richard D.; Daiuto, Brian J.

1987-01-01

An iterative method is proposed for the sharpening of programmable filters in a 4-f optical correlator. Continuously variable spatial light modulators (SLMs) permit the fine adjustment of optical processing filters so as to compensate for the departures from ideal behavior of a real optical system. Although motivated by the development of continuously variable phase-only SLMs, the proposed sharpening method is also applicable to amplitude modulators and, with appropriate adjustments, to binary modulators as well. A computer simulation is presented that illustrates the potential effectiveness of the method: an image is placed on the input to the correlator, and its corresponding phase-only filter is adjusted (allowed to relax) so as to produce a progressively brighter and more centralized peak in the correlation plane. The technique is highly robust against the form of the system's departure from ideal behavior.

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.

A novel shape from focus method based on 3D steerable filters for improved performance on treating textureless region

NASA Astrophysics Data System (ADS)

Fan, Tiantian; Yu, Hongbin

2018-03-01

A novel shape from focus method combining 3D steerable filter for improved performance on treating textureless region was proposed in this paper. Different from conventional spatial methods focusing on the search of maximum edges' response to estimate the depth map, the currently proposed method took both of the edges' response and the axial imaging blur degree into consideration during treatment. As a result, more robust and accurate identification for the focused location can be achieved, especially when treating textureless objects. Improved performance in depth measurement has been successfully demonstrated from both of the simulation and experiment results.

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

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.

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

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.

Two-Dimensional Planar Lightwave Circuit Integrated Spatial Filter Array and Method of Use Thereof

NASA Technical Reports Server (NTRS)

Dimov, Fedor (Inventor); Ai, Jun (Inventor)

2015-01-01

A large coherent two-dimensional (2D) spatial filter array (SFA), 30 by 30 or larger, is produced by coupling a 2D planar lightwave circuit (PLC) array with a pair of lenslet arrays at the input and output side. The 2D PLC array is produced by stacking a plurality of chips, each chip with a plural number of straight PLC waveguides. A pupil array is coated onto the focal plane of the lenslet array. The PLC waveguides are produced by deposition of a plural number of silica layers on the silicon wafer, followed by photolithography and reactive ion etching (RIE) processes. A plural number of mode filters are included in the silica-on-silicon waveguide such that the PLC waveguide is transparent to the fundamental mode but higher order modes are attenuated by 40 dB or more.

Describing litho-constrained layout by a high-resolution model filter

NASA Astrophysics Data System (ADS)

Tsai, Min-Chun

2008-05-01

A novel high-resolution model (HRM) filtering technique was proposed to describe litho-constrained layouts. Litho-constrained layouts are layouts that have difficulties to pattern or are highly sensitive to process-fluctuations under current lithography technologies. HRM applies a short-wavelength (or high NA) model simulation directly on the pre-OPC, original design layout to filter out low spatial-frequency regions, and retain high spatial-frequency components which are litho-constrained. Since no OPC neither mask-synthesis steps are involved, this new technique is highly efficient in run time and can be used in design stage to detect and fix litho-constrained patterns. This method has successfully captured all the hot-spots with less than 15% overshoots on a realistic 80 mm2 full-chip M1 layout in 65nm technology node. A step by step derivation of this HRM technique is presented in this paper.

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.

Image enhancement by spatial frequency post-processing of images obtained with pupil filters

NASA Astrophysics Data System (ADS)

Estévez, Irene; Escalera, Juan C.; Stefano, Quimey Pears; Iemmi, Claudio; Ledesma, Silvia; Yzuel, María J.; Campos, Juan

2016-12-01

The use of apodizing or superresolving filters improves the performance of an optical system in different frequency bands. This improvement can be seen as an increase in the OTF value compared to the OTF for the clear aperture. In this paper we propose a method to enhance the contrast of an image in both its low and its high frequencies. The method is based on the generation of a synthetic Optical Transfer Function, by multiplexing the OTFs given by the use of different non-uniform transmission filters on the pupil. We propose to capture three images, one obtained with a clear pupil, one obtained with an apodizing filter that enhances the low frequencies and another one taken with a superresolving filter that improves the high frequencies. In the Fourier domain the three spectra are combined by using smoothed passband filters, and then the inverse transform is performed. We show that we can create an enhanced image better than the image obtained with the clear aperture. To evaluate the performance of the method, bar tests (sinusoidal tests) with different frequency content are used. The results show that a contrast improvement in the high and low frequencies is obtained.

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.

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.

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.

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.

A nowcasting technique based on application of the particle filter blending algorithm

NASA Astrophysics Data System (ADS)

Chen, Yuanzhao; Lan, Hongping; Chen, Xunlai; Zhang, Wenhai

2017-10-01

To improve the accuracy of nowcasting, a new extrapolation technique called particle filter blending was configured in this study and applied to experimental nowcasting. Radar echo extrapolation was performed by using the radar mosaic at an altitude of 2.5 km obtained from the radar images of 12 S-band radars in Guangdong Province, China. The first bilateral filter was applied in the quality control of the radar data; an optical flow method based on the Lucas-Kanade algorithm and the Harris corner detection algorithm were used to track radar echoes and retrieve the echo motion vectors; then, the motion vectors were blended with the particle filter blending algorithm to estimate the optimal motion vector of the true echo motions; finally, semi-Lagrangian extrapolation was used for radar echo extrapolation based on the obtained motion vector field. A comparative study of the extrapolated forecasts of four precipitation events in 2016 in Guangdong was conducted. The results indicate that the particle filter blending algorithm could realistically reproduce the spatial pattern, echo intensity, and echo location at 30- and 60-min forecast lead times. The forecasts agreed well with observations, and the results were of operational significance. Quantitative evaluation of the forecasts indicates that the particle filter blending algorithm performed better than the cross-correlation method and the optical flow method. Therefore, the particle filter blending method is proved to be superior to the traditional forecasting methods and it can be used to enhance the ability of nowcasting in operational weather forecasts.

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.

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

Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar

PubMed Central

Long, Teng; Zhang, Honggang; Zeng, Tao; Chen, Xinliang; Liu, Quanhua; Zheng, Le

2016-01-01

Distributed array radar can improve radar detection capability and measurement accuracy. However, it will suffer cyclic ambiguity in its angle estimates according to the spatial Nyquist sampling theorem since the large sparse array is undersampling. Consequently, the state estimation accuracy and track validity probability degrades when the ambiguous angles are directly used for target tracking. This paper proposes a second probability data association filter (SePDAF)-based tracking method for distributed array radar. Firstly, the target motion model and radar measurement model is built. Secondly, the fusion result of each radar’s estimation is employed to the extended Kalman filter (EKF) to finish the first filtering. Thirdly, taking this result as prior knowledge, and associating with the array-processed ambiguous angles, the SePDAF is applied to accomplish the second filtering, and then achieving a high accuracy and stable trajectory with relatively low computational complexity. Moreover, the azimuth filtering accuracy will be promoted dramatically and the position filtering accuracy will also improve. Finally, simulations illustrate the effectiveness of the proposed method. PMID:27618058

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.

Spatial effects in real networks: Measures, null models, and applications

NASA Astrophysics Data System (ADS)

Ruzzenenti, Franco; Picciolo, Francesco; Basosi, Riccardo; Garlaschelli, Diego

2012-12-01

Spatially embedded networks are shaped by a combination of purely topological (space-independent) and space-dependent formation rules. While it is quite easy to artificially generate networks where the relative importance of these two factors can be varied arbitrarily, it is much more difficult to disentangle these two architectural effects in real networks. Here we propose a solution to this problem, by introducing global and local measures of spatial effects that, through a comparison with adequate null models, effectively filter out the spurious contribution of nonspatial constraints. Our filtering allows us to consistently compare different embedded networks or different historical snapshots of the same network. As a challenging application we analyze the World Trade Web, whose topology is known to depend on geographic distances but is also strongly determined by nonspatial constraints (degree sequence or gross domestic product). Remarkably, we are able to detect weak but significant spatial effects both locally and globally in the network, showing that our method succeeds in retrieving spatial information even when nonspatial factors dominate. We finally relate our results to the economic literature on gravity models and trade globalization.

Spatial wavefield gradient-based seismic wavefield separation

NASA Astrophysics Data System (ADS)

Van Renterghem, C.; Schmelzbach, C.; Sollberger, D.; Robertsson, J. OA

2018-03-01

Measurements of the horizontal and vertical components of particle motion combined with estimates of the spatial gradients of the seismic wavefield enable seismic data to be acquired and processed using single dedicated multicomponent stations (e.g. rotational sensors) and/or small receiver groups instead of large receiver arrays. Here, we present seismic wavefield decomposition techniques that use spatial wavefield gradient data to separate land and ocean bottom data into their upgoing/downgoing and P/S constituents. Our method is based on the elastodynamic representation theorem with the derived filters requiring local measurements of the wavefield and its spatial gradients only. We demonstrate with synthetic data and a land seismic field data example that combining translational measurements with spatial wavefield gradient estimates allows separating seismic data recorded either at the Earth's free-surface or at the sea bottom into upgoing/downgoing and P/S wavefield constituents for typical incidence angle ranges of body waves. A key finding is that the filter application only requires knowledge of the elastic properties exactly at the recording locations and is valid for a wide elastic property range.

Method and apparatus for an optical function generator for seamless tiled displays

NASA Technical Reports Server (NTRS)

Johnson, Michael (Inventor); Chen, Chung-Jen (Inventor)

2004-01-01

Producing seamless tiled images from multiple displays includes measuring a luminance profile of each of the displays, computing a desired luminance profile for each of the displays, and determining a spatial gradient profile of each of the displays based on the measured luminance profile and the computed desired luminance profile. The determined spatial gradient profile is applied to a spatial filter to be inserted into each of the displays to produce the seamless tiled display image.

Method and apparatus for detecting a desired behavior in digital image data

DOEpatents

Kegelmeyer, Jr., W. Philip

1997-01-01

A method for detecting stellate lesions in digitized mammographic image data includes the steps of prestoring a plurality of reference images, calculating a plurality of features for each of the pixels of the reference images, and creating a binary decision tree from features of randomly sampled pixels from each of the reference images. Once the binary decision tree has been created, a plurality of features, preferably including an ALOE feature (analysis of local oriented edges), are calculated for each of the pixels of the digitized mammographic data. Each of these plurality of features of each pixel are input into the binary decision tree and a probability is determined, for each of the pixels, corresponding to the likelihood of the presence of a stellate lesion, to create a probability image. Finally, the probability image is spatially filtered to enforce local consensus among neighboring pixels and the spatially filtered image is output.

Adaptive optics system performance approximations for atmospheric turbulence correction

NASA Astrophysics Data System (ADS)

Tyson, Robert K.

1990-10-01

Analysis of adaptive optics system behavior often can be reduced to a few approximations and scaling laws. For atmospheric turbulence correction, the deformable mirror (DM) fitting error is most often used to determine a priori the interactuator spacing and the total number of correction zones required. This paper examines the mirror fitting error in terms of its most commonly used exponential form. The explicit constant in the error term is dependent on deformable mirror influence function shape and actuator geometry. The method of least squares fitting of discrete influence functions to the turbulent wavefront is compared to the linear spatial filtering approximation of system performance. It is found that the spatial filtering method overstimates the correctability of the adaptive optics system by a small amount. By evaluating fitting error for a number of DM configurations, actuator geometries, and influence functions, fitting error constants verify some earlier investigations.

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.

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

A Probabilistic Collocation Based Iterative Kalman Filter for Landfill Data Assimilation

NASA Astrophysics Data System (ADS)

Qiang, Z.; Zeng, L.; Wu, L.

2016-12-01

Due to the strong spatial heterogeneity of landfill, uncertainty is ubiquitous in gas transport process in landfill. To accurately characterize the landfill properties, the ensemble Kalman filter (EnKF) has been employed to assimilate the measurements, e.g., the gas pressure. As a Monte Carlo (MC) based method, the EnKF usually requires a large ensemble size, which poses a high computational cost for large scale problems. In this work, we propose a probabilistic collocation based iterative Kalman filter (PCIKF) to estimate permeability in a liquid-gas coupling model. This method employs polynomial chaos expansion (PCE) to represent and propagate the uncertainties of model parameters and states, and an iterative form of Kalman filter to assimilate the current gas pressure data. To further reduce the computation cost, the functional ANOVA (analysis of variance) decomposition is conducted, and only the first order ANOVA components are remained for PCE. Illustrated with numerical case studies, this proposed method shows significant superiority in computation efficiency compared with the traditional MC based iterative EnKF. The developed method has promising potential in reliable prediction and management of landfill gas production.

SU-E-I-37: Low-Dose Real-Time Region-Of-Interest X-Ray Fluoroscopic Imaging with a GPU-Accelerated Spatially Different Bilateral Filtering

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

Chung, H; Lee, J; Pua, R

2014-06-01

Purpose: The purpose of our study is to reduce imaging radiation dose while maintaining image quality of region of interest (ROI) in X-ray fluoroscopy. A low-dose real-time ROI fluoroscopic imaging technique which includes graphics-processing-unit- (GPU-) accelerated image processing for brightness compensation and noise filtering was developed in this study. Methods: In our ROI fluoroscopic imaging, a copper filter is placed in front of the X-ray tube. The filter contains a round aperture to reduce radiation dose to outside of the aperture. To equalize the brightness difference between inner and outer ROI regions, brightness compensation was performed by use of amore » simple weighting method that applies selectively to the inner ROI, the outer ROI, and the boundary zone. A bilateral filtering was applied to the images to reduce relatively high noise in the outer ROI images. To speed up the calculation of our technique for real-time application, the GPU-acceleration was applied to the image processing algorithm. We performed a dosimetric measurement using an ion-chamber dosimeter to evaluate the amount of radiation dose reduction. The reduction of calculation time compared to a CPU-only computation was also measured, and the assessment of image quality in terms of image noise and spatial resolution was conducted. Results: More than 80% of dose was reduced by use of the ROI filter. The reduction rate depended on the thickness of the filter and the size of ROI aperture. The image noise outside the ROI was remarkably reduced by the bilateral filtering technique. The computation time for processing each frame image was reduced from 3.43 seconds with single CPU to 9.85 milliseconds with GPU-acceleration. Conclusion: The proposed technique for X-ray fluoroscopy can substantially reduce imaging radiation dose to the patient while maintaining image quality particularly in the ROI region in real-time.« less

Landsat 7 thermal-IR image sharpening using an artificial neural network and sensor model

USGS Publications Warehouse

Lemeshewsky, G.P.; Schowengerdt, R.A.; ,

2001-01-01

The enhanced thematic mapper (plus) (ETM+) instrument on Landsat 7 shares the same basic design as the TM sensors on Landsats 4 and 5, with some significant improvements. In common are six multispectral bands with a 30-m ground-projected instantaneous field of view (GIFOV). However, the thermaL-IR (TIR) band now has a 60-m GIFOV, instead of 120-m. Also, a 15-m panchromatic band has been added. The artificial neural network (NN) image sharpening method described here uses data from the higher spatial resolution ETM+ bands to enhance (sharpen) the spatial resolution of the TIR imagery. It is based on an assumed correlation over multiple scales of resolution, between image edge contrast patterns in the TIR band and several other spectral bands. A multilayer, feedforward NN is trained to approximate TIR data at 60m, given degraded (from 30-m to 60-m) spatial resolution input from spectral bands 7, 5, and 2. After training, the NN output for full-resolution input generates an approximation of a TIR image at 30-m resolution. Two methods are used to degrade the spatial resolution of the imagery used for NN training, and the corresponding sharpening results are compared. One degradation method uses a published sensor transfer function (TF) for Landsat 5 to simulate sensor coarser resolution imagery from higher resolution imagery. For comparison, the second degradation method is simply Gaussian low pass filtering and subsampling, wherein the Gaussian filter approximates the full width at half maximum amplitude characteristics of the TF-based spatial filter. Two fixed-size NNs (that is, number of weights and processing elements) were trained separately with the degraded resolution data, and the sharpening results compared. The comparison evaluates the relative influence of the degradation technique employed and whether or not it is desirable to incorporate a sensor TF model. Preliminary results indicate some improvements for the sensor model-based technique. Further evaluation using a higher resolution reference image and strict application of sensor model to data is recommended.

Multisubject Learning for Common Spatial Patterns in Motor-Imagery BCI

PubMed Central

Devlaminck, Dieter; Wyns, Bart; Grosse-Wentrup, Moritz; Otte, Georges; Santens, Patrick

2011-01-01

Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern filter (CSP) as preprocessing step before feature extraction and classification. The CSP method is a supervised algorithm and therefore needs subject-specific training data for calibration, which is very time consuming to collect. In order to reduce the amount of calibration data that is needed for a new subject, one can apply multitask (from now on called multisubject) machine learning techniques to the preprocessing phase. Here, the goal of multisubject learning is to learn a spatial filter for a new subject based on its own data and that of other subjects. This paper outlines the details of the multitask CSP algorithm and shows results on two data sets. In certain subjects a clear improvement can be seen, especially when the number of training trials is relatively low. PMID:22007194

Solar Confocal Interferometers for Sub-Picometer-Resolution Spectral Filters

NASA Technical Reports Server (NTRS)

Gary, G. Allen; Pietraszewski, Chris; West, Edward A.; Dines, Terence C.

2006-01-01

The confocal Fabry-Perot interferometer allows sub-picometer spectral resolution of Fraunhofer line profiles. Such high spectral resolution is needed to keep pace with the higher spatial resolution of the new set of large-aperture solar telescopes. The line-of-sight spatial resolution derived for line profile inversions would then track the improvements of the transverse spatial scale provided by the larger apertures. The confocal interferometer's unique properties allow a simultaneous increase in both etendue and spectral power. Methods: We have constructed and tested two confocal interferometers. Conclusions: In this paper we compare the confocal interferometer with other spectral imaging filters, provide initial design parameters, show construction details for two designs, and report on the laboratory test results for these interferometers, and propose a multiple etalon system for future testing of these units and to obtain sub-picometer spectral resolution information on the photosphere in both the visible and near-infrared.

Laser Beam Filtration for High Spatial Resolution MALDI Imaging Mass Spectrometry

NASA Astrophysics Data System (ADS)

Zavalin, Andre; Yang, Junhai; Caprioli, Richard

2013-07-01

We describe an easy and inexpensive way to provide a highly defined Gaussian shaped laser spot on target of 5 μm diameter for imaging mass spectrometry using a commercial MALDI TOF instrument that is designed to produce a 20 μm diameter laser beam on target at its lowest setting. A 25 μm pinhole filter on a swivel arm was installed in the laser beam optics outside the vacuum ion source chamber so it is easily flipped into or out of the beam as desired by the operator. The resulting ion images at 5 μm spatial resolution are sharp since the satellite secondary laser beam maxima have been removed by the filter. Ion images are shown to demonstrate the performance and are compared with the method of oversampling to achieve higher spatial resolution when only a larger laser beam spot on target is available.

Adaptive nonlocal means filtering based on local noise level for CT denoising

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

Li, Zhoubo; Trzasko, Joshua D.; Lake, David S.

2014-01-15

Purpose: To develop and evaluate an image-domain noise reduction method based on a modified nonlocal means (NLM) algorithm that is adaptive to local noise level of CT images and to implement this method in a time frame consistent with clinical workflow. Methods: A computationally efficient technique for local noise estimation directly from CT images was developed. A forward projection, based on a 2D fan-beam approximation, was used to generate the projection data, with a noise model incorporating the effects of the bowtie filter and automatic exposure control. The noise propagation from projection data to images was analytically derived. The analyticalmore » noise map was validated using repeated scans of a phantom. A 3D NLM denoising algorithm was modified to adapt its denoising strength locally based on this noise map. The performance of this adaptive NLM filter was evaluated in phantom studies in terms of in-plane and cross-plane high-contrast spatial resolution, noise power spectrum (NPS), subjective low-contrast spatial resolution using the American College of Radiology (ACR) accreditation phantom, and objective low-contrast spatial resolution using a channelized Hotelling model observer (CHO). Graphical processing units (GPU) implementation of this noise map calculation and the adaptive NLM filtering were developed to meet demands of clinical workflow. Adaptive NLM was piloted on lower dose scans in clinical practice. Results: The local noise level estimation matches the noise distribution determined from multiple repetitive scans of a phantom, demonstrated by small variations in the ratio map between the analytical noise map and the one calculated from repeated scans. The phantom studies demonstrated that the adaptive NLM filter can reduce noise substantially without degrading the high-contrast spatial resolution, as illustrated by modulation transfer function and slice sensitivity profile results. The NPS results show that adaptive NLM denoising preserves the shape and peak frequency of the noise power spectrum better than commercial smoothing kernels, and indicate that the spatial resolution at low contrast levels is not significantly degraded. Both the subjective evaluation using the ACR phantom and the objective evaluation on a low-contrast detection task using a CHO model observer demonstrate an improvement on low-contrast performance. The GPU implementation can process and transfer 300 slice images within 5 min. On patient data, the adaptive NLM algorithm provides more effective denoising of CT data throughout a volume than standard NLM, and may allow significant lowering of radiation dose. After a two week pilot study of lower dose CT urography and CT enterography exams, both GI and GU radiology groups elected to proceed with permanent implementation of adaptive NLM in their GI and GU CT practices. Conclusions: This work describes and validates a computationally efficient technique for noise map estimation directly from CT images, and an adaptive NLM filtering based on this noise map, on phantom and patient data. Both the noise map calculation and the adaptive NLM filtering can be performed in times that allow integration with clinical workflow. The adaptive NLM algorithm provides effective denoising of CT data throughout a volume, and may allow significant lowering of radiation dose.« less

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

Digital holographic microscope with low-frequency attenuation filter for position measurement of a nanoparticle.

PubMed

Pham, Quang Duc; Kusumi, Yuichi; Hasegawa, Satoshi; Hayasaki, Yoshio

2012-10-01

We propose a new method for three-dimensional (3D) position measurement of nanoparticles using an in-line digital holographic microscope. The method improves the signal-to-noise ratio of the amplitude of the interference fringes to achieve higher accuracy in the position measurement by increasing weak scattered light from a nanoparticle relative to the reference light by using a low spatial frequency attenuation filter. We demonstrated the improvements of signal-to-noise ratio of the optical system and contrast of the interference fringes, allowing the 3D positions of nanoparticles to be determined more precisely.

Real-time optical multiple object recognition and tracking system and method

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor); Liu, Hua Kuang (Inventor)

1987-01-01

The invention relates to an apparatus and associated methods for the optical recognition and tracking of multiple objects in real time. Multiple point spatial filters are employed that pre-define the objects to be recognized at run-time. The system takes the basic technology of a Vander Lugt filter and adds a hololens. The technique replaces time, space and cost-intensive digital techniques. In place of multiple objects, the system can also recognize multiple orientations of a single object. This later capability has potential for space applications where space and weight are at a premium.

Highway traffic estimation of improved precision using the derivative-free nonlinear Kalman Filter

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Siano, Pierluigi; Zervos, Nikolaos; Melkikh, Alexey

2015-12-01

The paper proves that the PDE dynamic model of the highway traffic is a differentially flat one and by applying spatial discretization its shows that the model's transformation into an equivalent linear canonical state-space form is possible. For the latter representation of the traffic's dynamics, state estimation is performed with the use of the Derivative-free nonlinear Kalman Filter. The proposed filter consists of the Kalman Filter recursion applied on the transformed state-space model of the highway traffic. Moreover, it makes use of an inverse transformation, based again on differential flatness theory which enables to obtain estimates of the state variables of the initial nonlinear PDE model. By avoiding approximate linearizations and the truncation of nonlinear terms from the PDE model of the traffic's dynamics the proposed filtering methods outperforms, in terms of accuracy, other nonlinear estimators such as the Extended Kalman Filter. The article's theoretical findings are confirmed through simulation experiments.

Transverse mode control in proton-implanted and oxide-confined VCSELs via patterned dielectric anti-phase filters

NASA Astrophysics Data System (ADS)

Kesler, Benjamin; O'Brien, Thomas; Dallesasse, John M.

2017-02-01

A novel method for controlling the transverse lasing modes in both proton implanted and oxide-confined vertical- cavity surface-emitting lasers (VCSELs) with a multi-layer, patterned, dielectric anti-phase (DAP) filter is pre- sented. Using a simple photolithographic liftoff process, dielectric layers are deposited and patterned on individual VCSELs to modify (increase or decrease) the mirror reflectivity across the emission aperture via anti-phase reflections, creating spatially-dependent threshold material gain. The shape of the dielectric pattern can be tailored to overlap with specific transverse VCSEL modes or subsets of transverse modes to either facilitate or inhibit lasing by decreasing or increasing, respectively, the threshold modal gain. A silicon dioxide (SiO2) and titanium dioxide (TiO2) anti-phase filter is used to achieve a single-fundamental-mode, continuous-wave output power greater than 4.0 mW in an oxide-confined VCSEL at a lasing wavelength of 850 nm. A filter consisting of SiO2 and TiO2 is used to facilitate injection-current-insensitive fundamental mode and lower order mode lasing in proton implanted VCSELs at a lasing wavelength of 850 nm. Higher refractive index dielectric materials such as amorphous silicon (a-Si) can be used to increase the effectiveness of the anti-phase filter on proton implanted devices by reducing the threshold modal gain of any spatially overlapping modes. This additive, non-destructive method allows for mode selection at any lasing wavelength and for any VCSEL layer structure without the need for semiconductor etching or epitaxial regrowth. It also offers the capability of designing a filter based upon available optical coating materials.

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.

RADC Multi-Dimensional Signal-Processing Research Program.

DTIC Science & Technology

1980-09-30

Formulation 7 3.2.2 Methods of Accelerating Convergence 8 3.2.3 Application to Image Deblurring 8 3.2.4 Extensions 11 3.3 Convergence of Iterative Signal... noise -driven linear filters, permit development of the joint probability density function oz " kelihood function for the image. With an expression...spatial linear filter driven by white noise (see Fig. i). If the probability density function for the white noise is known, Fig. t. Model for image

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.

Low-complexity DOA estimation from short data snapshots for ULA systems using the annihilating filter technique

NASA Astrophysics Data System (ADS)

Bellili, Faouzi; Amor, Souheib Ben; Affes, Sofiène; Ghrayeb, Ali

2017-12-01

This paper addresses the problem of DOA estimation using uniform linear array (ULA) antenna configurations. We propose a new low-cost method of multiple DOA estimation from very short data snapshots. The new estimator is based on the annihilating filter (AF) technique. It is non-data-aided (NDA) and does not impinge therefore on the whole throughput of the system. The noise components are assumed temporally and spatially white across the receiving antenna elements. The transmitted signals are also temporally and spatially white across the transmitting sources. The new method is compared in performance to the Cramér-Rao lower bound (CRLB), the root-MUSIC algorithm, the deterministic maximum likelihood estimator and another Bayesian method developed precisely for the single snapshot case. Simulations show that the new estimator performs well over a wide SNR range. Prominently, the main advantage of the new AF-based method is that it succeeds in accurately estimating the DOAs from short data snapshots and even from a single snapshot outperforming by far the state-of-the-art techniques both in DOA estimation accuracy and computational cost.

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.

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

Wavelength Scanning with a Tilting Interference Filter for Glow-Discharge Elemental Imaging.

PubMed

Storey, Andrew P; Ray, Steven J; Hoffmann, Volker; Voronov, Maxim; Engelhard, Carsten; Buscher, Wolfgang; Hieftje, Gary M

2017-06-01

Glow discharges have long been used for depth profiling and bulk analysis of solid samples. In addition, over the past decade, several methods of obtaining lateral surface elemental distributions have been introduced, each with its own strengths and weaknesses. Challenges for each of these techniques are acceptable optical throughput and added instrumental complexity. Here, these problems are addressed with a tilting-filter instrument. A pulsed glow discharge is coupled to an optical system comprising an adjustable-angle tilting filter, collimating and imaging lenses, and a gated, intensified charge-coupled device (CCD) camera, which together provide surface elemental mapping of solid samples. The tilting-filter spectrometer is instrumentally simpler, produces less image distortion, and achieves higher optical throughput than a monochromator-based instrument, but has a much more limited tunable spectral range and poorer spectral resolution. As a result, the tilting-filter spectrometer is limited to single-element or two-element determinations, and only when the target spectral lines fall within an appropriate spectral range and can be spectrally discerned. Spectral interferences that result from heterogeneous impurities can be flagged and overcome by observing the spatially resolved signal response across the available tunable spectral range. The instrument has been characterized and evaluated for the spatially resolved analysis of glow-discharge emission from selected but representative samples.

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.

Interpolating seismic data via the POCS method based on shearlet transform

NASA Astrophysics Data System (ADS)

Jicheng, Liu; Yongxin, Chou; Jianjiang, Zhu

2018-06-01

A method based on shearlet transform and the projection onto convex sets with L0-norm constraint is proposed to interpolate irregularly sampled 2D and 3D seismic data. The 2D directional filter of shearlet transform is constructed by modulating a low-pass diamond filter pair to minimize the effect of additional edges introduced by the missing traces. In order to abate the spatial aliasing and control the maximal gap between missing traces for a 3D data cube, a 2D separable jittered sampling strategy is discussed. Finally, numerical experiments on 2D and 3D synthetic and real data with different under-sampling rates prove the validity of the proposed method.

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.

Dynamic Transmit-Receive Beamforming by Spatial Matched Filtering for Ultrasound Imaging with Plane Wave Transmission.

PubMed

Chen, Yuling; Lou, Yang; Yen, Jesse

2017-07-01

During conventional ultrasound imaging, the need for multiple transmissions for one image and the time of flight for a desired imaging depth limit the frame rate of the system. Using a single plane wave pulse during each transmission followed by parallel receive processing allows for high frame rate imaging. However, image quality is degraded because of the lack of transmit focusing. Beamforming by spatial matched filtering (SMF) is a promising method which focuses ultrasonic energy using spatial filters constructed from the transmit-receive impulse response of the system. Studies by other researchers have shown that SMF beamforming can provide dynamic transmit-receive focusing throughout the field of view. In this paper, we apply SMF beamforming to plane wave transmissions (PWTs) to achieve both dynamic transmit-receive focusing at all imaging depths and high imaging frame rate (>5000 frames per second). We demonstrated the capability of the combined method (PWT + SMF) of achieving two-way focusing mathematically through analysis based on the narrowband Rayleigh-Sommerfeld diffraction theory. Moreover, the broadband performance of PWT + SMF was quantified in terms of lateral resolution and contrast from both computer simulations and experimental data. Results were compared between SMF beamforming and conventional delay-and-sum (DAS) beamforming in both simulations and experiments. At an imaging depth of 40 mm, simulation results showed a 29% lateral resolution improvement and a 160% contrast improvement with PWT + SMF. These improvements were 17% and 48% for experimental data with noise.

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

A coupling method for a cardiovascular simulation model which includes the Kalman filter.

PubMed

Hasegawa, Yuki; Shimayoshi, Takao; Amano, Akira; Matsuda, Tetsuya

2012-01-01

Multi-scale models of the cardiovascular system provide new insight that was unavailable with in vivo and in vitro experiments. For the cardiovascular system, multi-scale simulations provide a valuable perspective in analyzing the interaction of three phenomenons occurring at different spatial scales: circulatory hemodynamics, ventricular structural dynamics, and myocardial excitation-contraction. In order to simulate these interactions, multiscale cardiovascular simulation systems couple models that simulate different phenomena. However, coupling methods require a significant amount of calculation, since a system of non-linear equations must be solved for each timestep. Therefore, we proposed a coupling method which decreases the amount of calculation by using the Kalman filter. In our method, the Kalman filter calculates approximations for the solution to the system of non-linear equations at each timestep. The approximations are then used as initial values for solving the system of non-linear equations. The proposed method decreases the number of iterations required by 94.0% compared to the conventional strong coupling method. When compared with a smoothing spline predictor, the proposed method required 49.4% fewer iterations.

Technical Note: Image filtering to make computer-aided detection robust to image reconstruction kernel choice in lung cancer CT screening

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

Ohkubo, Masaki, E-mail: mook@clg.niigata-u.ac.jp

Purpose: In lung cancer computed tomography (CT) screening, the performance of a computer-aided detection (CAD) system depends on the selection of the image reconstruction kernel. To reduce this dependence on reconstruction kernels, the authors propose a novel application of an image filtering method previously proposed by their group. Methods: The proposed filtering process uses the ratio of modulation transfer functions (MTFs) of two reconstruction kernels as a filtering function in the spatial-frequency domain. This method is referred to as MTF{sub ratio} filtering. Test image data were obtained from CT screening scans of 67 subjects who each had one nodule. Imagesmore » were reconstructed using two kernels: f{sub STD} (for standard lung imaging) and f{sub SHARP} (for sharp edge-enhancement lung imaging). The MTF{sub ratio} filtering was implemented using the MTFs measured for those kernels and was applied to the reconstructed f{sub SHARP} images to obtain images that were similar to the f{sub STD} images. A mean filter and a median filter were applied (separately) for comparison. All reconstructed and filtered images were processed using their prototype CAD system. Results: The MTF{sub ratio} filtered images showed excellent agreement with the f{sub STD} images. The standard deviation for the difference between these images was very small, ∼6.0 Hounsfield units (HU). However, the mean and median filtered images showed larger differences of ∼48.1 and ∼57.9 HU from the f{sub STD} images, respectively. The free-response receiver operating characteristic (FROC) curve for the f{sub SHARP} images indicated poorer performance compared with the FROC curve for the f{sub STD} images. The FROC curve for the MTF{sub ratio} filtered images was equivalent to the curve for the f{sub STD} images. However, this similarity was not achieved by using the mean filter or median filter. Conclusions: The accuracy of MTF{sub ratio} image filtering was verified and the method was demonstrated to be effective for reducing the kernel dependence of CAD performance.« less

Quantification of the Spatial Distribution of Radionuclides in Field Lysimeters with a Collimated High-Resolution Gamma-Ray Spectrometer

NASA Astrophysics Data System (ADS)

Erdmann, Bryan James

The objective of this work is to quantify the one-dimensional spatial distribution of radionuclides in field lysimeters from the Radionuclide Field Lysimeter Experiment (RadFLEX) facility at the Savannah River Nationals Laboratory (SRNL). The lysimeters, containing 137Cs, 60Co, 133Ba and 152Eu incorporated either into solid wasteforms (Portland cement and reducing grout) or introduced into soil via a filter paper wasteform, were weathered for three to four years. The initial contaminant activities range from 4.0 to 9.0 MBq for the cementitious wasteforms and 0.25 to 0.47 MBq for the filter paper wasteform. An analytical method was developed to perform non-destructive measurements to quantify the spatial distributions measured in field lysimeters. This method provides an alternative to traditional destructive techniques to determine the spatial distribution of activity. This non-destructive method also allows for multiple scans to be performed periodically. Observing how these distributions change with time would improve modeling transport parameters. The detection system consists of a collimated high-purity germanium (HPGe) radiation detector coupled with a linear translational table. A lead collimator is used to achieve spatial resolution as high as 0.25 cm. The lysimeters are positioned relative to the detector using a linear translation stage that can move vertically via a computercontrolled stepping motor. A user control interface was developed with National Instruments LabVIEWRTM that synchronizes the data acquisition from the radiation detector with the lysimeter movement and positioning thus allowing the lysimeter scans to be automated. The detection efficiency of the system was investigated using two methods. Europium-152 is an ideal candidate for calibration source due to its multiple gamma-ray emissions across a wide range of energies. One method uses a 152Eu point source as the calibration standard while the other method uses the 152Eu within the lysimeter systems themselves as the calibration standard. These methods show that system geometry and source distribution are the key factors influencing the detection efficiency. This suggest that to reduce the impact from the source distribution and geometry variability within a volume, that lysimeters be rotated during measurements. These scans showed downward mobility of 60Co and 133Ba when the radionuclides were incorporated directly into the Savannah River Site (SRS) soil via the filter paper wasteform. When radionuclides were incorporated into the cementitious wasteforms positioned in the SRSS soil, 137Cs exhibited both upward and downward dispersion while the other radionuclides showed no movement. This dispersion was more significant for the Portland cement than the reducing grout wasteform. In the case of the filter paper wasteform, 137Cs mobility was greatly reduced. This suggests the presence of a cementitious wasteform enhances 137Cs mobility. The movement of 137Cs from the solid wasteform was modelled using a retarded diffusion model. Retardation factors for 137Cs are determined to range from approximately 700-2500 for Portland cement, 1500-4000 for reducing grout, and up to 2500-8000 the filter paper wasteform. Numerical simulations were run to investigate the hypothesis that ions released from the wasteforms compete for sorption sites in the SRS soil, enhancing the mobility of 137Cs. These simulations suggest ion-competition could be a factor, but more data is needed to explore this mechanism for Cs+ transport. Understanding radionuclide movement in the environment is important for informing strategies used for waste management and disposal.

An improved ring removal procedure for in-line x-ray phase contrast tomography

NASA Astrophysics Data System (ADS)

Massimi, Lorenzo; Brun, Francesco; Fratini, Michela; Bukreeva, Inna; Cedola, Alessia

2018-02-01

The suppression of ring artifacts in x-ray computed tomography (CT) is a required step in practical applications; it can be addressed by introducing refined digital low pass filters within the reconstruction process. However, these filters may introduce additional ringing artifacts when simultaneously imaging pure phase objects and elements having a non-negligible absorption coefficient. Ringing originates at sharp interfaces, due to the truncation of spatial high frequencies, and severely affects qualitative and quantitative analysis of the reconstructed slices. In this work, we discuss the causes of ringing artifacts, and present a general compensation procedure to account for it. The proposed procedure has been tested with CT datasets of the mouse central nervous system acquired at different synchrotron radiation facilities. The results demonstrate that the proposed method compensates for ringing artifacts induced by low pass ring removal filters. The effectiveness of the ring suppression filters is not altered; the proposed method can thus be considered as a framework to improve the ring removal step, regardless of the specific filter adopted or the imaged sample.

An improved ring removal procedure for in-line x-ray phase contrast tomography.

PubMed

Massimi, Lorenzo; Brun, Francesco; Fratini, Michela; Bukreeva, Inna; Cedola, Alessia

2018-02-12

The suppression of ring artifacts in x-ray computed tomography (CT) is a required step in practical applications; it can be addressed by introducing refined digital low pass filters within the reconstruction process. However, these filters may introduce additional ringing artifacts when simultaneously imaging pure phase objects and elements having a non-negligible absorption coefficient. Ringing originates at sharp interfaces, due to the truncation of spatial high frequencies, and severely affects qualitative and quantitative analysis of the reconstructed slices. In this work, we discuss the causes of ringing artifacts, and present a general compensation procedure to account for it. The proposed procedure has been tested with CT datasets of the mouse central nervous system acquired at different synchrotron radiation facilities. The results demonstrate that the proposed method compensates for ringing artifacts induced by low pass ring removal filters. The effectiveness of the ring suppression filters is not altered; the proposed method can thus be considered as a framework to improve the ring removal step, regardless of the specific filter adopted or the imaged sample.

Union operation image processing of data cubes separately processed by different objective filters and its application to void analysis in an all-solid-state lithium-ion battery.

PubMed

Yamamoto, Yuta; Iriyama, Yasutoshi; Muto, Shunsuke

2016-04-01

In this article, we propose a smart image-analysis method suitable for extracting target features with hierarchical dimension from original data. The method was applied to three-dimensional volume data of an all-solid lithium-ion battery obtained by the automated sequential sample milling and imaging process using a focused ion beam/scanning electron microscope to investigate the spatial configuration of voids inside the battery. To automatically fully extract the shape and location of the voids, three types of filters were consecutively applied: a median blur filter to extract relatively larger voids, a morphological opening operation filter for small dot-shaped voids and a morphological closing operation filter for small voids with concave contrasts. Three data cubes separately processed by the above-mentioned filters were integrated by a union operation to the final unified volume data, which confirmed the correct extraction of the voids over the entire dimension contained in the original data. © The Author 2015. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

On controlling nonlinear dissipation in high order filter methods for ideal and non-ideal MHD

NASA Technical Reports Server (NTRS)

Yee, H. C.; Sjogreen, B.

2004-01-01

The newly developed adaptive numerical dissipation control in spatially high order filter schemes for the compressible Euler and Navier-Stokes equations has been recently extended to the ideal and non-ideal magnetohydrodynamics (MHD) equations. These filter schemes are applicable to complex unsteady MHD high-speed shock/shear/turbulence problems. They also provide a natural and efficient way for the minimization of Div(B) numerical error. The adaptive numerical dissipation mechanism 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 from numerical dissipation contamination. The numerical dissipation considered consists of high order linear dissipation for the suppression of high frequency oscillation and the nonlinear dissipative portion of high-resolution shock-capturing methods for discontinuity capturing. The applicable nonlinear dissipative portion of high-resolution shock-capturing methods is very general. The objective of this paper is to investigate the performance of three commonly used types of nonlinear numerical dissipation for both the ideal and non-ideal MHD.

Efficient data assimilation algorithm for bathymetry application

NASA Astrophysics Data System (ADS)

Ghorbanidehno, H.; Lee, J. H.; Farthing, M.; Hesser, T.; Kitanidis, P. K.; Darve, E. F.

2017-12-01

Information on the evolving state of the nearshore zone bathymetry is crucial to shoreline management, recreational safety, and naval operations. The high cost and complex logistics of using ship-based surveys for bathymetry estimation have encouraged the use of remote sensing techniques. Data assimilation methods combine the remote sensing data and nearshore hydrodynamic models to estimate the unknown bathymetry and the corresponding uncertainties. In particular, several recent efforts have combined Kalman Filter-based techniques such as ensembled-based Kalman filters with indirect video-based observations to address the bathymetry inversion problem. However, these methods often suffer from ensemble collapse and uncertainty underestimation. Here, the Compressed State Kalman Filter (CSKF) method is used to estimate the bathymetry based on observed wave celerity. In order to demonstrate the accuracy and robustness of the CSKF method, we consider twin tests with synthetic observations of wave celerity, while the bathymetry profiles are chosen based on surveys taken by the U.S. Army Corps of Engineer Field Research Facility (FRF) in Duck, NC. The first test case is a bathymetry estimation problem for a spatially smooth and temporally constant bathymetry profile. The second test case is a bathymetry estimation problem for a temporally evolving bathymetry from a smooth to a non-smooth profile. For both problems, we compare the results of CSKF with those obtained by the local ensemble transform Kalman filter (LETKF), which is a popular ensemble-based Kalman filter method.

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.

A novel spatial-temporal detection method of dim infrared moving small target

NASA Astrophysics Data System (ADS)

Chen, Zhong; Deng, Tao; Gao, Lei; Zhou, Heng; Luo, Song

2014-09-01

Moving small target detection under complex background in infrared image sequence is one of the major challenges of modern military in Early Warning Systems (EWS) and the use of Long-Range Strike (LRS). However, because of the low SNR and undulating background, the infrared moving small target detection is a difficult problem in a long time. To solve this problem, a novel spatial-temporal detection method based on bi-dimensional empirical mode decomposition (EMD) and time-domain difference is proposed in this paper. This method is downright self-data decomposition and do not rely on any transition kernel function, so it has a strong adaptive capacity. Firstly, we generalized the 1D EMD algorithm to the 2D case. In this process, the project has solved serial issues in 2D EMD, such as large amount of data operations, define and identify extrema in 2D case, and two-dimensional signal boundary corrosion. The EMD algorithm studied in this project can be well adapted to the automatic detection of small targets under low SNR and complex background. Secondly, considering the characteristics of moving target, we proposed an improved filtering method based on three-frame difference on basis of the original difference filtering in time-domain, which greatly improves the ability of anti-jamming algorithm. Finally, we proposed a new time-space fusion method based on a combined processing of 2D EMD and improved time-domain differential filtering. And, experimental results show that this method works well in infrared small moving target detection under low SNR and complex background.

QUANTIFYING SPATIAL POSITION OF WETLANDS FOR STREAM HABITAT QUALITY PREDICTION

EPA Science Inventory

A watershed's capacity to store and filter water, and the resulting effects on the hydrologic regine, is a key forcing function for insteam processes and community structure. However, methods for describing wetland position have traditionally been qualitative. A Geographic Info...

Comparison between wavelet transform and moving average as filter method of MODIS imagery to recognize paddy cropping pattern in West Java

NASA Astrophysics Data System (ADS)

Dwi Nugroho, Kreshna; Pebrianto, Singgih; Arif Fatoni, Muhammad; Fatikhunnada, Alvin; Liyantono; Setiawan, Yudi

2017-01-01

Information on the area and spatial distribution of paddy field are needed to support sustainable agricultural and food security program. Mapping or distribution of cropping pattern paddy field is important to obtain sustainability paddy field area. It can be done by direct observation and remote sensing method. This paper discusses remote sensing for paddy field monitoring based on MODIS time series data. In time series MODIS data, difficult to direct classified of data, because of temporal noise. Therefore wavelet transform and moving average are needed as filter methods. The Objective of this study is to recognize paddy cropping pattern with wavelet transform and moving average in West Java using MODIS imagery (MOD13Q1) from 2001 to 2015 then compared between both of methods. The result showed the spatial distribution almost have the same cropping pattern. The accuracy of wavelet transform (75.5%) is higher than moving average (70.5%). Both methods showed that the majority of the cropping pattern in West Java have pattern paddy-fallow-paddy-fallow with various time planting. The difference of the planting schedule was occurs caused by the availability of irrigation water.

An unsupervised technique for optimal feature selection in attribute profiles for spectral-spatial classification of hyperspectral images

NASA Astrophysics Data System (ADS)

Bhardwaj, Kaushal; Patra, Swarnajyoti

2018-04-01

Inclusion of spatial information along with spectral features play a significant role in classification of remote sensing images. Attribute profiles have already proved their ability to represent spatial information. In order to incorporate proper spatial information, multiple attributes are required and for each attribute large profiles need to be constructed by varying the filter parameter values within a wide range. Thus, the constructed profiles that represent spectral-spatial information of an hyperspectral image have huge dimension which leads to Hughes phenomenon and increases computational burden. To mitigate these problems, this work presents an unsupervised feature selection technique that selects a subset of filtered image from the constructed high dimensional multi-attribute profile which are sufficiently informative to discriminate well among classes. In this regard the proposed technique exploits genetic algorithms (GAs). The fitness function of GAs are defined in an unsupervised way with the help of mutual information. The effectiveness of the proposed technique is assessed using one-against-all support vector machine classifier. The experiments conducted on three hyperspectral data sets show the robustness of the proposed method in terms of computation time and classification accuracy.

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.

Speeding Up the Bilateral Filter: A Joint Acceleration Way.

PubMed

Dai, Longquan; Yuan, Mengke; Zhang, Xiaopeng

2016-06-01

Computational complexity of the brute-force implementation of the bilateral filter (BF) depends on its filter kernel size. To achieve the constant-time BF whose complexity is irrelevant to the kernel size, many techniques have been proposed, such as 2D box filtering, dimension promotion, and shiftability property. Although each of the above techniques suffers from accuracy and efficiency problems, previous algorithm designers were used to take only one of them to assemble fast implementations due to the hardness of combining them together. Hence, no joint exploitation of these techniques has been proposed to construct a new cutting edge implementation that solves these problems. Jointly employing five techniques: kernel truncation, best N-term approximation as well as previous 2D box filtering, dimension promotion, and shiftability property, we propose a unified framework to transform BF with arbitrary spatial and range kernels into a set of 3D box filters that can be computed in linear time. To the best of our knowledge, our algorithm is the first method that can integrate all these acceleration techniques and, therefore, can draw upon one another's strong point to overcome deficiencies. The strength of our method has been corroborated by several carefully designed experiments. In particular, the filtering accuracy is significantly improved without sacrificing the efficiency at running time.

Fingerprint image enhancement by differential hysteresis processing.

PubMed

Blotta, Eduardo; Moler, Emilce

2004-05-10

A new method to enhance defective fingerprints images through image digital processing tools is presented in this work. When the fingerprints have been taken without any care, blurred and in some cases mostly illegible, as in the case presented here, their classification and comparison becomes nearly impossible. A combination of spatial domain filters, including a technique called differential hysteresis processing (DHP), is applied to improve these kind of images. This set of filtering methods proved to be satisfactory in a wide range of cases by uncovering hidden details that helped to identify persons. Dactyloscopy experts from Policia Federal Argentina and the EAAF have validated these results.

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.

Chromotomography for a rotating-prism instrument using backprojection, then filtering.

PubMed

Deming, Ross W

2006-08-01

A simple closed-form solution is derived for reconstructing a 3D spatial-chromatic image cube from a set of chromatically dispersed 2D image frames. The algorithm is tailored for a particular instrument in which the dispersion element is a matching set of mechanically rotated direct vision prisms positioned between a lens and a focal plane array. By using a linear operator formalism to derive the Tikhonov-regularized pseudoinverse operator, it is found that the unique minimum-norm solution is obtained by applying the adjoint operator, followed by 1D filtering with respect to the chromatic variable. Thus the filtering and backprojection (adjoint) steps are applied in reverse order relative to an existing method. Computational efficiency is provided by use of the fast Fourier transform in the filtering step.

Tunable output-frequency filter algorithm for imaging through scattering media under LED illumination

NASA Astrophysics Data System (ADS)

Zhou, Meiling; Singh, Alok Kumar; Pedrini, Giancarlo; Osten, Wolfgang; Min, Junwei; Yao, Baoli

2018-03-01

We present a tunable output-frequency filter (TOF) algorithm to reconstruct the object from noisy experimental data under low-power partially coherent illumination, such as LED, when imaging through scattering media. In the iterative algorithm, we employ Gaussian functions with different filter windows at different stages of iteration process to reduce corruption from experimental noise to search for a global minimum in the reconstruction. In comparison with the conventional iterative phase retrieval algorithm, we demonstrate that the proposed TOF algorithm achieves consistent and reliable reconstruction in the presence of experimental noise. Moreover, the spatial resolution and distinctive features are retained in the reconstruction since the filter is applied only to the region outside the object. The feasibility of the proposed method is proved by experimental results.

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

Zeroth-order phase-contrast technique.

PubMed

Pizolato, José Carlos; Cirino, Giuseppe Antonio; Gonçalves, Cristhiane; Neto, Luiz Gonçalves

2007-11-01

What we believe to be a new phase-contrast technique is proposed to recover intensity distributions from phase distributions modulated by spatial light modulators (SLMs) and binary diffractive optical elements (DOEs). The phase distribution is directly transformed into intensity distributions using a 4f optical correlator and an iris centered in the frequency plane as a spatial filter. No phase-changing plates or phase dielectric dots are used as a filter. This method allows the use of twisted nematic liquid-crystal televisions (LCTVs) operating in the real-time phase-mostly regime mode between 0 and p to generate high-intensity multiple beams for optical trap applications. It is also possible to use these LCTVs as input SLMs for optical correlators to obtain high-intensity Fourier transform distributions of input amplitude objects.

Multichannel spatial auditory display for speech communications

NASA Technical Reports Server (NTRS)

Begault, D. R.; Erbe, T.; Wenzel, E. M. (Principal Investigator)

1994-01-01

A spatial auditory display for multiple speech communications was developed at NASA/Ames Research Center. Input is spatialized by the use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four-letter call signs used by launch personnel at NASA against diotic speech babble. Spatial positions at 30 degrees azimuth increments were evaluated. The results from eight subjects showed a maximum intelligibility improvement of about 6-7 dB when the signal was spatialized to 60 or 90 degrees azimuth positions.

Multi-channel spatial auditory display for speech communications

NASA Astrophysics Data System (ADS)

Begault, Durand; Erbe, Tom

1993-10-01

A spatial auditory display for multiple speech communications was developed at NASA-Ames Research Center. Input is spatialized by use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four letter call signs used by launch personnel at NASA, against diotic speech babble. Spatial positions at 30 deg azimuth increments were evaluated. The results from eight subjects showed a maximal intelligibility improvement of about 6 to 7 dB when the signal was spatialized to 60 deg or 90 deg azimuth positions.

Multichannel spatial auditory display for speech communications.

PubMed

Begault, D R; Erbe, T

1994-10-01

A spatial auditory display for multiple speech communications was developed at NASA/Ames Research Center. Input is spatialized by the use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four-letter call signs used by launch personnel at NASA against diotic speech babble. Spatial positions at 30 degrees azimuth increments were evaluated. The results from eight subjects showed a maximum intelligibility improvement of about 6-7 dB when the signal was spatialized to 60 or 90 degrees azimuth positions.

Multichannel Spatial Auditory Display for Speed Communications

NASA Technical Reports Server (NTRS)

Begault, Durand R.; Erbe, Tom

1994-01-01

A spatial auditory display for multiple speech communications was developed at NASA/Ames Research Center. Input is spatialized by the use of simplifiedhead-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four-letter call signs used by launch personnel at NASA against diotic speech babble. Spatial positions at 30 degree azimuth increments were evaluated. The results from eight subjects showed a maximum intelligibility improvement of about 6-7 dB when the signal was spatialized to 60 or 90 degree azimuth positions.

Multi-channel spatial auditory display for speech communications

NASA Technical Reports Server (NTRS)

Begault, Durand; Erbe, Tom

1993-01-01

A spatial auditory display for multiple speech communications was developed at NASA-Ames Research Center. Input is spatialized by use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four letter call signs used by launch personnel at NASA, against diotic speech babble. Spatial positions at 30 deg azimuth increments were evaluated. The results from eight subjects showed a maximal intelligibility improvement of about 6 to 7 dB when the signal was spatialized to 60 deg or 90 deg azimuth positions.

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.

Multiscale vector fields for image pattern recognition

NASA Technical Reports Server (NTRS)

Low, Kah-Chan; Coggins, James M.

1990-01-01

A uniform processing framework for low-level vision computing in which a bank of spatial filters maps the image intensity structure at each pixel into an abstract feature space is proposed. Some properties of the filters and the feature space are described. Local orientation is measured by a vector sum in the feature space as follows: each filter's preferred orientation along with the strength of the filter's output determine the orientation and the length of a vector in the feature space; the vectors for all filters are summed to yield a resultant vector for a particular pixel and scale. The orientation of the resultant vector indicates the local orientation, and the magnitude of the vector indicates the strength of the local orientation preference. Limitations of the vector sum method are discussed. Investigations show that the processing framework provides a useful, redundant representation of image structure across orientation and scale.

Bayesian Tracking of Emerging Epidemics Using Ensemble Optimal Statistical Interpolation

PubMed Central

Cobb, Loren; Krishnamurthy, Ashok; Mandel, Jan; Beezley, Jonathan D.

2014-01-01

We present a preliminary test of the Ensemble Optimal Statistical Interpolation (EnOSI) method for the statistical tracking of an emerging epidemic, with a comparison to its popular relative for Bayesian data assimilation, the Ensemble Kalman Filter (EnKF). The spatial data for this test was generated by a spatial susceptible-infectious-removed (S-I-R) epidemic model of an airborne infectious disease. Both tracking methods in this test employed Poisson rather than Gaussian noise, so as to handle epidemic data more accurately. The EnOSI and EnKF tracking methods worked well on the main body of the simulated spatial epidemic, but the EnOSI was able to detect and track a distant secondary focus of infection that the EnKF missed entirely. PMID:25113590

Off-axis illumination direct-to-digital holography

DOEpatents

Thomas, Clarence E.; Price, Jeffery R.; Voelkl, Edgar; Hanson, Gregory R.

2004-06-08

Systems and methods are described for off-axis illumination direct-to-digital holography. A method of recording an off-axis illuminated spatially heterodyne hologram including spatially heterodyne fringes for Fourier analysis, includes: reflecting a reference beam from a reference mirror at a non-normal angle; reflecting an object beam from an object at an angle with respect to an optical axis defined by a focusing lens; focusing the reference beam and the object beam at a focal plane of a digital recorder to form the off-axis illuminated spatially heterodyne hologram including spatially heterodyne fringes for Fourier analysis; digitally recording the off-axis illuminated spatially heterodyne hologram including spatially heterodyne fringes for Fourier analysis; Fourier analyzing the recorded off-axis illuminated spatially heterodyne hologram including spatially heterodyne fringes by transforming axes of the recorded off-axis illuminated spatially heterodyne hologram including spatially heterodyne fringes in Fourier space to sit on top of a heterodyne carrier frequency defined as an angle between the reference beam and the object beam; applying a digital filter to cut off signals around an original origin; and then performing an inverse Fourier transform.

Evolutionary Algorithm Based Feature Optimization for Multi-Channel EEG Classification.

PubMed

Wang, Yubo; Veluvolu, Kalyana C

2017-01-01

The most BCI systems that rely on EEG signals employ Fourier based methods for time-frequency decomposition for feature extraction. The band-limited multiple Fourier linear combiner is well-suited for such band-limited signals due to its real-time applicability. Despite the improved performance of these techniques in two channel settings, its application in multiple-channel EEG is not straightforward and challenging. As more channels are available, a spatial filter will be required to eliminate the noise and preserve the required useful information. Moreover, multiple-channel EEG also adds the high dimensionality to the frequency feature space. Feature selection will be required to stabilize the performance of the classifier. In this paper, we develop a new method based on Evolutionary Algorithm (EA) to solve these two problems simultaneously. The real-valued EA encodes both the spatial filter estimates and the feature selection into its solution and optimizes it with respect to the classification error. Three Fourier based designs are tested in this paper. Our results show that the combination of Fourier based method with covariance matrix adaptation evolution strategy (CMA-ES) has the best overall performance.

Infrasonic wind-noise reduction by barriers and spatial filters.

PubMed

Hedlin, Michael A H; Raspet, Richard

2003-09-01

This paper reports experimental observations of wind speed and infrasonic noise reduction inside a wind barrier. The barrier is compared with "rosette" spatial filters and with a reference site that uses no noise reduction system. The barrier is investigated for use at International Monitoring System (IMS) infrasound array sites where spatially extensive noise-reducing systems cannot be used because of a shortage of suitable land. Wind speed inside a 2-m-high 50%-porous hexagonal barrier coated with a fine wire mesh is reduced from ambient levels by 90%. If the infrasound wind-noise level reductions are all plotted versus the reduced frequency given by f*L/v, where L is the characteristic size of the array or barrier, f is the frequency, and v is the wind speed, the reductions at different wind speeds are observed to collapse into a single curve for each wind-noise reduction method. The reductions are minimal below a reduced frequency of 0.3 to 1, depending on the device, then spatial averaging over the turbulence structure leads to increased reduction. Above the reduced corner frequency, the barrier reduces infrasonic noise by up to 20 to 25 dB. Below the corner frequency the barrier displays a small reduction of about 4 dB. The rosettes display no reduction below the corner frequency. One other advantage of the wind barrier over rosette spatial filters is that the signal recorded inside the barrier enters the microbarometer from free air and is not integrated, possibly out of phase, after propagation through a system of narrow pipes.

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.

Experiences with digital processing of images at INPE

NASA Technical Reports Server (NTRS)

Mascarenhas, N. D. A. (Principal Investigator)

1984-01-01

Four different research experiments with digital image processing at INPE will be described: (1) edge detection by hypothesis testing; (2) image interpolation by finite impulse response filters; (3) spatial feature extraction methods in multispectral classification; and (4) translational image registration by sequential tests of hypotheses.

a Data Field Method for Urban Remotely Sensed Imagery Classification Considering Spatial Correlation

NASA Astrophysics Data System (ADS)

Zhang, Y.; Qin, K.; Zeng, C.; Zhang, E. B.; Yue, M. X.; Tong, X.

2016-06-01

Spatial correlation between pixels is important information for remotely sensed imagery classification. Data field method and spatial autocorrelation statistics have been utilized to describe and model spatial information of local pixels. The original data field method can represent the spatial interactions of neighbourhood pixels effectively. However, its focus on measuring the grey level change between the central pixel and the neighbourhood pixels results in exaggerating the contribution of the central pixel to the whole local window. Besides, Geary's C has also been proven to well characterise and qualify the spatial correlation between each pixel and its neighbourhood pixels. But the extracted object is badly delineated with the distracting salt-and-pepper effect of isolated misclassified pixels. To correct this defect, we introduce the data field method for filtering and noise limitation. Moreover, the original data field method is enhanced by considering each pixel in the window as the central pixel to compute statistical characteristics between it and its neighbourhood pixels. The last step employs a support vector machine (SVM) for the classification of multi-features (e.g. the spectral feature and spatial correlation feature). In order to validate the effectiveness of the developed method, experiments are conducted on different remotely sensed images containing multiple complex object classes inside. The results show that the developed method outperforms the traditional method in terms of classification accuracies.

Classifying Facial Actions

PubMed Central

Donato, Gianluca; Bartlett, Marian Stewart; Hager, Joseph C.; Ekman, Paul; Sejnowski, Terrence J.

2010-01-01

The Facial Action Coding System (FACS) [23] is an objective method for quantifying facial movement in terms of component actions. This system is widely used in behavioral investigations of emotion, cognitive processes, and social interaction. The coding is presently performed by highly trained human experts. This paper explores and compares techniques for automatically recognizing facial actions in sequences of images. These techniques include analysis of facial motion through estimation of optical flow; holistic spatial analysis, such as principal component analysis, independent component analysis, local feature analysis, and linear discriminant analysis; and methods based on the outputs of local filters, such as Gabor wavelet representations and local principal components. Performance of these systems is compared to naive and expert human subjects. Best performances were obtained using the Gabor wavelet representation and the independent component representation, both of which achieved 96 percent accuracy for classifying 12 facial actions of the upper and lower face. The results provide converging evidence for the importance of using local filters, high spatial frequencies, and statistical independence for classifying facial actions. PMID:21188284

Time Dependent Tomography of the Solar Corona in Three Spatial Dimensions

NASA Astrophysics Data System (ADS)

Butala, M. D.; Frazin, R. A.; Kamalabadi, F.

2006-12-01

The combination of the soon to be launched STEREO mission with SOHO will provide scientists with three simultaneous space-borne views of the Sun. The increase in available measurements will reduce the data acquisition time necessary to obtain 3D coronal electron density (N_e) estimates from coronagraph images using a technique called solar rotational tomography (SRT). However, the data acquisition period will still be long enough for the corona to dynamically evolve, requiring time dependent solar tomography. The Kalman filter (KF) would seem to be an ideal computational method for time dependent SRT. Unfortunately, the KF scales poorly with problem size and is, as a result, inapplicable. A Monte Carlo approximation to the KF called the localized ensemble Kalman filter was developed for massive applications and has the promise of making the time dependent estimation of the 3D coronal N_e possible. We present simulations showing that this method will make time dependent tomography in three spatial dimensions computationally feasible.

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.

The performance of the spatiotemporal Kalman filter and LORETA in seizure onset localization.

PubMed

Hamid, Laith; Sarabi, Masoud; Japaridze, Natia; Wiegand, Gert; Heute, Ulrich; Stephani, Ulrich; Galka, Andreas; Siniatchkin, Michael

2015-08-01

The assumption of spatial-smoothness is often used to solve the bioelectric inverse problem during electroencephalographic (EEG) source imaging, e.g., in low resolution electromagnetic tomography (LORETA). Since the EEG data show a temporal structure, the combination of the temporal-smoothness and the spatial-smoothness constraints may improve the solution of the EEG inverse problem. This study investigates the performance of the spatiotemporal Kalman filter (STKF) method, which is based on spatial and temporal smoothness, in the localization of a focal seizure's onset and compares its results to those of LORETA. The main finding of the study was that the STKF with an autoregressive model of order two significantly outperformed LORETA in the accuracy and consistency of the localization, provided that the source space consists of a whole-brain volumetric grid. In the future, these promising results will be confirmed using data from more patients and performing statistical analyses on the results. Furthermore, the effects of the temporal smoothness constraint will be studied using different types of focal seizures.

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.

Simple and sensitive technique for alignment of the pinhole of a spatial filter of a high-energy, high-power laser system.

PubMed

Sharma, Avnish Kumar; Patidar, Rajesh Kumar; Daiya, Deepak; Joshi, Anandverdhan; Naik, Prasad Anant; Gupta, Parshotam Dass

2013-04-20

In this paper, a new method for alignment of the pinhole of a spatial filter (SF) has been proposed and demonstrated experimentally. The effect of the misalignment of the pinhole on the laser beam profiles has been calculated for circular and elliptical Gaussian laser beams. Theoretical computation has been carried out to illustrate the effect of an intensity mask, placed before the focusing lens of the SF, on the spatial beam profile after the pinhole of the SF. It is shown, both theoretically and experimentally, that a simple intensity mask, consisting of a black dot, can be used to visually align the pinhole with a high accuracy of 5% of the pinhole diameter. The accuracy may be further improved using a computer-based image processing algorithm. Finally, the proposed technique has been demonstrated to align a vacuum SF of a compact 40 J Nd:phosphate glass laser system.

Optimization of confocal laser induced fluorescence for long focal length applications

NASA Astrophysics Data System (ADS)

Jemiolo, Andrew J.; Henriquez, Miguel F.; Thompson, Derek S.; Scime, Earl E.

2017-10-01

Laser induced fluorescence (LIF) is a non-perturbative diagnostic for measuring ion and neutral particle velocities and temperatures in a plasma. The conventional method for single-photon LIF requires intersecting optical paths for light injection and collection. The multiple vacuum windows needed for such measurements are unavailable in many plasma experiments. Confocal LIF eliminates the need for perpendicular intersecting optical paths by using concentric injection and collection paths through a single window. One of the main challenges with using confocal LIF is achieving high resolution measurements at the longer focal lengths needed for many plasma experiments. We present confocal LIF measurements in HELIX, a helicon plasma experiment at West Virginia University, demonstrating spatial resolution dependence on focal length and spatial filtering. By combining aberration mitigating optics with spatial filtering, our results show high resolution measurements at focal lengths of 0.5 m, long enough to access the interiors of many laboratory plasma experiments. This work was supported by U.S. National Science Foundation Grant No. PHY-1360278.

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.

Video denoising, deblocking, and enhancement through separable 4-D nonlocal spatiotemporal transforms.

PubMed

Maggioni, Matteo; Boracchi, Giacomo; Foi, Alessandro; Egiazarian, Karen

2012-09-01

We propose a powerful video filtering algorithm that exploits temporal and spatial redundancy characterizing natural video sequences. The algorithm implements the paradigm of nonlocal grouping and collaborative filtering, where a higher dimensional transform-domain representation of the observations is leveraged to enforce sparsity, and thus regularize the data: 3-D spatiotemporal volumes are constructed by tracking blocks along trajectories defined by the motion vectors. Mutually similar volumes are then grouped together by stacking them along an additional fourth dimension, thus producing a 4-D structure, termed group, where different types of data correlation exist along the different dimensions: local correlation along the two dimensions of the blocks, temporal correlation along the motion trajectories, and nonlocal spatial correlation (i.e., self-similarity) along the fourth dimension of the group. Collaborative filtering is then realized by transforming each group through a decorrelating 4-D separable transform and then by shrinkage and inverse transformation. In this way, the collaborative filtering provides estimates for each volume stacked in the group, which are then returned and adaptively aggregated to their original positions in the video. The proposed filtering procedure addresses several video processing applications, such as denoising, deblocking, and enhancement of both grayscale and color data. Experimental results prove the effectiveness of our method in terms of both subjective and objective visual quality, and show that it outperforms the state of the art in video denoising.

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.

Ensembles of adaptive spatial filters increase BCI performance: an online evaluation

NASA Astrophysics Data System (ADS)

Sannelli, Claudia; Vidaurre, Carmen; Müller, Klaus-Robert; Blankertz, Benjamin

2016-08-01

Objective: In electroencephalographic (EEG) data, signals from distinct sources within the brain are widely spread by volume conduction and superimposed such that sensors receive mixtures of a multitude of signals. This reduction of spatial information strongly hampers single-trial analysis of EEG data as, for example, required for brain-computer interfacing (BCI) when using features from spontaneous brain rhythms. Spatial filtering techniques are therefore greatly needed to extract meaningful information from EEG. Our goal is to show, in online operation, that common spatial pattern patches (CSPP) are valuable to counteract this problem. Approach: Even though the effect of spatial mixing can be encountered by spatial filters, there is a trade-off between performance and the requirement of calibration data. Laplacian derivations do not require calibration data at all, but their performance for single-trial classification is limited. Conversely, data-driven spatial filters, such as common spatial patterns (CSP), can lead to highly distinctive features; however they require a considerable amount of training data. Recently, we showed in an offline analysis that CSPP can establish a valuable compromise. In this paper, we confirm these results in an online BCI study. In order to demonstrate the paramount feature that CSPP requires little training data, we used them in an adaptive setting with 20 participants and focused on users who did not have success with previous BCI approaches. Main results: The results of the study show that CSPP adapts faster and thereby allows users to achieve better feedback within a shorter time than previous approaches performed with Laplacian derivations and CSP filters. The success of the experiment highlights that CSPP has the potential to further reduce BCI inefficiency. Significance: CSPP are a valuable compromise between CSP and Laplacian filters. They allow users to attain better feedback within a shorter time and thus reduce BCI inefficiency to one-fourth in comparison to previous non-adaptive paradigms.

Ensembles of adaptive spatial filters increase BCI performance: an online evaluation.

PubMed

Sannelli, Claudia; Vidaurre, Carmen; Müller, Klaus-Robert; Blankertz, Benjamin

2016-08-01

In electroencephalographic (EEG) data, signals from distinct sources within the brain are widely spread by volume conduction and superimposed such that sensors receive mixtures of a multitude of signals. This reduction of spatial information strongly hampers single-trial analysis of EEG data as, for example, required for brain-computer interfacing (BCI) when using features from spontaneous brain rhythms. Spatial filtering techniques are therefore greatly needed to extract meaningful information from EEG. Our goal is to show, in online operation, that common spatial pattern patches (CSPP) are valuable to counteract this problem. Even though the effect of spatial mixing can be encountered by spatial filters, there is a trade-off between performance and the requirement of calibration data. Laplacian derivations do not require calibration data at all, but their performance for single-trial classification is limited. Conversely, data-driven spatial filters, such as common spatial patterns (CSP), can lead to highly distinctive features; however they require a considerable amount of training data. Recently, we showed in an offline analysis that CSPP can establish a valuable compromise. In this paper, we confirm these results in an online BCI study. In order to demonstrate the paramount feature that CSPP requires little training data, we used them in an adaptive setting with 20 participants and focused on users who did not have success with previous BCI approaches. The results of the study show that CSPP adapts faster and thereby allows users to achieve better feedback within a shorter time than previous approaches performed with Laplacian derivations and CSP filters. The success of the experiment highlights that CSPP has the potential to further reduce BCI inefficiency. CSPP are a valuable compromise between CSP and Laplacian filters. They allow users to attain better feedback within a shorter time and thus reduce BCI inefficiency to one-fourth in comparison to previous non-adaptive paradigms.

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.

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

Practical way to avoid spurious geometrical contributions in Brillouin light scattering experiments at variable scattering angles.

PubMed

Battistoni, Andrea; Bencivenga, Filippo; Fioretto, Daniele; Masciovecchio, Claudio

2014-10-15

In this Letter, we present a simple method to avoid the well-known spurious contributions in the Brillouin light scattering (BLS) spectrum arising from the finite aperture of collection optics. The method relies on the use of special spatial filters able to select the scattered light with arbitrary precision around a given value of the momentum transfer (Q). We demonstrate the effectiveness of such filters by analyzing the BLS spectra of a reference sample as a function of scattering angle. This practical and inexpensive method could be an extremely useful tool to fully exploit the potentiality of Brillouin acoustic spectroscopy, as it will easily allow for effective Q-variable experiments with unparalleled luminosity and resolution.

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.

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.

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

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.

Cyclic additional optical true time delay for microwave beam steering with spectral filtering.

PubMed

Cao, Z; Lu, R; Wang, Q; Tessema, N; Jiao, Y; van den Boom, H P A; Tangdiongga, E; Koonen, A M J

2014-06-15

Optical true time delay (OTTD) is an attractive way to realize microwave beam steering (MBS) due to its inherent features of broadband, low-loss, and compactness. In this Letter, we propose a novel OTTD approach named cyclic additional optical true time delay (CAO-TTD). It applies additional integer delays of the microwave carrier frequency to achieve spectral filtering but without disturbing the spatial filtering (beam steering). Based on such concept, a broadband MBS scheme for high-capacity wireless communication is proposed, which allows the tuning of both spectral filtering and spatial filtering. The experimental results match well with the theoretical analysis.

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.

Guided filter-based fusion method for multiexposure images

NASA Astrophysics Data System (ADS)

Hou, Xinglin; Luo, Haibo; Qi, Feng; Zhou, Peipei

2016-11-01

It is challenging to capture a high-dynamic range (HDR) scene using a low-dynamic range camera. A weighted sum-based image fusion (IF) algorithm is proposed so as to express an HDR scene with a high-quality image. This method mainly includes three parts. First, two image features, i.e., gradients and well-exposedness are measured to estimate the initial weight maps. Second, the initial weight maps are refined by a guided filter, in which the source image is considered as the guidance image. This process could reduce the noise in initial weight maps and preserve more texture consistent with the original images. Finally, the fused image is constructed by a weighted sum of source images in the spatial domain. The main contributions of this method are the estimation of the initial weight maps and the appropriate use of the guided filter-based weight maps refinement. It provides accurate weight maps for IF. Compared to traditional IF methods, this algorithm avoids image segmentation, combination, and the camera response curve calibration. Furthermore, experimental results demonstrate the superiority of the proposed method in both subjective and objective evaluations.

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.

Detection of anomalous signals in temporally correlated data (Invited)

NASA Astrophysics Data System (ADS)

Langbein, J. O.

2010-12-01

Detection of transient tectonic signals in data obtained from large geodetic networks requires the ability to detect signals that are both temporally and spatially coherent. In this report I will describe a modification to an existing method that estimates both the coefficients of temporally correlated noise model and an efficient filter based on the noise model. This filter, when applied to the original time-series, effectively whitens (or flattens) the power spectrum. The filtered data provide the means to calculate running averages which are then used to detect deviations from the background trends. For large networks, time-series of signal-to-noise ratio (SNR) can be easily constructed since, by filtering, each of the original time-series has been transformed into one that is closer to having a Gaussian distribution with a variance of 1.0. Anomalous intervals may be identified by counting the number of GPS sites for which the SNR exceeds a specified value. For example, during one time interval, if there were 5 out of 20 time-series with SNR>2, this would be considered anomalous; typically, one would expect at 95% confidence that there would be at least 1 out of 20 time-series with an SNR>2. For time intervals with an anomalously large number of high SNR, the spatial distribution of the SNR is mapped to identify the location of the anomalous signal(s) and their degree of spatial clustering. Estimating the filter that should be used to whiten the data requires modification of the existing methods that employ maximum likelihood estimation to determine the temporal covariance of the data. In these methods, it is assumed that the noise components in the data are a combination of white, flicker and random-walk processes and that they are derived from three different and independent sources. Instead, in this new method, the covariance matrix is constructed assuming that only one source is responsible for the noise and that source can be represented as a white-noise random-number generator convolved with a filter whose spectral properties are frequency (f) independent at its highest frequencies, 1/f at the middle frequencies, and 1/f2 at the lowest frequencies. For data sets with no gaps in their time-series, construction of covariance and inverse covariance matrices is extremely efficient. Application of the above algorithm to real data potentially involves several iterations as small, tectonic signals of interest are often indistinguishable from background noise. Consequently, simply plotting the time-series of each GPS site is used to identify the largest outliers and signals independent of their cause. Any analysis of the background noise levels must factor in these other signals while the gross outliers need to be removed.

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.

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.

Comparison of Two Methods of Noise Power Spectrum Determinations of Medical Radiography Systems

NASA Astrophysics Data System (ADS)

Hassan, Wan Muhamad Saridan Wan; Ahmed Darwish, Zeki

2011-03-01

Noise in medical images is recognized as an important factor that determines the image quality. Image noise is characterized by noise power spectrum (NPS). We compared two methods of NPS determination namely the methods of Wagner and Dobbins on Lanex Regular TMG screen-film system and Hologic Lorad Selenia full field digital mammography system, with the aim of choosing the better method to use. The methods differ in terms of various parametric choices and algorithm implementations. These parameters include the low pass filtering, low frequency filtering, windowing, smoothing, aperture correction, overlapping of region of interest (ROI), length of fast Fourier transform, ROI size, method of ROI normalization, and slice selection of the NPS. Overall, the two methods agreed to the practical value of noise power spectrum between 10-3-10-6 mm2 over spatial frequency range 0-10 mm-1.

Hollow core waveguide as mid-infrared laser modal beam filter

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

Patimisco, P.; Giglio, M.; Spagnolo, V.

2015-09-21

A novel method for mid-IR laser beam mode cleaning employing hollow core waveguide as a modal filter element is reported. The influence of the input laser beam quality on fiber optical losses and output beam profile using a hollow core waveguide with 200 μm-bore size was investigated. Our results demonstrate that even when using a laser with a poor spatial profile, there will exist a minimum fiber length that allows transmission of only the Gaussian-like fundamental waveguide mode from the fiber, filtering out all the higher order modes. This essentially single mode output is preserved also when the waveguide is bentmore » to a radius of curvature of 7.5 cm, which demonstrates that laser mode filtering can be realized even if a curved light path is required.« less

Spatiotemporal Filtering Using Principal Component Analysis and Karhunen-Loeve Expansion Approaches for Regional GPS Network Analysis

NASA Technical Reports Server (NTRS)

Dong, D.; Fang, P.; Bock, F.; Webb, F.; Prawirondirdjo, L.; Kedar, S.; Jamason, P.

2006-01-01

Spatial filtering is an effective way to improve the precision of coordinate time series for regional GPS networks by reducing so-called common mode errors, thereby providing better resolution for detecting weak or transient deformation signals. The commonly used approach to regional filtering assumes that the common mode error is spatially uniform, which is a good approximation for networks of hundreds of kilometers extent, but breaks down as the spatial extent increases. A more rigorous approach should remove the assumption of spatially uniform distribution and let the data themselves reveal the spatial distribution of the common mode error. The principal component analysis (PCA) and the Karhunen-Loeve expansion (KLE) both decompose network time series into a set of temporally varying modes and their spatial responses. Therefore they provide a mathematical framework to perform spatiotemporal filtering.We apply the combination of PCA and KLE to daily station coordinate time series of the Southern California Integrated GPS Network (SCIGN) for the period 2000 to 2004. We demonstrate that spatially and temporally correlated common mode errors are the dominant error source in daily GPS solutions. The spatial characteristics of the common mode errors are close to uniform for all east, north, and vertical components, which implies a very long wavelength source for the common mode errors, compared to the spatial extent of the GPS network in southern California. Furthermore, the common mode errors exhibit temporally nonrandom patterns.

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.

Spatial Standard Observer

NASA Technical Reports Server (NTRS)

Watson, Andrw B. (Inventor)

2010-01-01

The present invention relates to devices and methods for the measurement and/or for the specification of the perceptual intensity of a visual image. or the perceptual distance between a pair of images. Grayscale test and reference images are processed to produce test and reference luminance images. A luminance filter function is convolved with the reference luminance image to produce a local mean luminance reference image . Test and reference contrast images are produced from the local mean luminance reference image and the test and reference luminance images respectively, followed by application of a contrast sensitivity filter. The resulting images are combined according to mathematical prescriptions to produce a Just Noticeable Difference, JND value, indicative of a Spatial Standard Observer. SSO. Some embodiments include masking functions. window functions. special treatment for images lying on or near border and pre-processing of test images.

Spatial Standard Observer

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

2012-01-01

The present invention relates to devices and methods for the measurement and/or for the specification of the perceptual intensity of a visual image, or the perceptual distance between a pair of images. Grayscale test and reference images are processed to produce test and reference luminance images. A luminance filter function is convolved with the reference luminance image to produce a local mean luminance reference image. Test and reference contrast images are produced from the local mean luminance reference image and the test and reference luminance images respectively, followed by application of a contrast sensitivity filter. The resulting images are combined according to mathematical prescriptions to produce a Just Noticeable Difference, JND value, indicative of a Spatial Standard Observer, SSO. Some embodiments include masking functions, window functions, special treatment for images lying on or near borders and pre-processing of test images.

Deposition Uniformity of Coal Dust on Filters and Its Effect on the Accuracy of FTIR Analyses for Silica.

PubMed

Miller, Arthur L; Drake, Pamela L; Murphy, Nathaniel C; Cauda, Emanuele G; LeBouf, Ryan F; Markevicius, Gediminas

Miners are exposed to silica-bearing dust which can lead to silicosis, a potentially fatal lung disease. Currently, airborne silica is measured by collecting filter samples and sending them to a laboratory for analysis. Since this may take weeks, a field method is needed to inform decisions aimed at reducing exposures. This study investigates a field-portable Fourier transform infrared (FTIR) method for end-of-shift (EOS) measurement of silica on filter samples. Since the method entails localized analyses, spatial uniformity of dust deposition can affect accuracy and repeatability. The study, therefore, assesses the influence of radial deposition uniformity on the accuracy of the method. Using laboratory-generated Minusil and coal dusts and three different types of sampling systems, multiple sets of filter samples were prepared. All samples were collected in pairs to create parallel sets for training and validation. Silica was measured by FTIR at nine locations across the face of each filter and the data analyzed using a multiple regression analysis technique that compared various models for predicting silica mass on the filters using different numbers of "analysis shots." It was shown that deposition uniformity is independent of particle type (kaolin vs. silica), which suggests the role of aerodynamic separation is negligible. Results also reflected the correlation between the location and number of shots versus the predictive accuracy of the models. The coefficient of variation (CV) for the models when predicting mass of validation samples was 4%-51% depending on the number of points analyzed and the type of sampler used, which affected the uniformity of radial deposition on the filters. It was shown that using a single shot at the center of the filter yielded predictivity adequate for a field method, (93% return, CV approximately 15%) for samples collected with 3-piece cassettes.

A high-order spatial filter for a cubed-sphere spectral element model

NASA Astrophysics Data System (ADS)

Kang, Hyun-Gyu; Cheong, Hyeong-Bin

2017-04-01

A high-order spatial filter is developed for the spectral-element-method dynamical core on the cubed-sphere grid which employs the Gauss-Lobatto Lagrange interpolating polynomials (GLLIP) as orthogonal basis functions. The filter equation is the high-order Helmholtz equation which corresponds to the implicit time-differencing of a diffusion equation employing the high-order Laplacian. The Laplacian operator is discretized within a cell which is a building block of the cubed sphere grid and consists of the Gauss-Lobatto grid. When discretizing a high-order Laplacian, due to the requirement of C0 continuity along the cell boundaries the grid-points in neighboring cells should be used for the target cell: The number of neighboring cells is nearly quadratically proportional to the filter order. Discrete Helmholtz equation yields a huge-sized and highly sparse matrix equation whose size is N*N with N the number of total grid points on the globe. The number of nonzero entries is also almost in quadratic proportion to the filter order. Filtering is accomplished by solving the huge-matrix equation. While requiring a significant computing time, the solution of global matrix provides the filtered field free of discontinuity along the cell boundaries. To achieve the computational efficiency and the accuracy at the same time, the solution of the matrix equation was obtained by only accounting for the finite number of adjacent cells. This is called as a local-domain filter. It was shown that to remove the numerical noise near the grid-scale, inclusion of 5*5 cells for the local-domain filter was found sufficient, giving the same accuracy as that obtained by global domain solution while reducing the computing time to a considerably lower level. The high-order filter was evaluated using the standard test cases including the baroclinic instability of the zonal flow. Results indicated that the filter performs better on the removal of grid-scale numerical noises than the explicit high-order viscosity. It was also presented that the filter can be easily implemented on the distributed-memory parallel computers with a desirable scalability.

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.

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.

Methodology to estimate the relative pressure field from noisy experimental velocity data

NASA Astrophysics Data System (ADS)

Bolin, C. D.; Raguin, L. G.

2008-11-01

The determination of intravascular pressure fields is important to the characterization of cardiovascular pathology. We present a two-stage method that solves the inverse problem of estimating the relative pressure field from noisy velocity fields measured by phase contrast magnetic resonance imaging (PC-MRI) on an irregular domain with limited spatial resolution, and includes a filter for the experimental noise. For the pressure calculation, the Poisson pressure equation is solved by embedding the irregular flow domain into a regular domain. To lessen the propagation of the noise inherent to the velocity measurements, three filters - a median filter and two physics-based filters - are evaluated using a 2-D Couette flow. The two physics-based filters outperform the median filter for the estimation of the relative pressure field for realistic signal-to-noise ratios (SNR = 5 to 30). The most accurate pressure field results from a filter that applies in a least-squares sense three constraints simultaneously: consistency between measured and filtered velocity fields, divergence-free and additional smoothness conditions. This filter leads to a 5-fold gain in accuracy for the estimated relative pressure field compared to without noise filtering, in conditions consistent with PC-MRI of the carotid artery: SNR = 5, 20 x 20 discretized flow domain (25 X 25 computational domain).

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.

Project Report: Reducing Color Rivalry in Imagery for Conjugated Multiple Bandpass Filter Based Stereo Endoscopy

NASA Technical Reports Server (NTRS)

Ream, Allen

2011-01-01

A pair of conjugated multiple bandpass filters (CMBF) can be used to create spatially separated pupils in a traditional lens and imaging sensor system allowing for the passive capture of stereo video. This method is especially useful for surgical endoscopy where smaller cameras are needed to provide ample room for manipulating tools while also granting improved visualizations of scene depth. The significant issue in this process is that, due to the complimentary nature of the filters, the colors seen through each filter do not match each other, and also differ from colors as seen under a white illumination source. A color correction model was implemented that included optimized filter selection, such that the degree of necessary post-processing correction was minimized, and a chromatic adaptation transformation that attempted to fix the imaged colors tristimulus indices based on the principle of color constancy. Due to fabrication constraints, only dual bandpass filters were feasible. The theoretical average color error after correction between these filters was still above the fusion limit meaning that rivalry conditions are possible during viewing. This error can be minimized further by designing the filters for a subset of colors corresponding to specific working environments.

Robust adaptive multichannel SAR processing based on covariance matrix reconstruction

NASA Astrophysics Data System (ADS)

Tan, Zhen-ya; He, Feng

2018-04-01

With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.

Method of assessing heterogeneity in images

DOEpatents

Jacob, Richard E.; Carson, James P.

2016-08-23

A method of assessing heterogeneity in images is disclosed. 3D images of an object are acquired. The acquired images may be filtered and masked. Iterative decomposition is performed on the masked images to obtain image subdivisions that are relatively homogeneous. Comparative analysis, such as variogram analysis or correlogram analysis, is performed of the decomposed images to determine spatial relationships between regions of the images that are relatively homogeneous.

Multireference adaptive noise canceling applied to the EEG.

PubMed

James, C J; Hagan, M T; Jones, R D; Bones, P J; Carroll, G J

1997-08-01

The technique of multireference adaptive noise canceling (MRANC) is applied to enhance transient nonstationarities in the electroeancephalogram (EEG), with the adaptation implemented by means of a multilayer-perception artificial neural network (ANN). The method was applied to recorded EEG segments and the performance on documented nonstationarities recorded. The results show that the neural network (nonlinear) gives an improvement in performance (i.e., signal-to-noise ratio (SNR) of the nonstationarities) compared to a linear implementation of MRANC. In both cases an improvement in the SNR was obtained. The advantage of the spatial filtering aspect of MRANC is highlighted when the performance of MRANC is compared to that of the inverse auto-regressive filtering of the EEG, a purely temporal filter.

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.

Three-dimensional Image Reconstruction in J-PET Using Filtered Back-projection Method

NASA Astrophysics Data System (ADS)

Shopa, R. Y.; Klimaszewski, K.; Kowalski, P.; Krzemień, W.; Raczyński, L.; Wiślicki, W.; Białas, P.; Curceanu, C.; Czerwiński, E.; Dulski, K.; Gajos, A.; Głowacz, B.; Gorgol, M.; Hiesmayr, B.; Jasińska, B.; Kisielewska-Kamińska, D.; Korcyl, G.; Kozik, T.; Krawczyk, N.; Kubicz, E.; Mohammed, M.; Pawlik-Niedźwiecka, M.; Niedźwiecki, S.; Pałka, M.; Rudy, Z.; Sharma, N. G.; Sharma, S.; Silarski, M.; Skurzok, M.; Wieczorek, A.; Zgardzińska, B.; Zieliński, M.; Moskal, P.

We present a method and preliminary results of the image reconstruction in the Jagiellonian PET tomograph. Using GATE (Geant4 Application for Tomographic Emission), interactions of the 511 keV photons with a cylindrical detector were generated. Pairs of such photons, flying back-to-back, originate from e+e- annihilations inside a 1-mm spherical source. Spatial and temporal coordinates of hits were smeared using experimental resolutions of the detector. We incorporated the algorithm of the 3D Filtered Back Projection, implemented in the STIR and TomoPy software packages, which differ in approximation methods. Consistent results for the Point Spread Functions of ~5/7,mm and ~9/20, mm were obtained, using STIR, for transverse and longitudinal directions, respectively, with no time of flight information included.

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.

Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm.

PubMed

Wang, Xingmei; Liu, Shu; Liu, Zhipeng

2017-01-01

This paper proposes a combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm to detect underwater objects in sonar images. Specifically, for the first time, the problem of inappropriate filtering degree parameter which commonly occurs in non-local spatial information and seriously affects the denoising performance in sonar images, was solved with the method utilizing a novel filtering degree parameter. Then, a quantum-inspired shuffled frog leaping algorithm based on new search mechanism (QSFLA-NSM) is proposed to precisely and quickly detect sonar images. Each frog individual is directly encoded by real numbers, which can greatly simplify the evolution process of the quantum-inspired shuffled frog leaping algorithm (QSFLA). Meanwhile, a fitness function combining intra-class difference with inter-class difference is adopted to evaluate frog positions more accurately. On this basis, recurring to an analysis of the quantum-behaved particle swarm optimization (QPSO) and the shuffled frog leaping algorithm (SFLA), a new search mechanism is developed to improve the searching ability and detection accuracy. At the same time, the time complexity is further reduced. Finally, the results of comparative experiments using the original sonar images, the UCI data sets and the benchmark functions demonstrate the effectiveness and adaptability of the proposed method.

Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm

PubMed Central

Liu, Zhipeng

2017-01-01

This paper proposes a combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm to detect underwater objects in sonar images. Specifically, for the first time, the problem of inappropriate filtering degree parameter which commonly occurs in non-local spatial information and seriously affects the denoising performance in sonar images, was solved with the method utilizing a novel filtering degree parameter. Then, a quantum-inspired shuffled frog leaping algorithm based on new search mechanism (QSFLA-NSM) is proposed to precisely and quickly detect sonar images. Each frog individual is directly encoded by real numbers, which can greatly simplify the evolution process of the quantum-inspired shuffled frog leaping algorithm (QSFLA). Meanwhile, a fitness function combining intra-class difference with inter-class difference is adopted to evaluate frog positions more accurately. On this basis, recurring to an analysis of the quantum-behaved particle swarm optimization (QPSO) and the shuffled frog leaping algorithm (SFLA), a new search mechanism is developed to improve the searching ability and detection accuracy. At the same time, the time complexity is further reduced. Finally, the results of comparative experiments using the original sonar images, the UCI data sets and the benchmark functions demonstrate the effectiveness and adaptability of the proposed method. PMID:28542266

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

Modeling astronomical adaptive optics performance with temporally filtered Wiener reconstruction of slope data

NASA Astrophysics Data System (ADS)

Correia, Carlos M.; Bond, Charlotte Z.; Sauvage, Jean-François; Fusco, Thierry; Conan, Rodolphe; Wizinowich, Peter L.

2017-10-01

We build on a long-standing tradition in astronomical adaptive optics (AO) of specifying performance metrics and error budgets using linear systems modeling in the spatial-frequency domain. Our goal is to provide a comprehensive tool for the calculation of error budgets in terms of residual temporally filtered phase power spectral densities and variances. In addition, the fast simulation of AO-corrected point spread functions (PSFs) provided by this method can be used as inputs for simulations of science observations with next-generation instruments and telescopes, in particular to predict post-coronagraphic contrast improvements for planet finder systems. We extend the previous results and propose the synthesis of a distributed Kalman filter to mitigate both aniso-servo-lag and aliasing errors whilst minimizing the overall residual variance. We discuss applications to (i) analytic AO-corrected PSF modeling in the spatial-frequency domain, (ii) post-coronagraphic contrast enhancement, (iii) filter optimization for real-time wavefront reconstruction, and (iv) PSF reconstruction from system telemetry. Under perfect knowledge of wind velocities, we show that $\\sim$60 nm rms error reduction can be achieved with the distributed Kalman filter embodying anti- aliasing reconstructors on 10 m class high-order AO systems, leading to contrast improvement factors of up to three orders of magnitude at few ${\\lambda}/D$ separations ($\\sim1-5{\\lambda}/D$) for a 0 magnitude star and reaching close to one order of magnitude for a 12 magnitude star.

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 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.

Generalized assorted pixel camera: postcapture control of resolution, dynamic range, and spectrum.

PubMed

Yasuma, Fumihito; Mitsunaga, Tomoo; Iso, Daisuke; Nayar, Shree K

2010-09-01

We propose the concept of a generalized assorted pixel (GAP) camera, which enables the user to capture a single image of a scene and, after the fact, control the tradeoff between spatial resolution, dynamic range and spectral detail. The GAP camera uses a complex array (or mosaic) of color filters. A major problem with using such an array is that the captured image is severely under-sampled for at least some of the filter types. This leads to reconstructed images with strong aliasing. We make four contributions in this paper: 1) we present a comprehensive optimization method to arrive at the spatial and spectral layout of the color filter array of a GAP camera. 2) We develop a novel algorithm for reconstructing the under-sampled channels of the image while minimizing aliasing artifacts. 3) We demonstrate how the user can capture a single image and then control the tradeoff of spatial resolution to generate a variety of images, including monochrome, high dynamic range (HDR) monochrome, RGB, HDR RGB, and multispectral images. 4) Finally, the performance of our GAP camera has been verified using extensive simulations that use multispectral images of real world scenes. A large database of these multispectral images has been made available at http://www1.cs.columbia.edu/CAVE/projects/gap_camera/ for use by the research community.

Autofocus system and autofocus method for focusing on a surface

DOEpatents

O'Neill, Mary Morabito

2017-05-23

An autofocus system includes an imaging device, a lens system and a focus control actuator that is configured to change a focus position of the imaging device in relation to a stage. The electronic control unit is configured to control the focus control actuator to a plurality of predetermined focus positions, and activate the imaging device to obtain an image at predetermined positions and then apply a spatial filter to the obtained images. This generates a filtered image for the obtained images. The control unit determines a focus score for the filtered images such that the focus score corresponds to a degree of focus in the obtained images. The control unit identifies a best focus position by comparing the focus score of the filtered images, and controls the focus control actuator to the best focus position corresponding to the highest focus score.

Dynamic spatial filtering using a digital micromirror device for high-speed optical diffraction tomography.

PubMed

Jin, Di; Zhou, Renjie; Yaqoob, Zahid; So, Peter T C

2018-01-08

Optical diffraction tomography (ODT) is an emerging microscopy technique for three-dimensional (3D) refractive index (RI) mapping of transparent specimens. Recently, the digital micromirror device (DMD) based scheme for angle-controlled plane wave illumination has been proposed to improve the imaging speed and stability of ODT. However, undesired diffraction noise always exists in the reported DMD-based illumination scheme, which leads to a limited contrast ratio of the measurement fringe and hence inaccurate RI mapping. Here we present a novel spatial filtering method, based on a second DMD, to dynamically remove the diffraction noise. The reported results illustrate significantly enhanced image quality of the obtained interferograms and the subsequently derived phase maps. And moreover, with this method, we demonstrate mapping of 3D RI distribution of polystyrene beads as well as biological cells with high accuracy. Importantly, with the proper hardware configuration, our method does not compromise the 3D imaging speed advantage promised by the DMD-based illumination scheme. Specifically, we have been able to successfully obtain interferograms at over 1 kHz speed, which is critical for potential high-throughput label-free 3D image cytometry applications.

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.

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.

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.

Spatial and Temporal Variation of Land Surface Temperature in Fujian Province from 2001 TO 2015

NASA Astrophysics Data System (ADS)

Li, Y.; Wang, X.; Ding, Z.

2018-04-01

Land surface temperature (LST) is an essential parameter in the physics of land surface processes. The spatiotemporal variations of LST on the Fujian province were studied using AQUA Moderate Resolution Imaging Spectroradiometer LST data. Considering the data gaps in remotely sensed LST products caused by cloud contamination, the Savitzky-Golay (S-G) filter method was used to eliminate the influence of cloud cover and to describe the periodical signals of LST. Observed air temperature data from 27 weather stations were employed to evaluate the fitting performance of the S-G filter method. Results indicate that S-G can effectively fit the LST time series and remove the influence of cloud cover. Based on the S-G-derived result, Spatial and temporal Variations of LST in Fujian province from 2001 to 2015 are analysed through slope analysis. The results show that: 1) the spatial distribution of annual mean LST generally exhibits consistency with altitude in the study area and the average of LST was much higher in the east than in the west. 2) The annual mean temperature of LST declines slightly among 15 years in Fujian. 3) Slope analysis reflects the spatial distribution characteristics of LST changing trend in Fujian.Improvement areas of LST are mainly concentrated in the urban areas of Fujian, especially in the eastern urban areas. Apparent descent areas are mainly distributed in the area of Zhangzhou and eastern mountain area.

Spatial Frequency Requirements and Gaze Strategy in Visual-Only and Audiovisual Speech Perception

ERIC Educational Resources Information Center

Wilson, Amanda H.; Alsius, Agnès; Parè, Martin; Munhall, Kevin G.

2016-01-01

Purpose: The aim of this article is to examine the effects of visual image degradation on performance and gaze behavior in audiovisual and visual-only speech perception tasks. Method: We presented vowel-consonant-vowel utterances visually filtered at a range of frequencies in visual-only, audiovisual congruent, and audiovisual incongruent…

Landsat multispectral sharpening using a sensor system model and panchromatic image

USGS Publications Warehouse

Lemeshewsky, G.P.; ,

2003-01-01

The thematic mapper (TM) sensor aboard Landsats 4, 5 and enhanced TM plus (ETM+) on Landsat 7 collect imagery at 30-m sample distance in six spectral bands. New with ETM+ is a 15-m panchromatic (P) band. With image sharpening techniques, this higher resolution P data, or as an alternative, the 10-m (or 5-m) P data of the SPOT satellite, can increase the spatial resolution of the multispectral (MS) data. Sharpening requires that the lower resolution MS image be coregistered and resampled to the P data before high spatial frequency information is transferred to the MS data. For visual interpretation and machine classification tasks, it is important that the sharpened data preserve the spectral characteristics of the original low resolution data. A technique was developed for sharpening (in this case, 3:1 spatial resolution enhancement) visible spectral band data, based on a model of the sensor system point spread function (PSF) in order to maintain spectral fidelity. It combines high-pass (HP) filter sharpening methods with iterative image restoration to reduce degradations caused by sensor-system-induced blurring and resembling. Also there is a spectral fidelity requirement: sharpened MS when filtered by the modeled degradations should reproduce the low resolution source MS. Quantitative evaluation of sharpening performance was made by using simulated low resolution data generated from digital color-IR aerial photography. In comparison to the HP-filter-based sharpening method, results for the technique in this paper with simulated data show improved spectral fidelity. Preliminary results with TM 30-m visible band data sharpened with simulated 10-m panchromatic data are promising but require further study.

An improved non-uniformity correction algorithm and its GPU parallel implementation

NASA Astrophysics Data System (ADS)

Cheng, Kuanhong; Zhou, Huixin; Qin, Hanlin; Zhao, Dong; Qian, Kun; Rong, Shenghui

2018-05-01

The performance of SLP-THP based non-uniformity correction algorithm is seriously affected by the result of SLP filter, which always leads to image blurring and ghosting artifacts. To address this problem, an improved SLP-THP based non-uniformity correction method with curvature constraint was proposed. Here we put forward a new way to estimate spatial low frequency component. First, the details and contours of input image were obtained respectively by minimizing local Gaussian curvature and mean curvature of image surface. Then, the guided filter was utilized to combine these two parts together to get the estimate of spatial low frequency component. Finally, we brought this SLP component into SLP-THP method to achieve non-uniformity correction. The performance of proposed algorithm was verified by several real and simulated infrared image sequences. The experimental results indicated that the proposed algorithm can reduce the non-uniformity without detail losing. After that, a GPU based parallel implementation that runs 150 times faster than CPU was presented, which showed the proposed algorithm has great potential for real time application.

Speckle-based three-dimensional velocity measurement using spatial filtering velocimetry.

PubMed

Iversen, Theis F Q; Jakobsen, Michael L; Hanson, Steen G

2011-04-10

We present an optical method for measuring the real-time three-dimensional (3D) translational velocity of a diffusely scattering rigid object observed through an imaging system. The method is based on a combination of the motion of random speckle patterns and regular fringe patterns. The speckle pattern is formed in the observation plane of the imaging system due to reflection from an area of the object illuminated by a coherent light source. The speckle pattern translates in response to in-plane translation of the object, and the presence of an angular offset reference wave coinciding with the speckle pattern in the observation plane gives rise to interference, resulting in a fringe pattern that translates in response to the out-of-plane translation of the object. Numerical calculations are performed to evaluate the dynamic properties of the intensity distribution and the response of realistic spatial filters designed to measure the three components of the object's translational velocity. Furthermore, experimental data are presented that demonstrate full 3D velocity measurement. © 2011 Optical Society of America

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.

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.

State updating of a distributed hydrological model with Ensemble Kalman Filtering: Effects of updating frequency and observation network density on forecast accuracy

NASA Astrophysics Data System (ADS)

Rakovec, O.; Weerts, A.; Hazenberg, P.; Torfs, P.; Uijlenhoet, R.

2012-12-01

This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model (Rakovec et al., 2012a). The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property). Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a relatively quickly responding catchment in the Belgian Ardennes. The uncertain precipitation model forcings were obtained using a time-dependent multivariate spatial conditional simulation method (Rakovec et al., 2012b), which is further made conditional on preceding simulations. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty. Rakovec, O., Weerts, A. H., Hazenberg, P., Torfs, P. J. J. F., and Uijlenhoet, R.: State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy, Hydrol. Earth Syst. Sci. Discuss., 9, 3961-3999, doi:10.5194/hessd-9-3961-2012, 2012a. Rakovec, O., Hazenberg, P., Torfs, P. J. J. F., Weerts, A. H., and Uijlenhoet, R.: Generating spatial precipitation ensembles: impact of temporal correlation structure, Hydrol. Earth Syst. Sci. Discuss., 9, 3087-3127, doi:10.5194/hessd-9-3087-2012, 2012b.

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.

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.

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

Filter forensics: microbiota recovery from residential HVAC filters.

PubMed

Maestre, Juan P; Jennings, Wiley; Wylie, Dennis; Horner, Sharon D; Siegel, Jeffrey; Kinney, Kerry A

2018-01-30

Establishing reliable methods for assessing the microbiome within the built environment is critical for understanding the impact of biological exposures on human health. High-throughput DNA sequencing of dust samples provides valuable insights into the microbiome present in human-occupied spaces. However, the effect that different sampling methods have on the microbial community recovered from dust samples is not well understood across sample types. Heating, ventilation, and air conditioning (HVAC) filters hold promise as long-term, spatially integrated, high volume samplers to characterize the airborne microbiome in homes and other climate-controlled spaces. In this study, the effect that dust recovery method (i.e., cut and elution, swabbing, or vacuuming) has on the microbial community structure, membership, and repeatability inferred by Illumina sequencing was evaluated. The results indicate that vacuum samples captured higher quantities of total, bacterial, and fungal DNA than swab or cut samples. Repeated swab and vacuum samples collected from the same filter were less variable than cut samples with respect to both quantitative DNA recovery and bacterial community structure. Vacuum samples captured substantially greater bacterial diversity than the other methods, whereas fungal diversity was similar across all three methods. Vacuum and swab samples of HVAC filter dust were repeatable and generally superior to cut samples. Nevertheless, the contribution of environmental and human sources to the bacterial and fungal communities recovered via each sampling method was generally consistent across the methods investigated. Dust recovery methodologies have been shown to affect the recovery, repeatability, structure, and membership of microbial communities recovered from dust samples in the built environment. The results of this study are directly applicable to indoor microbiota studies utilizing the filter forensics approach. More broadly, this study provides a better understanding of the microbial community variability attributable to sampling methodology and helps inform interpretation of data collected from other types of dust samples collected from indoor environments.

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

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.

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

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.

Application of a common spatial pattern-based algorithm for an fNIRS-based motor imagery brain-computer interface.

PubMed

Zhang, Shen; Zheng, Yanchun; Wang, Daifa; Wang, Ling; Ma, Jianai; Zhang, Jing; Xu, Weihao; Li, Deyu; Zhang, Dan

2017-08-10

Motor imagery is one of the most investigated paradigms in the field of brain-computer interfaces (BCIs). The present study explored the feasibility of applying a common spatial pattern (CSP)-based algorithm for a functional near-infrared spectroscopy (fNIRS)-based motor imagery BCI. Ten participants performed kinesthetic imagery of their left- and right-hand movements while 20-channel fNIRS signals were recorded over the motor cortex. The CSP method was implemented to obtain the spatial filters specific for both imagery tasks. The mean, slope, and variance of the CSP filtered signals were taken as features for BCI classification. Results showed that the CSP-based algorithm outperformed two representative channel-wise methods for classifying the two imagery statuses using either data from all channels or averaged data from imagery responsive channels only (oxygenated hemoglobin: CSP-based: 75.3±13.1%; all-channel: 52.3±5.3%; averaged: 64.8±13.2%; deoxygenated hemoglobin: CSP-based: 72.3±13.0%; all-channel: 48.8±8.2%; averaged: 63.3±13.3%). Furthermore, the effectiveness of the CSP method was also observed for the motor execution data to a lesser extent. A partial correlation analysis revealed significant independent contributions from all three types of features, including the often-ignored variance feature. To our knowledge, this is the first study demonstrating the effectiveness of the CSP method for fNIRS-based motor imagery BCIs. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial-frequency dependent binocular imbalance in amblyopia

PubMed Central

Kwon, MiYoung; Wiecek, Emily; Dakin, Steven C.; Bex, Peter J.

2015-01-01

While amblyopia involves both binocular imbalance and deficits in processing high spatial frequency information, little is known about the spatial-frequency dependence of binocular imbalance. Here we examined binocular imbalance as a function of spatial frequency in amblyopia using a novel computer-based method. Binocular imbalance at four spatial frequencies was measured with a novel dichoptic letter chart in individuals with amblyopia, or normal vision. Our dichoptic letter chart was composed of band-pass filtered letters arranged in a layout similar to the ETDRS acuity chart. A different chart was presented to each eye of the observer via stereo-shutter glasses. The relative contrast of the corresponding letter in each eye was adjusted by a computer staircase to determine a binocular Balance Point at which the observer reports the letter presented to either eye with equal probability. Amblyopes showed pronounced binocular imbalance across all spatial frequencies, with greater imbalance at high compared to low spatial frequencies (an average increase of 19%, p < 0.01). Good test-retest reliability of the method was demonstrated by the Bland-Altman plot. Our findings suggest that spatial-frequency dependent binocular imbalance may be useful for diagnosing amblyopia and as an outcome measure for recovery of binocular vision following therapy. PMID:26603125

Spatial-frequency dependent binocular imbalance in amblyopia.

PubMed

Kwon, MiYoung; Wiecek, Emily; Dakin, Steven C; Bex, Peter J

2015-11-25

While amblyopia involves both binocular imbalance and deficits in processing high spatial frequency information, little is known about the spatial-frequency dependence of binocular imbalance. Here we examined binocular imbalance as a function of spatial frequency in amblyopia using a novel computer-based method. Binocular imbalance at four spatial frequencies was measured with a novel dichoptic letter chart in individuals with amblyopia, or normal vision. Our dichoptic letter chart was composed of band-pass filtered letters arranged in a layout similar to the ETDRS acuity chart. A different chart was presented to each eye of the observer via stereo-shutter glasses. The relative contrast of the corresponding letter in each eye was adjusted by a computer staircase to determine a binocular Balance Point at which the observer reports the letter presented to either eye with equal probability. Amblyopes showed pronounced binocular imbalance across all spatial frequencies, with greater imbalance at high compared to low spatial frequencies (an average increase of 19%, p < 0.01). Good test-retest reliability of the method was demonstrated by the Bland-Altman plot. Our findings suggest that spatial-frequency dependent binocular imbalance may be useful for diagnosing amblyopia and as an outcome measure for recovery of binocular vision following therapy.

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.

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.

Multiple-Parameter Estimation Method Based on Spatio-Temporal 2-D Processing for Bistatic MIMO Radar.

PubMed

Yang, Shouguo; Li, Yong; Zhang, Kunhui; Tang, Weiping

2015-12-14

A novel spatio-temporal 2-dimensional (2-D) processing method that can jointly estimate the transmitting-receiving azimuth and Doppler frequency for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise and an unknown number of targets is proposed. In the temporal domain, the cross-correlation of the matched filters' outputs for different time-delay sampling is used to eliminate the spatial colored noise. In the spatial domain, the proposed method uses a diagonal loading method and subspace theory to estimate the direction of departure (DOD) and direction of arrival (DOA), and the Doppler frequency can then be accurately estimated through the estimation of the DOD and DOA. By skipping target number estimation and the eigenvalue decomposition (EVD) of the data covariance matrix estimation and only requiring a one-dimensional search, the proposed method achieves low computational complexity. Furthermore, the proposed method is suitable for bistatic MIMO radar with an arbitrary transmitted and received geometrical configuration. The correction and efficiency of the proposed method are verified by computer simulation results.

A robust spatial filtering technique for multisource localization and geoacoustic inversion.

PubMed

Stotts, S A

2005-07-01

Geoacoustic inversion and source localization using beamformed data from a ship of opportunity has been demonstrated with a bottom-mounted array. An alternative approach, which lies within a class referred to as spatial filtering, transforms element level data into beam data, applies a bearing filter, and transforms back to element level data prior to performing inversions. Automation of this filtering approach is facilitated for broadband applications by restricting the inverse transform to the degrees of freedom of the array, i.e., the effective number of elements, for frequencies near or below the design frequency. A procedure is described for nonuniformly spaced elements that guarantees filter stability well above the design frequency. Monitoring energy conservation with respect to filter output confirms filter stability. Filter performance with both uniformly spaced and nonuniformly spaced array elements is discussed. Vertical (range and depth) and horizontal (range and bearing) ambiguity surfaces are constructed to examine filter performance. Examples that demonstrate this filtering technique with both synthetic data and real data are presented along with comparisons to inversion results using beamformed data. Examinations of cost functions calculated within a simulated annealing algorithm reveal the efficacy of the approach.

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.

Spatially resolved speckle-correlometry of sol-gel transition

NASA Astrophysics Data System (ADS)

Isaeva, A. A.; Isaeva, E. A.; Pantyukov, A. V.; Zimnyakov, D. A.

2018-04-01

Sol-gel transition was studied using the speckle correlometry method with a localized light source and spatial filtering of backscattered radiation. Water solutions of technical or food gelatin with added TiO2 nanoparticles were used as studied objects. Structural transformation of "sol-gel" system was studied at various temperatures from 25°C to 50°C using analysis of the correlation and structure functions of speckle intensity fluctuations. The characteristic temperatures of "sol - gel" transition were evaluated for studied systems. Obtained results can be used for various applications in biomedicine and food industry.

Small Infrared Target Detection by Region-Adaptive Clutter Rejection for Sea-Based Infrared Search and Track

PubMed Central

Kim, Sungho; Lee, Joohyoung

2014-01-01

This paper presents a region-adaptive clutter rejection method for small target detection in sea-based infrared search and track. In the real world, clutter normally generates many false detections that impede the deployment of such detection systems. Incoming targets (missiles, boats, etc.) can be located in the sky, horizon and sea regions, which have different types of clutters, such as clouds, a horizontal line and sea-glint. The characteristics of regional clutter were analyzed after the geometrical analysis-based region segmentation. The false detections caused by cloud clutter were removed by the spatial attribute-based classification. Those by the horizontal line were removed using the heterogeneous background removal filter. False alarms by sun-glint were rejected using the temporal consistency filter, which is the most difficult part. The experimental results of the various cluttered background sequences show that the proposed region adaptive clutter rejection method produces fewer false alarms than that of the mean subtraction filter (MSF) with an acceptable degradation detection rate. PMID:25054633

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)

Kalman filter parameter estimation for a nonlinear diffusion model of epithelial cell migration using stochastic collocation and the Karhunen-Loeve expansion.

PubMed

Barber, Jared; Tanase, Roxana; Yotov, Ivan

2016-06-01

Several Kalman filter algorithms are presented for data assimilation and parameter estimation for a nonlinear diffusion model of epithelial cell migration. These include the ensemble Kalman filter with Monte Carlo sampling and a stochastic collocation (SC) Kalman filter with structured sampling. Further, two types of noise are considered -uncorrelated noise resulting in one stochastic dimension for each element of the spatial grid and correlated noise parameterized by the Karhunen-Loeve (KL) expansion resulting in one stochastic dimension for each KL term. The efficiency and accuracy of the four methods are investigated for two cases with synthetic data with and without noise, as well as data from a laboratory experiment. While it is observed that all algorithms perform reasonably well in matching the target solution and estimating the diffusion coefficient and the growth rate, it is illustrated that the algorithms that employ SC and KL expansion are computationally more efficient, as they require fewer ensemble members for comparable accuracy. In the case of SC methods, this is due to improved approximation in stochastic space compared to Monte Carlo sampling. In the case of KL methods, the parameterization of the noise results in a stochastic space of smaller dimension. The most efficient method is the one combining SC and KL expansion. Copyright © 2016 Elsevier Inc. All rights reserved.

An enhanced structure tensor method for sea ice ridge detection from GF-3 SAR imagery

NASA Astrophysics Data System (ADS)

Zhu, T.; Li, F.; Zhang, Y.; Zhang, S.; Spreen, G.; Dierking, W.; Heygster, G.

2017-12-01

In SAR imagery, ridges or leads are shown as the curvilinear features. The proposed ridge detection method is facilitated by their curvilinear shapes. The bright curvilinear features are recognized as the ridges while the dark curvilinear features are classified as the leads. In dual-polarization HH or HV channel of C-band SAR imagery, the bright curvilinear feature may be false alarm because the frost flowers of young leads may show as bright pixels associated with changes in the surface salinity under calm surface conditions. Wind roughened leads also trigger the backscatter increasing that can be misclassified as ridges [1]. Thus the width limitation is considered in this proposed structure tensor method [2], since only shape feature based method is not enough for detecting ridges. The ridge detection algorithm is based on the hypothesis that the bright pixels are ridges with curvilinear shapes and the ridge width is less 30 meters. Benefited from GF-3 with high spatial resolution of 3 meters, we provide an enhanced structure tensor method for detecting the significant ridge. The preprocessing procedures including the calibration and incidence angle normalization are also investigated. The bright pixels will have strong response to the bandpass filtering. The ridge training samples are delineated from the SAR imagery in the Log-Gabor filters to construct structure tensor. From the tensor, the dominant orientation of the pixel representing the ridge is determined by the dominant eigenvector. For the post-processing of structure tensor, the elongated kernel is desired to enhance the ridge curvilinear shape. Since ridge presents along a certain direction, the ratio of the dominant eigenvector will be used to measure the intensity of local anisotropy. The convolution filter has been utilized in the constructed structure tensor is used to model spatial contextual information. Ridge detection results from GF-3 show the proposed method performs better compared to the direct threshold method.

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.

Multi-frame linear regressive filter for the measurement of infrared pixel spatial response and MTF from sparse data.

PubMed

Huard, Edouard; Derelle, Sophie; Jaeck, Julien; Nghiem, Jean; Haïdar, Riad; Primot, Jérôme

2018-03-05

A challenging point in the prediction of the image quality of infrared imaging systems is the evaluation of the detector modulation transfer function (MTF). In this paper, we present a linear method to get a 2D continuous MTF from sparse spectral data. Within the method, an object with a predictable sparse spatial spectrum is imaged by the focal plane array. The sparse data is then treated to return the 2D continuous MTF with the hypothesis that all the pixels have an identical spatial response. The linearity of the treatment is a key point to estimate directly the error bars of the resulting detector MTF. The test bench will be presented along with measurement tests on a 25 μm pitch InGaAs detector.

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.

Portable modular detection system

DOEpatents

Brennan, James S [Rodeo, CA; Singh, Anup [Danville, CA; Throckmorton, Daniel J [Tracy, CA; Stamps, James F [Livermore, CA

2009-10-13

Disclosed herein are portable and modular detection devices and systems for detecting electromagnetic radiation, such as fluorescence, from an analyte which comprises at least one optical element removably attached to at least one alignment rail. Also disclosed are modular detection devices and systems having an integrated lock-in amplifier and spatial filter and assay methods using the portable and modular detection devices.

Fixed-pattern noise correction method based on improved moment matching for a TDI CMOS image sensor.

PubMed

Xu, Jiangtao; Nie, Huafeng; Nie, Kaiming; Jin, Weimin

2017-09-01

In this paper, an improved moment matching method based on a spatial correlation filter (SCF) and bilateral filter (BF) is proposed to correct the fixed-pattern noise (FPN) of a time-delay-integration CMOS image sensor (TDI-CIS). First, the values of row FPN (RFPN) and column FPN (CFPN) are estimated and added to the original image through SCF and BF, respectively. Then the filtered image will be processed by an improved moment matching method with a moving window. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination, the standard deviation of row mean vector (SDRMV) decreases from 5.6761 LSB to 0.1948 LSB, while the standard deviation of the column mean vector (SDCMV) decreases from 15.2005 LSB to 13.1949LSB. In addition, for different images captured by different TDI-CISs, the average decrease of SDRMV and SDCMV is 5.4922/2.0357 LSB, respectively. Comparative experimental results indicate that the proposed method can effectively correct the FPNs of different TDI-CISs while maintaining image details without any auxiliary equipment.

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.

Median Filtering Methods for Non-volcanic Tremor Detection

NASA Astrophysics Data System (ADS)

Damiao, L. G.; Nadeau, R. M.; Dreger, D. S.; Luna, B.; Zhang, H.

2016-12-01

Various properties of median filtering over time and space are used to address challenges posed by the Non-volcanic tremor detection problem. As part of a "Big-Data" effort to characterize the spatial and temporal distribution of ambient tremor throughout the Northern San Andreas Fault system, continuous seismic data from multiple seismic networks with contrasting operational characteristics and distributed over a variety of regions are being used. Automated median filtering methods that are flexible enough to work consistently with these data are required. Tremor is characterized by a low-amplitude, long-duration signal-train whose shape is coherent at multiple stations distributed over a large area. There are no consistent phase arrivals or mechanisms in a given tremor's signal and even the durations and shapes among different tremors vary considerably. A myriad of masquerading noise, anthropogenic and natural-event signals must also be discriminated in order to obtain accurate tremor detections. We present here results of the median methods applied to data from four regions of the San Andreas Fault system in northern California (Geysers Geothermal Field, Napa, Bitterwater and Parkfield) to illustrate the ability of the methods to detect tremor under diverse conditions.

Fast Shear Compounding Using Robust Two-dimensional Shear Wave Speed Calculation and Multi-directional Filtering

PubMed Central

Song, Pengfei; Manduca, Armando; Zhao, Heng; Urban, Matthew W.; Greenleaf, James F.; Chen, Shigao

2014-01-01

A fast shear compounding method was developed in this study using only one shear wave push-detect cycle, such that the shear wave imaging frame rate is preserved and motion artifacts are minimized. The proposed method is composed of the following steps: 1. applying a comb-push to produce multiple differently angled shear waves at different spatial locations simultaneously; 2. decomposing the complex shear wave field into individual shear wave fields with differently oriented shear waves using a multi-directional filter; 3. using a robust two-dimensional (2D) shear wave speed calculation to reconstruct 2D shear elasticity maps from each filter direction; 4. compounding these 2D maps from different directions into a final map. An inclusion phantom study showed that the fast shear compounding method could achieve comparable performance to conventional shear compounding without sacrificing the imaging frame rate. A multi-inclusion phantom experiment showed that the fast shear compounding method could provide a full field-of-view (FOV), 2D, and compounded shear elasticity map with three types of inclusions clearly resolved and stiffness measurements showing excellent agreement to the nominal values. PMID:24613636

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.

The Riesz transform and simultaneous representations of phase, energy and orientation in spatial vision.

PubMed

Langley, Keith; Anderson, Stephen J

2010-08-06

To represent the local orientation and energy of a 1-D image signal, many models of early visual processing employ bandpass quadrature filters, formed by combining the original signal with its Hilbert transform. However, representations capable of estimating an image signal's 2-D phase have been largely ignored. Here, we consider 2-D phase representations using a method based upon the Riesz transform. For spatial images there exist two Riesz transformed signals and one original signal from which orientation, phase and energy may be represented as a vector in 3-D signal space. We show that these image properties may be represented by a Singular Value Decomposition (SVD) of the higher-order derivatives of the original and the Riesz transformed signals. We further show that the expected responses of even and odd symmetric filters from the Riesz transform may be represented by a single signal autocorrelation function, which is beneficial in simplifying Bayesian computations for spatial orientation. Importantly, the Riesz transform allows one to weight linearly across orientation using both symmetric and asymmetric filters to account for some perceptual phase distortions observed in image signals - notably one's perception of edge structure within plaid patterns whose component gratings are either equal or unequal in contrast. Finally, exploiting the benefits that arise from the Riesz definition of local energy as a scalar quantity, we demonstrate the utility of Riesz signal representations in estimating the spatial orientation of second-order image signals. We conclude that the Riesz transform may be employed as a general tool for 2-D visual pattern recognition by its virtue of representing phase, orientation and energy as orthogonal signal quantities.

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.

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.

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.

Fluorescence detection system for microfluidic droplets

NASA Astrophysics Data System (ADS)

Chen, Binyu; Han, Xiaoming; Su, Zhen; Liu, Quanjun

2018-05-01

In microfluidic detection technology, because of the universality of optical methods in laboratory, optical detection is an attractive solution for microfluidic chip laboratory equipment. In addition, the equipment with high stability and low cost can be realized by integrating appropriate optical detection technology on the chip. This paper reports a detection system for microfluidic droplets. Photomultiplier tubes (PMT) is used as a detection device to improve the sensitivity of detection. This system improves the signal to noise ratio by software filtering and spatial filter. The fluorescence intensity is proportional to the concentration of the fluorescence and intensity of the laser. The fluorescence micro droplets of different concentrations can be distinguished by this system.

Background derivation and image flattening: getimages

NASA Astrophysics Data System (ADS)

Men'shchikov, A.

2017-11-01

Modern high-resolution images obtained with space observatories display extremely strong intensity variations across images on all spatial scales. Source extraction in such images with methods based on global thresholding may bring unacceptably large numbers of spurious sources in bright areas while failing to detect sources in low-background or low-noise areas. It would be highly beneficial to subtract background and equalize the levels of small-scale fluctuations in the images before extracting sources or filaments. This paper describes getimages, a new method of background derivation and image flattening. It is based on median filtering with sliding windows that correspond to a range of spatial scales from the observational beam size up to a maximum structure width Xλ. The latter is a single free parameter of getimages that can be evaluated manually from the observed image ℐλ. The median filtering algorithm provides a background image \\tilde{Bλ} for structures of all widths below Xλ. The same median filtering procedure applied to an image of standard deviations 𝓓λ derived from a background-subtracted image \\tilde{Sλ} results in a flattening image \\tilde{Fλ}. Finally, a flattened detection image I{λD} = \\tilde{Sλ}/\\tilde{Fλ} is computed, whose standard deviations are uniform outside sources and filaments. Detecting sources in such greatly simplified images results in much cleaner extractions that are more complete and reliable. As a bonus, getimages reduces various observational and map-making artifacts and equalizes noise levels between independent tiles of mosaicked images.

Adaptive smoothing based on Gaussian processes regression increases the sensitivity and specificity of fMRI data.

PubMed

Strappini, Francesca; Gilboa, Elad; Pitzalis, Sabrina; Kay, Kendrick; McAvoy, Mark; Nehorai, Arye; Snyder, Abraham Z

2017-03-01

Temporal and spatial filtering of fMRI data is often used to improve statistical power. However, conventional methods, such as smoothing with fixed-width Gaussian filters, remove fine-scale structure in the data, necessitating a tradeoff between sensitivity and specificity. Specifically, smoothing may increase sensitivity (reduce noise and increase statistical power) but at the cost loss of specificity in that fine-scale structure in neural activity patterns is lost. Here, we propose an alternative smoothing method based on Gaussian processes (GP) regression for single subjects fMRI experiments. This method adapts the level of smoothing on a voxel by voxel basis according to the characteristics of the local neural activity patterns. GP-based fMRI analysis has been heretofore impractical owing to computational demands. Here, we demonstrate a new implementation of GP that makes it possible to handle the massive data dimensionality of the typical fMRI experiment. We demonstrate how GP can be used as a drop-in replacement to conventional preprocessing steps for temporal and spatial smoothing in a standard fMRI pipeline. We present simulated and experimental results that show the increased sensitivity and specificity compared to conventional smoothing strategies. Hum Brain Mapp 38:1438-1459, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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.

A Proposed Imaging System to Spatially and Temporally Monitor Unburned Hydrocarbons in Jet Engine Exhaust

NASA Astrophysics Data System (ADS)

Berkson, Emily E.

The local air quality surrounding airports is significantly impacted by ground-based airplane operations, such as landing, taxiing, idling, and takeoff. In recent years, studies performed across the country revealed that people living near major airports suffer from increased cancer risks and higher likelihoods of developing respiratory issues. Jet engine emissions have been monitored extensively by direct probing of the exhaust, but there are currently no inexpensive, portable, and unobtrusive methods with which to study exhaust plume dynamics. This study assesses the feasibility of designing a multispectral imaging system to track the spatial-temporal nature of a jet engine plume. Ideally, the imaging system will be both inexpensive and portable enough to be deployed at any airport. We begin by characterizing the phenomenology of jet engine emissions during ground operations and select unburned hydrocarbons (UHCs) as the basis for our plume tracking. A proposed LWIR imaging system layout and radiometric governing equation is developed to predict the camera's sensor-reaching radiance. We use two methods, the Ideal Gas Law and the Gaussian Plume Equation, to three-dimensionally model the UHC concentration within the plume, which, in turn, is used to predict the plume transmission as a function of downwind distance. Radiometric models are used to predict the sensor-reaching radiance of the camera, and two filter combinations are selected to maximize the plume detectability. Each filter combination uses one filter to monitor the background radiance and one filter to trace the plume radiance. They are located at 9.001/9.333 [mum] and 9.12/12.212 [mum]. The plume tracing filters are used to assess plume detectability, and we find that that a camera with an NEDeltaT of 0.05 [K] will be able to detect the plume up to 120 seconds after the engine has passed. We conclude by predicting what filter difference the camera will observe temporally, as plumes are continuously generated and dissipated. The effect of individual UHCs on total plume transmission was also examined, and a selection of narrowband filters for monitoring specific UHCs is proposed for future work. Results will help to prototype a system for deployment at the Greater Rochester International Airport. This work will make airport emissions inventories more accessible and allow for improved governing of emission caps and pollution bylaws.

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.

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.

High-Resolution Infrared Filter System for Solar Spectroscopy and Polarimetry

NASA Astrophysics Data System (ADS)

Cao, W.; Ma, J.; Wang, J.; Goode, P. R.; Wang, H.; Denker, C.

2003-05-01

We report on the design of an imaging filter system working at the near infrared (NIR) of 1.56 μ m to obtain monochromatic images and to probe weak magnetic fields in different layers of the deep photosphere with high temporal resolution and spatial resolution at Big Bear Solar Observatory (BBSO). This filter system consists of an interference filter, a birefringent filter, and a Fabry-Pérot etalon. As the narrowest filter system, the infrared Fabry-Pérot plays an important role in achieving narrow band transmission and high throughput, maintaining wavelength tuning ability, and assuring stability and reliability. In this poster, we outline a set of methods for the evaluation and calibration of the near infrared Fabry-Pérot etalon. Two-dimensional characteristic maps of the near infrared Fabry-Pérot etalon, including full-width-at-half-maximum (FWHM), effective finesse, peak transmission, along with free spectral range, flatness, roughness, stability and repeatability were obtained with lab equipments. Finally, by utilizing these results, a detailed analysis of the filter performance for the Fe I 1.5648 μ m and Fe I 1.5652 μ m Zeeman sensitive lines is presented. These results will benefit the design of NIR spectro-polarimeter of Advanced Technology Solar Telescope (ATST).

Infrared and visible image fusion with spectral graph wavelet transform.

PubMed

Yan, Xiang; Qin, Hanlin; Li, Jia; Zhou, Huixin; Zong, Jing-guo

2015-09-01

Infrared and visible image fusion technique is a popular topic in image analysis because it can integrate complementary information and obtain reliable and accurate description of scenes. Multiscale transform theory as a signal representation method is widely used in image fusion. In this paper, a novel infrared and visible image fusion method is proposed based on spectral graph wavelet transform (SGWT) and bilateral filter. The main novelty of this study is that SGWT is used for image fusion. On the one hand, source images are decomposed by SGWT in its transform domain. The proposed approach not only effectively preserves the details of different source images, but also excellently represents the irregular areas of the source images. On the other hand, a novel weighted average method based on bilateral filter is proposed to fuse low- and high-frequency subbands by taking advantage of spatial consistency of natural images. Experimental results demonstrate that the proposed method outperforms seven recently proposed image fusion methods in terms of both visual effect and objective evaluation metrics.

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.

Nanophotonic Image Sensors.

PubMed

Chen, Qin; Hu, Xin; Wen, Long; Yu, Yan; Cumming, David R S

2016-09-01

The increasing miniaturization and resolution of image sensors bring challenges to conventional optical elements such as spectral filters and polarizers, the properties of which are determined mainly by the materials used, including dye polymers. Recent developments in spectral filtering and optical manipulating techniques based on nanophotonics have opened up the possibility of an alternative method to control light spectrally and spatially. By integrating these technologies into image sensors, it will become possible to achieve high compactness, improved process compatibility, robust stability and tunable functionality. In this Review, recent representative achievements on nanophotonic image sensors are presented and analyzed including image sensors with nanophotonic color filters and polarizers, metamaterial-based THz image sensors, filter-free nanowire image sensors and nanostructured-based multispectral image sensors. This novel combination of cutting edge photonics research and well-developed commercial products may not only lead to an important application of nanophotonics but also offer great potential for next generation image sensors beyond Moore's Law expectations. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Off-axis digital holographic camera for quantitative phase microscopy.

PubMed

Monemhaghdoust, Zahra; Montfort, Frédéric; Emery, Yves; Depeursinge, Christian; Moser, Christophe

2014-06-01

We propose and experimentally demonstrate a digital holographic camera which can be attached to the camera port of a conventional microscope for obtaining digital holograms in a self-reference configuration, under short coherence illumination and in a single shot. A thick holographic grating filters the beam containing the sample information in two dimensions through diffraction. The filtered beam creates the reference arm of the interferometer. The spatial filtering method, based on the high angular selectivity of the thick grating, reduces the alignment sensitivity to angular displacements compared with pinhole based Fourier filtering. The addition of a thin holographic grating alters the coherence plane tilt introduced by the thick grating so as to create high-visibility interference over the entire field of view. The acquired full-field off-axis holograms are processed to retrieve the amplitude and phase information of the sample. The system produces phase images of cheek cells qualitatively similar to phase images extracted with a standard commercial DHM.

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.

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.

Images and Spectral Performance of WFC3 Interference Filters

NASA Technical Reports Server (NTRS)

Quijada, Manuel A.; Boucarut, R.; Telfer, R.; Baggett, S.; Quijano, J. Kim; Allen, George; Arsenovic, Peter

2006-01-01

The Wide Field Camera 3 (WFC3) is a panchromatic imager that will be deployed in the Hubble Space Telescope (HST). The mission of the WFC3 is to enhance HST1s imaging capability in the ultraviolet, visible and near-infrared spectral regions. Together with a wavelength coverage spanning 2000A to 1.7 micron, the WFC3 high sensitivity, high spatial resolution, and large field-of-view provide the astronomer with an unprecedented set of tools for exploring all types of exciting astrophysical terrain and for addressing many key questions in astronomy today. The filter compliment, which includes broad, medium, and narrow band filters, naturally reflects the diversity of astronomical programs to be targeted with WFC3. The WFC3 holds 61 UVIS filters elements, 14 IR filters, and 3 dispersive elements. During ground testing, the majority of the UVIS filters were found to exhibit excellent performance consistent with or exceeding expectations; however, a subset of filters showed considerable ghost images; some with relative intensity as high as 10-15%. Replacement filters with band-defining coatings that substantially reduce these ghost images were designed and procured. A state-of-the-art characterization setup was developed to measured the intensity of ghost images, focal shift, wedge direction , transmitted uniformity and surface feature of filters that could effect uniform flat field images. We will report on this new filter characterization methods, as well as the spectral performance measurements of the in-band transmittance and blocking.

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.

Enhanced dual-frequency pattern scheme based on spatial-temporal fringes method

NASA Astrophysics Data System (ADS)

Wang, Minmin; Zhou, Canlin; Si, Shuchun; Lei, Zhenkun; Li, Xiaolei; Li, Hui; Li, YanJie

2018-07-01

One of the major challenges of employing a dual-frequency phase-shifting algorithm for phase retrieval is its sensitivity to noise. Yun et al proposed a dual-frequency method based on the Fourier transform profilometry, yet the low-frequency lobes are close to each other for accurate band-pass filtering. In the light of this problem, a novel dual-frequency pattern based on the spatial-temporal fringes (STF) method is developed in this paper. Three fringe patterns with two different frequencies are required. The low-frequency phase is obtained from two low-frequency fringe patterns by the STF method, so the signal lobes can be extracted accurately as they are far away from each other. The high-frequency phase is retrieved from another fringe pattern without the impact of the DC component. Simulations and experiments are conducted to demonstrate the excellent precision of the proposed method.

Scene Analysis: Non-Linear Spatial Filtering for Automatic Target Detection.

DTIC Science & Technology

1982-12-01

In this thesis, a method for two-dimensional pattern recognition was developed and tested. The method included a global search scheme for candidate...test global switch TYPEO Creating negative video file only.W 11=0 12=256 13=512 14=768 GO 70 2 1 TYPE" Creating negative and horizontally flipped video...purpose was to develop a base of image processing software for the AFIT Digital Signal Processing Laboratory NOVA- ECLIPSE minicomputer system, for

Performance comparisons on spatial lattice algorithm and direct matrix inverse method with application to adaptive arrays processing

NASA Technical Reports Server (NTRS)

An, S. H.; Yao, K.

1986-01-01

Lattice algorithm has been employed in numerous adaptive filtering applications such as speech analysis/synthesis, noise canceling, spectral analysis, and channel equalization. In this paper the application to adaptive-array processing is discussed. The advantages are fast convergence rate as well as computational accuracy independent of the noise and interference conditions. The results produced by this technique are compared to those obtained by the direct matrix inverse method.

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.

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.

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.

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.

New Methods of Entanglement with Spatial Modes of Light

DTIC Science & Technology

2014-02-01

Poincare beam by state nulling. ....................................... 15 Figure 13: Poincare patterns measured by imaging polarimetry ...perform imaging polarimetry . This entails taking six single photon images, pixel by pixel, after the passage through six different polarization filters...state nulling [21,22] and by imaging polarimetry [24]. Figure 12 shows the result of state nulling measurements in diagnosing the mode of a Poincare

VizieR Online Data Catalog: Spatial deconvolution code (Quintero Noda+, 2015)

NASA Astrophysics Data System (ADS)

Quintero Noda, C.; Asensio Ramos, A.; Orozco Suarez, D.; Ruiz Cobo, B.

2015-05-01

This deconvolution method follows the scheme presented in Ruiz Cobo & Asensio Ramos (2013A&A...549L...4R) The Stokes parameters are projected onto a few spectral eigenvectors and the ensuing maps of coefficients are deconvolved using a standard Lucy-Richardson algorithm. This introduces a stabilization because the PCA filtering reduces the amount of noise. (1 data file).

Crop Surveillance Demonstration Using a Near-Daily MODIS Derived Vegetation Index Time Series

NASA Technical Reports Server (NTRS)

McKellip, Rodney; Ryan, Robert E.; Blonski, Slawomir; Prados, Don

2005-01-01

Effective response to crop disease outbreaks requires rapid identification and diagnosis of an event. A near-daily vegetation index product, such as a Normalized Difference Vegetation Index (NDVI), at moderate spatial resolution may serve as a good method for monitoring quick-acting diseases. NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flown on the Terra and Aqua satellites has the temporal, spatial, and spectral properties to make it an excellent coarse-resolution data source for rapid, comprehensive surveillance of agricultural areas. A proof-of-concept wide area crop surveillance system using daily MODIS imagery was developed and tested on a set of San Joaquin cotton fields over a growing season. This area was chosen in part because excellent ground truth data were readily available. Preliminary results indicate that, at least in the southwestern part of the United States, near-daily NDVI products can be generated that show the natural variations in the crops as well as specific crop practices. Various filtering methods were evaluated and compared with standard MOD13 NDVI MODIS products. We observed that specific chemical applications that produce defoliation, which would have been missed using the standard 16-day product, were easily detectable with the filtered daily NDVI products.

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.

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.

Simultaneous reconstruction of 3D refractive index, temperature, and intensity distribution of combustion flame by double computed tomography technologies based on spatial phase-shifting method

NASA Astrophysics Data System (ADS)

Guo, Zhenyan; Song, Yang; Yuan, Qun; Wulan, Tuya; Chen, Lei

2017-06-01

In this paper, a transient multi-parameter three-dimensional (3D) reconstruction method is proposed to diagnose and visualize a combustion flow field. Emission and transmission tomography based on spatial phase-shifted technology are combined to reconstruct, simultaneously, the various physical parameter distributions of a propane flame. Two cameras triggered by the internal trigger mode capture the projection information of the emission and moiré tomography, respectively. A two-step spatial phase-shifting method is applied to extract the phase distribution in the moiré fringes. By using the filtered back-projection algorithm, we reconstruct the 3D refractive-index distribution of the combustion flow field. Finally, the 3D temperature distribution of the flame is obtained from the refractive index distribution using the Gladstone-Dale equation. Meanwhile, the 3D intensity distribution is reconstructed based on the radiation projections from the emission tomography. Therefore, the structure and edge information of the propane flame are well visualized.

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.

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.

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.

a Novel Deep Convolutional Neural Network for Spectral-Spatial Classification of Hyperspectral Data

NASA Astrophysics Data System (ADS)

Li, N.; Wang, C.; Zhao, H.; Gong, X.; Wang, D.

2018-04-01

Spatial and spectral information are obtained simultaneously by hyperspectral remote sensing. Joint extraction of these information of hyperspectral image is one of most import methods for hyperspectral image classification. In this paper, a novel deep convolutional neural network (CNN) is proposed, which extracts spectral-spatial information of hyperspectral images correctly. The proposed model not only learns sufficient knowledge from the limited number of samples, but also has powerful generalization ability. The proposed framework based on three-dimensional convolution can extract spectral-spatial features of labeled samples effectively. Though CNN has shown its robustness to distortion, it cannot extract features of different scales through the traditional pooling layer that only have one size of pooling window. Hence, spatial pyramid pooling (SPP) is introduced into three-dimensional local convolutional filters for hyperspectral classification. Experimental results with a widely used hyperspectral remote sensing dataset show that the proposed model provides competitive performance.

Reflex ring laser amplifier system

DOEpatents

Summers, M.A.

1983-08-31

The invention is a method and apparatus for providing a reflex ring laser system for amplifying an input laser pulse. The invention is particularly useful in laser fusion experiments where efficient production of high-energy and high power laser pulses is required. The invention comprises a large aperture laser amplifier in an unstable ring resonator which includes a combination spatial filter and beam expander having a magnification greater than unity. An input pulse is injected into the resonator, e.g., through an aperture in an input mirror. The injected pulse passes through the amplifier and spatial filter/expander components on each pass around the ring. The unstable resonator is designed to permit only a predetermined number of passes before the amplified pulse exits the resonator. On the first pass through the amplifier, the beam fills only a small central region of the gain medium. On each successive pass, the beam has been expanded to fill the next concentric non-overlapping region of the gain medium.

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.

Suppression of small-scale self-focusing of high-power laser beams due to their self-filtration during propagation in free space

NASA Astrophysics Data System (ADS)

Ginzburg, V. N.; Kochetkov, A. A.; Potemkin, A. K.; Khazanov, E. A.

2018-04-01

It has been experimentally confirmed that self-cleaning of a laser beam from spatial noise during propagation in free space makes it possible to suppress efficiently the self-focusing instability without applying spatial filters. Measurements of the instability increment by two independent methods have demonstrated quantitative agreement with theory and high efficiency of small-scale self-focusing suppression. This opens new possibilities for using optical elements operating in transmission (frequency doublers, phase plates, beam splitters, polarisers, etc.) in beams with intensities on the order of a few TW cm‑2.

Vitamin D synthesis measured with a multiband filter radiometer in Río Gallegos, Argentina

NASA Astrophysics Data System (ADS)

Orte, Facundo; Wolfram, Elian; Salvador, Jacobo; D'Elia, Raúl; Bulnes, Daniela; Leme, N. Paes; Quel, Eduardo

2013-05-01

Vitamin D plays an important role in human health. Vitamin D production from the sun is affected by UVB solar radiation. This paper presents a simple method for retrieving vitamin D-weighted UV by using a multiband filter radiometer GUV-541 installed at the Atmospheric Observatory of Southern Patagonia (OAPA) (51 ° 33' S, 69° 19' W), Río Gallegos. The methodology used combines irradiance measurements from a multiband filter radiometer with spectral irradiance modeled by the SOS radiative transfer code (developed by Lille University of Science and Technology (USTL)). The spectrum modeled is weighted with vitamin D action spectra published by the International Commission on Illumination (CIE), which describes the relative effectiveness of different wavelengths in the generation of this particular biological response. This method is validated using the vitamin D-weighted UV derived from a Brewer MKIII spectrophotometer (SN 124) belonging to the National Institute for Spatial Research (INPE), Brazil, which is able to measure solar spectra between 290 and 325nm. The method presents a good correlation between the two independent instruments. This procedure increases the instrumental capabilities of the multiband filter radiometer. Moreover, it evaluates the annual variation of vitamin D-weighted UV doses from exposure to ultraviolet radiation. These values are likely to be lower than suitable levels of vitamin D during winter and part of spring and autumn at these latitudes.

Image super-resolution via adaptive filtering and regularization

NASA Astrophysics Data System (ADS)

Ren, Jingbo; Wu, Hao; Dong, Weisheng; Shi, Guangming

2014-11-01

Image super-resolution (SR) is widely used in the fields of civil and military, especially for the low-resolution remote sensing images limited by the sensor. Single-image SR refers to the task of restoring a high-resolution (HR) image from the low-resolution image coupled with some prior knowledge as a regularization term. One classic method regularizes image by total variation (TV) and/or wavelet or some other transform which introduce some artifacts. To compress these shortages, a new framework for single image SR is proposed by utilizing an adaptive filter before regularization. The key of our model is that the adaptive filter is used to remove the spatial relevance among pixels first and then only the high frequency (HF) part, which is sparser in TV and transform domain, is considered as the regularization term. Concretely, through transforming the original model, the SR question can be solved by two alternate iteration sub-problems. Before each iteration, the adaptive filter should be updated to estimate the initial HF. A high quality HF part and HR image can be obtained by solving the first and second sub-problem, respectively. In experimental part, a set of remote sensing images captured by Landsat satellites are tested to demonstrate the effectiveness of the proposed framework. Experimental results show the outstanding performance of the proposed method in quantitative evaluation and visual fidelity compared with the state-of-the-art methods.

Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI.

PubMed

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R

2017-04-01

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels. The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (<35 Hz) frequency ranges. MBRLAF is computationally more demanding than RLAF, but highly effective in all EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best. In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We introduce new algorithms for reducing EEG artifacts due to simultaneous fMRI The algorithms combine a reference layer and adaptive filtering Several evaluation criteria suggest superior effectivity in terms of artifact reduction We demonstrate that physiological EEG components are preserved.

Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI

NASA Astrophysics Data System (ADS)

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R.

2017-04-01

Objective. Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. Approach. To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels. Main results. The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (<35 Hz) frequency ranges. MBRLAF is computationally more demanding than RLAF, but highly effective in all EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best. Significance. In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We introduce new algorithms for reducing EEG artifacts due to simultaneous fMRI The algorithms combine a reference layer and adaptive filtering Several evaluation criteria suggest superior effectivity in terms of artifact reduction We demonstrate that physiological EEG components are preserved

SU-E-I-33: Initial Evaluation of Model-Based Iterative CT Reconstruction Using Standard Image Quality Phantoms

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

Gingold, E; Dave, J

2014-06-01

Purpose: The purpose of this study was to compare a new model-based iterative reconstruction with existing reconstruction methods (filtered backprojection and basic iterative reconstruction) using quantitative analysis of standard image quality phantom images. Methods: An ACR accreditation phantom (Gammex 464) and a CATPHAN600 phantom were scanned using 3 routine clinical acquisition protocols (adult axial brain, adult abdomen, and pediatric abdomen) on a Philips iCT system. Each scan was acquired using default conditions and 75%, 50% and 25% dose levels. Images were reconstructed using standard filtered backprojection (FBP), conventional iterative reconstruction (iDose4) and a prototype model-based iterative reconstruction (IMR). Phantom measurementsmore » included CT number accuracy, contrast to noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD), and noise power spectrum (NPS). Results: The choice of reconstruction method had no effect on CT number accuracy, or MTF (p<0.01). The CNR of a 6 HU contrast target was improved by 1–67% with iDose4 relative to FBP, while IMR improved CNR by 145–367% across all protocols and dose levels. Within each scan protocol, the CNR improvement from IMR vs FBP showed a general trend of greater improvement at lower dose levels. NPS magnitude was greatest for FBP and lowest for IMR. The NPS of the IMR reconstruction showed a pronounced decrease with increasing spatial frequency, consistent with the unusual noise texture seen in IMR images. Conclusion: Iterative Model Reconstruction reduces noise and improves contrast-to-noise ratio without sacrificing spatial resolution in CT phantom images. This offers the possibility of radiation dose reduction and improved low contrast detectability compared with filtered backprojection or conventional iterative reconstruction.« less

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.

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.

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.

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.

SU-G-TeP2-11: Initial Evaluation of a Novel Split-Filter Dual-Energy CT for Use in Radiation Oncology

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

Miller, J; Huang, J; Szczykutowicz, T

2016-06-15

Purpose: To perform an initial evaluation of a novel split-filter dual-energy CT (DECT) system with the goal of understanding the clinical utility and limitations of the system for radiation therapy. Methods: Several phantoms were imaged using the split-filter DECT technique on the Siemens Edge CT scanner using a range of clinically-relevant doses. The optimum-contrast reconstruction, the mixed reconstruction, and the monoenergetic reconstructions (ranging from 40 keV to 190 keV) were evaluated. Each image was analyzed for CT number accuracy, uniformity, noise, low-contrast visibility (LCV), spatial resolution and geometric distortion. For comparison purposes, all parameters were evaluated on 120 kVp single-energymore » CT (SECT) scans used for treatment planning, as well as, a sequential-scan DECT technique for corresponding doses. Results: For all DECT reconstructions no observable geometric distortion was found. Both the optimal-contrast and mixed images demonstrated slight improvements in LCV and noise when compared to the SECT, and slight reductions in CT number accuracy and spatial resolution. The CT numbers trended as expected for the monoenergetic reconstructions, with CT number accuracy within 50 HU for materials of density <2 g/cm3. Spatial resolution increased with energy, and for monoenergetic reconstructions >70 keV the spatial resolution exceeded that of the SECT. The noise in the monoenergetic reconstructions increased with decreasing energy. Thus, the image uniformity, signal-to-noise ratio and LCV were diminished at lower energies (70 keV). Applying iterative reconstruction techniques to the low-energy images reduced noise and improved LCV. The signal-to-noise ratio was stable for energies >100 keV. Conclusion: The initial commissioning of the novel split-filter DECT technology demonstrated favorable results for clinical implementation. The mixed reconstruction showed potential as a replacement for the treatment planning SECT. The image parameters for the monoenergetic reconstructions varied appropriately with energy. This work provides an initial understanding of the limitations and potential applications for monoenergetic imaging.« less

The use of wavelet filters for reducing noise in posterior fossa Computed Tomography images

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

Pita-Machado, Reinado; Perez-Diaz, Marlen, E-mail: mperez@uclv.edu.cu; Lorenzo-Ginori, Juan V., E-mail: mperez@uclv.edu.cu

Wavelet transform based de-noising like wavelet shrinkage, gives the good results in CT. This procedure affects very little the spatial resolution. Some applications are reconstruction methods, while others are a posteriori de-noising methods. De-noising after reconstruction is very difficult because the noise is non-stationary and has unknown distribution. Therefore, methods which work on the sinogram-space don’t have this problem, because they always work over a known noise distribution at this point. On the other hand, the posterior fossa in a head CT is a very complex region for physicians, because it is commonly affected by artifacts and noise which aremore » not eliminated during the reconstruction procedure. This can leads to some false positive evaluations. The purpose of our present work is to compare different wavelet shrinkage de-noising filters to reduce noise, particularly in images of the posterior fossa within CT scans in the sinogram-space. This work describes an experimental search for the best wavelets, to reduce Poisson noise in Computed Tomography (CT) scans. Results showed that de-noising with wavelet filters improved the quality of posterior fossa region in terms of an increased CNR, without noticeable structural distortions.« less

From Flashes to Edges to Objects: Recovery of Local Edge Fragments Initiates Spatiotemporal Boundary Formation

PubMed Central

Erlikhman, Gennady; Kellman, Philip J.

2016-01-01

Spatiotemporal boundary formation (SBF) is the perception of illusory boundaries, global form, and global motion from spatially and temporally sparse transformations of texture elements (Shipley and Kellman, 1993a, 1994; Erlikhman and Kellman, 2015). It has been theorized that the visual system uses positions and times of element transformations to extract local oriented edge fragments, which then connect by known interpolation processes to produce larger contours and shapes in SBF. To test this theory, we created a novel display consisting of a sawtooth arrangement of elements that disappeared and reappeared sequentially. Although apparent motion along the sawtooth would be expected, with appropriate spacing and timing, the resulting percept was of a larger, moving, illusory bar. This display approximates the minimal conditions for visual perception of an oriented edge fragment from spatiotemporal information and confirms that such events may be initiating conditions in SBF. Using converging objective and subjective methods, experiments showed that edge formation in these displays was subject to a temporal integration constraint of ~80 ms between element disappearances. The experiments provide clear support for models of SBF that begin with extraction of local edge fragments, and they identify minimal conditions required for this process. We conjecture that these results reveal a link between spatiotemporal object perception and basic visual filtering. Motion energy filters have usually been studied with orientation given spatially by luminance contrast. When orientation is not given in static frames, these same motion energy filters serve as spatiotemporal edge filters, yielding local orientation from discrete element transformations over time. As numerous filters of different characteristic orientations and scales may respond to any simple SBF stimulus, we discuss the aperture and ambiguity problems that accompany this conjecture and how they might be resolved by the visual system. PMID:27445886

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.

Grid artifact reduction for direct digital radiography detectors based on rotated stationary grids with homomorphic filtering

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

Kim, Dong Sik; Lee, Sanggyun

2013-06-15

Purpose: Grid artifacts are caused when using the antiscatter grid in obtaining digital x-ray images. In this paper, research on grid artifact reduction techniques is conducted especially for the direct detectors, which are based on amorphous selenium. Methods: In order to analyze and reduce the grid artifacts, the authors consider a multiplicative grid image model and propose a homomorphic filtering technique. For minimal damage due to filters, which are used to suppress the grid artifacts, rotated grids with respect to the sampling direction are employed, and min-max optimization problems for searching optimal grid frequencies and angles for given sampling frequenciesmore » are established. The authors then propose algorithms for the grid artifact reduction based on the band-stop filters as well as low-pass filters. Results: The proposed algorithms are experimentally tested for digital x-ray images, which are obtained from direct detectors with the rotated grids, and are compared with other algorithms. It is shown that the proposed algorithms can successfully reduce the grid artifacts for direct detectors. Conclusions: By employing the homomorphic filtering technique, the authors can considerably suppress the strong grid artifacts with relatively narrow-bandwidth filters compared to the normal filtering case. Using rotated grids also significantly reduces the ringing artifact. Furthermore, for specific grid frequencies and angles, the authors can use simple homomorphic low-pass filters in the spatial domain, and thus alleviate the grid artifacts with very low implementation complexity.« less

Linear phase encoding for holographic data storage with a single phase-only spatial light modulator.

PubMed

Nobukawa, Teruyoshi; Nomura, Takanori

2016-04-01

A linear phase encoding is presented for realizing a compact and simple holographic data storage system with a single spatial light modulator (SLM). This encoding method makes it possible to modulate a complex amplitude distribution with a single phase-only SLM in a holographic storage system. In addition, an undesired light due to the imperfection of an SLM can be removed by spatial frequency filtering with a Nyquist aperture. The linear phase encoding is introduced to coaxial holographic data storage. The generation of a signal beam using linear phase encoding is experimentally verified in an interferometer. In a coaxial holographic data storage system, single data recording, shift selectivity, and shift multiplexed recording are experimentally demonstrated.

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%.

On the simulation and mitigation of anisoplanatic optical turbulence for long range imaging

NASA Astrophysics Data System (ADS)

Hardie, Russell C.; LeMaster, Daniel A.

2017-05-01

We describe a numerical wave propagation method for simulating long range imaging of an extended scene under anisoplanatic conditions. Our approach computes an array of point spread functions (PSFs) for a 2D grid on the object plane. The PSFs are then used in a spatially varying weighted sum operation, with an ideal image, to produce a simulated image with realistic optical turbulence degradation. To validate the simulation we compare simulated outputs with the theoretical anisoplanatic tilt correlation and differential tilt variance. This is in addition to comparing the long- and short-exposure PSFs, and isoplanatic angle. Our validation analysis shows an excellent match between the simulation statistics and the theoretical predictions. The simulation tool is also used here to quantitatively evaluate a recently proposed block- matching and Wiener filtering (BMWF) method for turbulence mitigation. In this method block-matching registration algorithm is used to provide geometric correction for each of the individual input frames. The registered frames are then averaged and processed with a Wiener filter for restoration. A novel aspect of the proposed BMWF method is that the PSF model used for restoration takes into account the level of geometric correction achieved during image registration. This way, the Wiener filter is able fully exploit the reduced blurring achieved by registration. The BMWF method is relatively simple computationally, and yet, has excellent performance in comparison to state-of-the-art benchmark methods.

Sharpening advanced land imager multispectral data using a sensor model

USGS Publications Warehouse

Lemeshewsky, G.P.; ,

2005-01-01

The Advanced Land Imager (ALI) instrument on NASA's Earth Observing One (EO-1) satellite provides for nine spectral bands at 30m ground sample distance (GSD) and a 10m GSD panchromatic band. This report describes an image sharpening technique where the higher spatial resolution information of the panchromatic band is used to increase the spatial resolution of ALI multispectral (MS) data. To preserve the spectral characteristics, this technique combines reported deconvolution deblurring methods for the MS data with highpass filter-based fusion methods for the Pan data. The deblurring process uses the point spread function (PSF) model of the ALI sensor. Information includes calculation of the PSF from pre-launch calibration data. Performance was evaluated using simulated ALI MS data generated by degrading the spatial resolution of high resolution IKONOS satellite MS data. A quantitative measure of performance was the error between sharpened MS data and high resolution reference. This report also compares performance with that of a reported method that includes PSF information. Preliminary results indicate improved sharpening with the method reported here.

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.

Fast shear compounding using robust 2-D shear wave speed calculation and multi-directional filtering.

PubMed

Song, Pengfei; Manduca, Armando; Zhao, Heng; Urban, Matthew W; Greenleaf, James F; Chen, Shigao

2014-06-01

A fast shear compounding method was developed in this study using only one shear wave push-detect cycle, such that the shear wave imaging frame rate is preserved and motion artifacts are minimized. The proposed method is composed of the following steps: 1. Applying a comb-push to produce multiple differently angled shear waves at different spatial locations simultaneously; 2. Decomposing the complex shear wave field into individual shear wave fields with differently oriented shear waves using a multi-directional filter; 3. Using a robust 2-D shear wave speed calculation to reconstruct 2-D shear elasticity maps from each filter direction; and 4. Compounding these 2-D maps from different directions into a final map. An inclusion phantom study showed that the fast shear compounding method could achieve comparable performance to conventional shear compounding without sacrificing the imaging frame rate. A multi-inclusion phantom experiment showed that the fast shear compounding method could provide a full field-of-view, 2-D and compounded shear elasticity map with three types of inclusions clearly resolved and stiffness measurements showing excellent agreement to the nominal values. Copyright © 2014 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Visual information processing II; Proceedings of the Meeting, Orlando, FL, Apr. 14-16, 1993

NASA Technical Reports Server (NTRS)

Huck, Friedrich O. (Editor); Juday, Richard D. (Editor)

1993-01-01

Various papers on visual information processing are presented. Individual topics addressed include: aliasing as noise, satellite image processing using a hammering neural network, edge-detetion method using visual perception, adaptive vector median filters, design of a reading test for low-vision image warping, spatial transformation architectures, automatic image-enhancement method, redundancy reduction in image coding, lossless gray-scale image compression by predictive GDF, information efficiency in visual communication, optimizing JPEG quantization matrices for different applications, use of forward error correction to maintain image fidelity, effect of peanoscanning on image compression. Also discussed are: computer vision for autonomous robotics in space, optical processor for zero-crossing edge detection, fractal-based image edge detection, simulation of the neon spreading effect by bandpass filtering, wavelet transform (WT) on parallel SIMD architectures, nonseparable 2D wavelet image representation, adaptive image halftoning based on WT, wavelet analysis of global warming, use of the WT for signal detection, perfect reconstruction two-channel rational filter banks, N-wavelet coding for pattern classification, simulation of image of natural objects, number-theoretic coding for iconic systems.

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.

Medical Image Retrieval Using Multi-Texton Assignment.

PubMed

Tang, Qiling; Yang, Jirong; Xia, Xianfu

2018-02-01

In this paper, we present a multi-texton representation method for medical image retrieval, which utilizes the locality constraint to encode each filter bank response within its local-coordinate system consisting of the k nearest neighbors in texton dictionary and subsequently employs spatial pyramid matching technique to implement feature vector representation. Comparison with the traditional nearest neighbor assignment followed by texton histogram statistics method, our strategies reduce the quantization errors in mapping process and add information about the spatial layout of texton distributions and, thus, increase the descriptive power of the image representation. We investigate the effects of different parameters on system performance in order to choose the appropriate ones for our datasets and carry out experiments on the IRMA-2009 medical collection and the mammographic patch dataset. The extensive experimental results demonstrate that the proposed method has superior performance.

Nanophotonic Image Sensors

PubMed Central

Hu, Xin; Wen, Long; Yu, Yan; Cumming, David R. S.

2016-01-01

The increasing miniaturization and resolution of image sensors bring challenges to conventional optical elements such as spectral filters and polarizers, the properties of which are determined mainly by the materials used, including dye polymers. Recent developments in spectral filtering and optical manipulating techniques based on nanophotonics have opened up the possibility of an alternative method to control light spectrally and spatially. By integrating these technologies into image sensors, it will become possible to achieve high compactness, improved process compatibility, robust stability and tunable functionality. In this Review, recent representative achievements on nanophotonic image sensors are presented and analyzed including image sensors with nanophotonic color filters and polarizers, metamaterial‐based THz image sensors, filter‐free nanowire image sensors and nanostructured‐based multispectral image sensors. This novel combination of cutting edge photonics research and well‐developed commercial products may not only lead to an important application of nanophotonics but also offer great potential for next generation image sensors beyond Moore's Law expectations. PMID:27239941

Neuromorphic Kalman filter implementation in IBM’s TrueNorth

NASA Astrophysics Data System (ADS)

Carney, R.; Bouchard, K.; Calafiura, P.; Clark, D.; Donofrio, D.; Garcia-Sciveres, M.; Livezey, J.

2017-10-01

Following the advent of a post-Moore’s law field of computation, novel architectures continue to emerge. With composite, multi-million connection neuromorphic chips like IBM’s TrueNorth, neural engineering has now become a feasible technology in this novel computing paradigm. High Energy Physics experiments are continuously exploring new methods of computation and data handling, including neuromorphic, to support the growing challenges of the field and be prepared for future commodity computing trends. This work details the first instance of a Kalman filter implementation in IBM’s neuromorphic architecture, TrueNorth, for both parallel and serial spike trains. The implementation is tested on multiple simulated systems and its performance is evaluated with respect to an equivalent non-spiking Kalman filter. The limits of the implementation are explored whilst varying the size of weight and threshold registers, the number of spikes used to encode a state, size of neuron block for spatial encoding, and neuron potential reset schemes.

Comparison of reconstruction methods and quantitative accuracy in Siemens Inveon PET scanner

NASA Astrophysics Data System (ADS)

Ram Yu, A.; Kim, Jin Su; Kang, Joo Hyun; Moo Lim, Sang

2015-04-01

PET reconstruction is key to the quantification of PET data. To our knowledge, no comparative study of reconstruction methods has been performed to date. In this study, we compared reconstruction methods with various filters in terms of their spatial resolution, non-uniformities (NU), recovery coefficients (RCs), and spillover ratios (SORs). In addition, the linearity of reconstructed radioactivity between linearity of measured and true concentrations were also assessed. A Siemens Inveon PET scanner was used in this study. Spatial resolution was measured with NEMA standard by using a 1 mm3 sized 18F point source. Image quality was assessed in terms of NU, RC and SOR. To measure the effect of reconstruction algorithms and filters, data was reconstructed using FBP, 3D reprojection algorithm (3DRP), ordered subset expectation maximization 2D (OSEM 2D), and maximum a posteriori (MAP) with various filters or smoothing factors (β). To assess the linearity of reconstructed radioactivity, image quality phantom filled with 18F was used using FBP, OSEM and MAP (β =1.5 & 5 × 10-5). The highest achievable volumetric resolution was 2.31 mm3 and the highest RCs were obtained when OSEM 2D was used. SOR was 4.87% for air and 3.97% for water, obtained OSEM 2D reconstruction was used. The measured radioactivity of reconstruction image was proportional to the injected one for radioactivity below 16 MBq/ml when FBP or OSEM 2D reconstruction methods were used. By contrast, when the MAP reconstruction method was used, activity of reconstruction image increased proportionally, regardless of the amount of injected radioactivity. When OSEM 2D or FBP were used, the measured radioactivity concentration was reduced by 53% compared with true injected radioactivity for radioactivity <16 MBq/ml. The OSEM 2D reconstruction method provides the highest achievable volumetric resolution and highest RC among all the tested methods and yields a linear relation between the measured and true concentrations for radioactivity Our data collectively showed that OSEM 2D reconstruction method provides quantitatively accurate reconstructed PET data results.

Geometrical superresolved imaging using nonperiodic spatial masking.

PubMed

Borkowski, Amikam; Zalevsky, Zeev; Javidi, Bahram

2009-03-01

The resolution of every imaging system is limited either by the F-number of its optics or by the geometry of its detection array. The geometrical limitation is caused by lack of spatial sampling points as well as by the shape of every sampling pixel that generates spectral low-pass filtering. We present a novel approach to overcome the low-pass filtering that is due to the shape of the sampling pixels. The approach combines special algorithms together with spatial masking placed in the intermediate image plane and eventually allows geometrical superresolved imaging without relation to the actual shape of the pixels.

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.

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.

Large-eddy simulation of a turbulent mixing layer

NASA Technical Reports Server (NTRS)

Mansour, N. N.; Ferziger, J. H.; Reynolds, W. C.

1978-01-01

The three dimensional, time dependent (incompressible) vorticity equations were used to simulate numerically the decay of isotropic box turbulence and time developing mixing layers. The vorticity equations were spatially filtered to define the large scale turbulence field, and the subgrid scale turbulence was modeled. A general method was developed to show numerical conservation of momentum, vorticity, and energy. The terms that arise from filtering the equations were treated (for both periodic boundary conditions and no stress boundary conditions) in a fast and accurate way by using fast Fourier transforms. Use of vorticity as the principal variable is shown to produce results equivalent to those obtained by use of the primitive variable equations.

Spatio-temporal Eigenvector Filtering: Application on Bioenergy Crop Impacts

NASA Astrophysics Data System (ADS)

Wang, M.; Kamarianakis, Y.; Georgescu, M.

2017-12-01

A suite of 10-year ensemble-based simulations was conducted to investigate the hydroclimatic impacts due to large-scale deployment of perennial bioenergy crops across the continental United States. Given the large size of the simulated dataset (about 60Tb), traditional hierarchical spatio-temporal statistical modelling cannot be implemented for the evaluation of physics parameterizations and biofuel impacts. In this work, we propose a filtering algorithm that takes into account the spatio-temporal autocorrelation structure of the data while avoiding spatial confounding. This method is used to quantify the robustness of simulated hydroclimatic impacts associated with bioenergy crops to alternative physics parameterizations and observational datasets. Results are evaluated against those obtained from three alternative Bayesian spatio-temporal specifications.

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.

Method for culturing mammalian cells in a perfused bioreactor

NASA Technical Reports Server (NTRS)

Schwarz, Ray P. (Inventor); Wolf, David A. (Inventor)

1992-01-01

A bio-reactor system wherein a tubular housing contains an internal circularly disposed set of blade members and a central tubular filter all mounted for rotation about a common horizontal axis and each having independent rotational support and rotational drive mechanisms. The housing, blade members and filter preferably are driven at a constant slow speed for placing a fluid culture medium with discrete microbeads and cell cultures in a discrete spatial suspension in the housing. Replacement fluid medium is symmetrically input and fluid medium is symmetrically output from the housing where the input and the output are part of a loop providing a constant or intermittent flow of fluid medium in a closed loop.

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.

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.

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.

Cest Analysis: Automated Change Detection from Very-High Remote Sensing Images

NASA Astrophysics Data System (ADS)

Ehlers, M.; Klonus, S.; Jarmer, T.; Sofina, N.; Michel, U.; Reinartz, P.; Sirmacek, B.

2012-08-01

A fast detection, visualization and assessment of change in areas of crisis or catastrophes are important requirements for coordination and planning of help. Through the availability of new satellites and/or airborne sensors with very high spatial resolutions (e.g., WorldView, GeoEye) new remote sensing data are available for a better detection, delineation and visualization of change. For automated change detection, a large number of algorithms has been proposed and developed. From previous studies, however, it is evident that to-date no single algorithm has the potential for being a reliable change detector for all possible scenarios. This paper introduces the Combined Edge Segment Texture (CEST) analysis, a decision-tree based cooperative suite of algorithms for automated change detection that is especially designed for the generation of new satellites with very high spatial resolution. The method incorporates frequency based filtering, texture analysis, and image segmentation techniques. For the frequency analysis, different band pass filters can be applied to identify the relevant frequency information for change detection. After transforming the multitemporal images via a fast Fourier transform (FFT) and applying the most suitable band pass filter, different methods are available to extract changed structures: differencing and correlation in the frequency domain and correlation and edge detection in the spatial domain. Best results are obtained using edge extraction. For the texture analysis, different 'Haralick' parameters can be calculated (e.g., energy, correlation, contrast, inverse distance moment) with 'energy' so far providing the most accurate results. These algorithms are combined with a prior segmentation of the image data as well as with morphological operations for a final binary change result. A rule-based combination (CEST) of the change algorithms is applied to calculate the probability of change for a particular location. CEST was tested with high-resolution satellite images of the crisis areas of Darfur (Sudan). CEST results are compared with a number of standard algorithms for automated change detection such as image difference, image ratioe, principal component analysis, delta cue technique and post classification change detection. The new combined method shows superior results averaging between 45% and 15% improvement in accuracy.

Detection of urban expansion in an urban-rural landscape with multitemporal QuickBird images

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio; Li, Guiying

2011-01-01

Accurately detecting urban expansion with remote sensing techniques is a challenge due to the complexity of urban landscapes. This paper explored methods for detecting urban expansion with multitemporal QuickBird images in Lucas do Rio Verde, Mato Grosso, Brazil. Different techniques, including image differencing, principal component analysis (PCA), and comparison of classified impervious surface images with the matched filtering method, were used to examine urbanization detection. An impervious surface image classified with the hybrid method was used to modify the urbanization detection results. As a comparison, the original multispectral image and segmentation-based mean-spectral images were used during the detection of urbanization. This research indicates that the comparison of classified impervious surface images with matched filtering method provides the best change detection performance, followed by the image differencing method based on segmentation-based mean spectral images. The PCA is not a good method for urban change detection in this study. Shadows and high spectral variation within the impervious surfaces represent major challenges to the detection of urban expansion when high spatial resolution images are used. PMID:21799706

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

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.

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.

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.

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).

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.

Acquisition of a full-resolution image and aliasing reduction for a spatially modulated imaging polarimeter with two snapshots

PubMed Central

Zhang, Jing; Yuan, Changan; Huang, Guohua; Zhao, Yinjun; Ren, Wenyi; Cao, Qizhi; Li, Jianying; Jin, Mingwu

2018-01-01

A snapshot imaging polarimeter using spatial modulation can encode four Stokes parameters allowing instantaneous polarization measurement from a single interferogram. However, the reconstructed polarization images could suffer a severe aliasing signal if the high-frequency component of the intensity image is prominent and occurs in the polarization channels, and the reconstructed intensity image also suffers reduction of spatial resolution due to low-pass filtering. In this work, a method using two anti-phase snapshots is proposed to address the two problems simultaneously. The full-resolution target image and the pure interference fringes can be obtained from the sum and the difference of the two anti-phase interferograms, respectively. The polarization information reconstructed from the pure interference fringes does not contain the aliasing signal from the high-frequency component of the object intensity image. The principles of the method are derived and its feasibility is tested by both computer simulation and a verification experiment. This work provides a novel method for spatially modulated imaging polarization technology with two snapshots to simultaneously reconstruct a full-resolution object intensity image and high-quality polarization components. PMID:29714224

Hybrid Discrete Wavelet Transform and Gabor Filter Banks Processing for Features Extraction from Biomedical Images

PubMed Central

Lahmiri, Salim; Boukadoum, Mounir

2013-01-01

A new methodology for automatic feature extraction from biomedical images and subsequent classification is presented. The approach exploits the spatial orientation of high-frequency textural features of the processed image as determined by a two-step process. First, the two-dimensional discrete wavelet transform (DWT) is applied to obtain the HH high-frequency subband image. Then, a Gabor filter bank is applied to the latter at different frequencies and spatial orientations to obtain new Gabor-filtered image whose entropy and uniformity are computed. Finally, the obtained statistics are fed to a support vector machine (SVM) binary classifier. The approach was validated on mammograms, retina, and brain magnetic resonance (MR) images. The obtained classification accuracies show better performance in comparison to common approaches that use only the DWT or Gabor filter banks for feature extraction. PMID:27006906

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

Complex sparse spatial filter for decoding mixed frequency and phase coded steady-state visually evoked potentials.

PubMed

Morikawa, Naoki; Tanaka, Toshihisa; Islam, Md Rabiul

2018-07-01

Mixed frequency and phase coding (FPC) can achieve the significant increase of the number of commands in steady-state visual evoked potential-based brain-computer interface (SSVEP-BCI). However, the inconsistent phases of the SSVEP over channels in a trial and the existence of non-contributing channels due to noise effects can decrease accurate detection of stimulus frequency. We propose a novel command detection method based on a complex sparse spatial filter (CSSF) by solving ℓ 1 - and ℓ 2,1 -regularization problems for a mixed-coded SSVEP-BCI. In particular, ℓ 2,1 -regularization (aka group sparsification) can lead to the rejection of electrodes that are not contributing to the SSVEP detection. A calibration data based canonical correlation analysis (CCA) and CSSF with ℓ 1 - and ℓ 2,1 -regularization cases were demonstrated for a 16-target stimuli with eleven subjects. The results of statistical test suggest that the proposed method with ℓ 1 - and ℓ 2,1 -regularization significantly achieved the highest ITR. The proposed approaches do not need any reference signals, automatically select prominent channels, and reduce the computational cost compared to the other mixed frequency-phase coding (FPC)-based BCIs. The experimental results suggested that the proposed method can be usable implementing BCI effectively with reduce visual fatigue. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

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.).

Quantifying spatial and temporal trends in beach-dune volumetric changes using spatial statistics

NASA Astrophysics Data System (ADS)

Eamer, Jordan B. R.; Walker, Ian J.

2013-06-01

Spatial statistics are generally underutilized in coastal geomorphology, despite offering great potential for identifying and quantifying spatial-temporal trends in landscape morphodynamics. In particular, local Moran's Ii provides a statistical framework for detecting clusters of significant change in an attribute (e.g., surface erosion or deposition) and quantifying how this changes over space and time. This study analyzes and interprets spatial-temporal patterns in sediment volume changes in a beach-foredune-transgressive dune complex following removal of invasive marram grass (Ammophila spp.). Results are derived by detecting significant changes in post-removal repeat DEMs derived from topographic surveys and airborne LiDAR. The study site was separated into discrete, linked geomorphic units (beach, foredune, transgressive dune complex) to facilitate sub-landscape scale analysis of volumetric change and sediment budget responses. Difference surfaces derived from a pixel-subtraction algorithm between interval DEMs and the LiDAR baseline DEM were filtered using the local Moran's Ii method and two different spatial weights (1.5 and 5 m) to detect statistically significant change. Moran's Ii results were compared with those derived from a more spatially uniform statistical method that uses a simpler student's t distribution threshold for change detection. Morphodynamic patterns and volumetric estimates were similar between the uniform geostatistical method and Moran's Ii at a spatial weight of 5 m while the smaller spatial weight (1.5 m) consistently indicated volumetric changes of less magnitude. The larger 5 m spatial weight was most representative of broader site morphodynamics and spatial patterns while the smaller spatial weight provided volumetric changes consistent with field observations. All methods showed foredune deflation immediately following removal with increased sediment volumes into the spring via deposition at the crest and on lobes in the lee, despite erosion on the stoss slope and dune toe. Generally, the foredune became wider by landward extension and the seaward slope recovered from erosion to a similar height and form to that of pre-restoration despite remaining essentially free of vegetation.

Improved signal recovery for flow cytometry based on ‘spatially modulated emission’

NASA Astrophysics Data System (ADS)

Quint, S.; Wittek, J.; Spang, P.; Levanon, N.; Walther, T.; Baßler, M.

2017-09-01

Recently, the technique of ‘spatially modulated emission’ has been introduced (Baßler et al 2008 US Patent 0080181827A1; Kiesel et al 2009 Appl. Phys. Lett. 94 041107; Kiesel et al 2011 Cytometry A 79A 317-24) improving the signal-to-noise ratio (SNR) for detecting bio-particles in the field of flow cytometry. Based on this concept, we developed two advanced signal processing methods which further enhance the SNR and selectivity for cell detection. The improvements are achieved by adapting digital filtering methods from RADAR technology and mainly address inherent offset elimination, increased signal dynamics and moreover reduction of erroneous detections due to processing artifacts. We present a comprehensive theory on SNR gain and provide experimental results of our concepts.

Time-alternating method based on single-sideband holography with half-zone-plate processing for the enlargement of viewing zones.

PubMed

Mishina, T; Okano, F; Yuyama, I

1999-06-10

The single-sideband method of holography, as is well known, cuts off beams that come from conjugate images for holograms produced in the Fraunhofer region and from objects with no phase components. The single-sideband method with half-zone-plate processing is also effective in the Fresnel region for beams from an object that has phase components. However, this method restricts the viewing zone to a narrow range. We propose a method to improve this restriction by time-alternating switching of hologram patterns and a spatial filter set on the focal plane of a reconstruction lens.

Geometrical optics modeling of the grating-slit test.

PubMed

Liang, Chao-Wen; Sasian, Jose

2007-02-19

A novel optical testing method termed the grating-slit test is discussed. This test uses a grating and a slit, as in the Ronchi test, but the grating-slit test is different in that the grating is used as the incoherent illuminating object instead of the spatial filter. The slit is located at the plane of the image of a sinusoidal intensity grating. An insightful geometrical-optics model for the grating-slit test is presented and the fringe contrast ratio with respect to the slit width and object-grating period is obtained. The concept of spatial bucket integration is used to obtain the fringe contrast ratio.

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

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.

Fixed Pattern Noise pixel-wise linear correction for crime scene imaging CMOS sensor

NASA Astrophysics Data System (ADS)

Yang, Jie; Messinger, David W.; Dube, Roger R.; Ientilucci, Emmett J.

2017-05-01

Filtered multispectral imaging technique might be a potential method for crime scene documentation and evidence detection due to its abundant spectral information as well as non-contact and non-destructive nature. Low-cost and portable multispectral crime scene imaging device would be highly useful and efficient. The second generation crime scene imaging system uses CMOS imaging sensor to capture spatial scene and bandpass Interference Filters (IFs) to capture spectral information. Unfortunately CMOS sensors suffer from severe spatial non-uniformity compared to CCD sensors and the major cause is Fixed Pattern Noise (FPN). IFs suffer from "blue shift" effect and introduce spatial-spectral correlated errors. Therefore, Fixed Pattern Noise (FPN) correction is critical to enhance crime scene image quality and is also helpful for spatial-spectral noise de-correlation. In this paper, a pixel-wise linear radiance to Digital Count (DC) conversion model is constructed for crime scene imaging CMOS sensor. Pixel-wise conversion gain Gi,j and Dark Signal Non-Uniformity (DSNU) Zi,j are calculated. Also, conversion gain is divided into four components: FPN row component, FPN column component, defects component and effective photo response signal component. Conversion gain is then corrected to average FPN column and row components and defects component so that the sensor conversion gain is uniform. Based on corrected conversion gain and estimated image incident radiance from the reverse of pixel-wise linear radiance to DC model, corrected image spatial uniformity can be enhanced to 7 times as raw image, and the bigger the image DC value within its dynamic range, the better the enhancement.

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.

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.

A new axial smoothing method based on elastic mapping

NASA Astrophysics Data System (ADS)

Yang, J.; Huang, S. C.; Lin, K. P.; Czernin, J.; Wolfenden, P.; Dahlbom, M.; Hoh, C. K.; Phelps, M. E.

1996-12-01

New positron emission tomography (PET) scanners have higher axial and in-plane spatial resolutions but at the expense of reduced per plane sensitivity, which prevents the higher resolution from being fully realized. Normally, Gaussian-weighted interplane axial smoothing is used to reduce noise. In this study, the authors developed a new algorithm that first elastically maps adjacent planes, and then the mapped images are smoothed axially to reduce the image noise level. Compared to those obtained by the conventional axial-directional smoothing method, the images by the new method have improved signal-to-noise ratio. To quantify the signal-to-noise improvement, both simulated and real cardiac PET images were studied. Various Hanning reconstruction filters with cutoff frequency=0.5, 0.7, 1.0/spl times/Nyquist frequency and Ramp filter were tested on simulated images. Effective in-plane resolution was measured by the effective global Gaussian resolution (EGGR) and noise reduction was evaluated by the cross-correlation coefficient. Results showed that the new method was robust to various noise levels and indicated larger noise reduction or better image feature preservation (i.e., smaller EGGR) than by the conventional method.

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.

Phase stability in fMRI time series: effect of noise regression, off-resonance correction and spatial filtering techniques.

PubMed

Hagberg, Gisela E; Bianciardi, Marta; Brainovich, Valentina; Cassara, Antonino Mario; Maraviglia, Bruno

2012-02-15

Although the majority of fMRI studies exploit magnitude changes only, there is an increasing interest regarding the potential additive information conveyed by the phase signal. This integrated part of the complex number furnished by the MR scanners can also be used for exploring direct detection of neuronal activity and for thermography. Few studies have explicitly addressed the issue of the available signal stability in the context of phase time-series, and therefore we explored the spatial pattern of frequency specific phase fluctuations, and evaluated the effect of physiological noise components (heart beat and respiration) on the phase signal. Three categories of retrospective noise reduction techniques were explored and the temporal signal stability was evaluated in terms of a physiologic noise model, for seven fMRI measurement protocols in eight healthy subjects at 3T, for segmented CSF, gray and white matter voxels. We confirmed that for most processing methods, an efficient use of the phase information is hampered by the fact that noise from physiological and instrumental sources contributes significantly more to the phase than to the magnitude instability. Noise regression based on the phase evolution of the central k-space point, RETROICOR, or an orthonormalized combination of these were able to reduce their impact, but without bringing phase stability down to levels expected from the magnitude signal. Similar results were obtained after targeted removal of scan-to-scan variations in the bulk magnetic field by the dynamic off-resonance in k-space (DORK) method and by the temporal off-resonance alignment of single-echo time series technique (TOAST). We found that spatial high-pass filtering was necessary, and in vivo a Gaussian filter width of 20mm was sufficient to suppress physiological noise and bring the phase fluctuations to magnitude levels. Stronger filters brought the fluctuations down to levels dictated by thermal noise contributions, and for 62.5mm(3) voxels the phase stability was as low as 5 mrad (0.27°). In conditions of low SNR(o) and high temporal sampling rate (short TR); we achieved an upper bound for the phase instabilities at 0.0017 ppm, which is close to the dHb contribution to the GM/WM phase contrast. Copyright © 2011 Elsevier Inc. All rights reserved.

In vivo single-shot three-dimensionally localized multiple quantum spectroscopy of GABA in the human brain with improved spectral selectivity

NASA Astrophysics Data System (ADS)

Choi, In-Young; Lee, Sang-Pil; Shen, Jun

2005-01-01

A single-shot multiple quantum filtering method is developed that uses two double-band frequency selective pulses for enhanced spectral selectivity in combination with a slice-selective 90°, a slice-selective universal rotator 90°, and a spectral-spatial pulse composed of two slice-selective universal rotator 45° pulses for single-shot three-dimensional localization. The use of this selective multiple quantum filtering method for C3 and C4 methylene protons of GABA resulted in improved spectral selectivity for GABA and effective suppression of overlapping signals such as creatine and glutathione in each single scan, providing reliable measurements of the GABA doublet in all subjects. The concentration of GABA was measured to be 0.7 ± 0.2 μmol/g (means ± SD, n = 15) in the fronto-parietal region of the human brain in vivo.

Smart Optical Material Characterization System and Method

NASA Technical Reports Server (NTRS)

Choi, Sang Hyouk (Inventor); Park, Yeonjoon (Inventor)

2015-01-01

Disclosed is a system and method for characterizing optical materials, using steps and equipment for generating a coherent laser light, filtering the light to remove high order spatial components, collecting the filtered light and forming a parallel light beam, splitting the parallel beam into a first direction and a second direction wherein the parallel beam travelling in the second direction travels toward the material sample so that the parallel beam passes through the sample, applying various physical quantities to the sample, reflecting the beam travelling in the first direction to produce a first reflected beam, reflecting the beam that passes through the sample to produce a second reflected beam that travels back through the sample, combining the second reflected beam after it travels back though the sample with the first reflected beam, sensing the light beam produced by combining the first and second reflected beams, and processing the sensed beam to determine sample characteristics and properties.

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

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.

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.

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

Spatio-Temporal Field Estimation Using Kriged Kalman Filter (KKF) with Sparsity-Enforcing Sensor Placement.

PubMed

Roy, Venkat; Simonetto, Andrea; Leus, Geert

2018-06-01

We propose a sensor placement method for spatio-temporal field estimation based on a kriged Kalman filter (KKF) using a network of static or mobile sensors. The developed framework dynamically designs the optimal constellation to place the sensors. We combine the estimation error (for the stationary as well as non-stationary component of the field) minimization problem with a sparsity-enforcing penalty to design the optimal sensor constellation in an economic manner. The developed sensor placement method can be directly used for a general class of covariance matrices (ill-conditioned or well-conditioned) modelling the spatial variability of the stationary component of the field, which acts as a correlated observation noise, while estimating the non-stationary component of the field. Finally, a KKF estimator is used to estimate the field using the measurements from the selected sensing locations. Numerical results are provided to exhibit the feasibility of the proposed dynamic sensor placement followed by the KKF estimation method.

Processing and analysis of cardiac optical mapping data obtained with potentiometric dyes

PubMed Central

Laughner, Jacob I.; Ng, Fu Siong; Sulkin, Matthew S.; Arthur, R. Martin

2012-01-01

Optical mapping has become an increasingly important tool to study cardiac electrophysiology in the past 20 years. Multiple methods are used to process and analyze cardiac optical mapping data, and no consensus currently exists regarding the optimum methods. The specific methods chosen to process optical mapping data are important because inappropriate data processing can affect the content of the data and thus alter the conclusions of the studies. Details of the different steps in processing optical imaging data, including image segmentation, spatial filtering, temporal filtering, and baseline drift removal, are provided in this review. We also provide descriptions of the common analyses performed on data obtained from cardiac optical imaging, including activation mapping, action potential duration mapping, repolarization mapping, conduction velocity measurements, and optical action potential upstroke analysis. Optical mapping is often used to study complex arrhythmias, and we also discuss dominant frequency analysis and phase mapping techniques used for the analysis of cardiac fibrillation. PMID:22821993

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.

Methods and means of Fourier-Stokes polarimetry and the spatial frequency filtering of phase anisotropy manifestations

NASA Astrophysics Data System (ADS)

Novakovskaya, O. Yu.; Ushenko, A. G.; Dubolazov, A. V.; Ushenko, V. A.; Ushenko, Yu. A.; Sakhnovskiy, M. Yu.; Soltys, I. V.; Zhytaryuk, V. H.; Olar, O. V.; Sidor, M.; Gorsky, M. P.

2016-12-01

The theoretical background of azimuthally stable method of Jones-matrix mapping of histological sections of biopsy of myocardium tissue on the basis of spatial frequency selection of the mechanisms of linear and circular birefringence is presented. The diagnostic application of a new correlation parameter - complex degree of mutual anisotropy - is analytically substantiated. The method of measuring coordinate distributions of complex degree of mutual anisotropy with further spatial filtration of their high- and low-frequency components is developed. The interconnections of such distributions with parameters of linear and circular birefringence of myocardium tissue histological sections are found. The comparative results of measuring the coordinate distributions of complex degree of mutual anisotropy formed by fibrillar networks of myosin fibrils of myocardium tissue of different necrotic states - dead due to coronary heart disease and acute coronary insufficiency are shown. The values and ranges of change of the statistical (moments of the 1st - 4th order) parameters of complex degree of mutual anisotropy coordinate distributions are studied. The objective criteria of differentiation of cause of death are determined.

Variational Bayesian Inversion of Quasi-Localized Seismic Attributes for the Spatial Distribution of Geological Facies

NASA Astrophysics Data System (ADS)

Nawaz, Muhammad Atif; Curtis, Andrew

2018-04-01

We introduce a new Bayesian inversion method that estimates the spatial distribution of geological facies from attributes of seismic data, by showing how the usual probabilistic inverse problem can be solved using an optimization framework still providing full probabilistic results. Our mathematical model consists of seismic attributes as observed data, which are assumed to have been generated by the geological facies. The method infers the post-inversion (posterior) probability density of the facies plus some other unknown model parameters, from the seismic attributes and geological prior information. Most previous research in this domain is based on the localized likelihoods assumption, whereby the seismic attributes at a location are assumed to depend on the facies only at that location. Such an assumption is unrealistic because of imperfect seismic data acquisition and processing, and fundamental limitations of seismic imaging methods. In this paper, we relax this assumption: we allow probabilistic dependence between seismic attributes at a location and the facies in any neighbourhood of that location through a spatial filter. We term such likelihoods quasi-localized.

Fourier spatial frequency analysis for image classification: training the training set

NASA Astrophysics Data System (ADS)

Johnson, Timothy H.; Lhamo, Yigah; Shi, Lingyan; Alfano, Robert R.; Russell, Stewart

2016-04-01

The Directional Fourier Spatial Frequencies (DFSF) of a 2D image can identify similarity in spatial patterns within groups of related images. A Support Vector Machine (SVM) can then be used to classify images if the inter-image variance of the FSF in the training set is bounded. However, if variation in FSF increases with training set size, accuracy may decrease as the size of the training set increases. This calls for a method to identify a set of training images from among the originals that can form a vector basis for the entire class. Applying the Cauchy product method we extract the DFSF spectrum from radiographs of osteoporotic bone, and use it as a matched filter set to eliminate noise and image specific frequencies, and demonstrate that selection of a subset of superclassifiers from within a set of training images improves SVM accuracy. Central to this challenge is that the size of the search space can become computationally prohibitive for all but the smallest training sets. We are investigating methods to reduce the search space to identify an optimal subset of basis training images.

Computation of transmitted and received B1 fields in magnetic resonance imaging.

PubMed

Milles, Julien; Zhu, Yue Min; Chen, Nan-Kuei; Panych, Lawrence P; Gimenez, Gérard; Guttmann, Charles R G

2006-05-01

Computation of B1 fields is a key issue for determination and correction of intensity nonuniformity in magnetic resonance images. This paper presents a new method for computing transmitted and received B1 fields. Our method combines a modified MRI acquisition protocol and an estimation technique based on the Levenberg-Marquardt algorithm and spatial filtering. It enables accurate estimation of transmitted and received B1 fields for both homogeneous and heterogeneous objects. The method is validated using numerical simulations and experimental data from phantom and human scans. The experimental results are in agreement with theoretical expectations.

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.

Infrared maritime target detection using the high order statistic filtering in fractional Fourier domain

NASA Astrophysics Data System (ADS)

Zhou, Anran; Xie, Weixin; Pei, Jihong

2018-06-01

Accurate detection of maritime targets in infrared imagery under various sea clutter conditions is always a challenging task. The fractional Fourier transform (FRFT) is the extension of the Fourier transform in the fractional order, and has richer spatial-frequency information. By combining it with the high order statistic filtering, a new ship detection method is proposed. First, the proper range of angle parameter is determined to make it easier for the ship components and background to be separated. Second, a new high order statistic curve (HOSC) at each fractional frequency point is designed. It is proved that maximal peak interval in HOSC reflects the target information, while the points outside the interval reflect the background. And the value of HOSC relative to the ship is much bigger than that to the sea clutter. Then, search the curve's maximal target peak interval and extract the interval by bandpass filtering in fractional Fourier domain. The value outside the peak interval of HOSC decreases rapidly to 0, so the background is effectively suppressed. Finally, the detection result is obtained by the double threshold segmenting and the target region selection method. The results show the proposed method is excellent for maritime targets detection with high clutters.

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.

Using mixture tuned match filtering to measure changes in subpixel vegetation area in Las Vegas, Nevada

NASA Astrophysics Data System (ADS)

Brelsford, Christa; Shepherd, Doug

2013-09-01

In desert cities, securing sufficient water supply to meet the needs of both existing population and future growth is a complex problem with few easy solutions. Grass lawns are a major driver of water consumption and accurate measurements of vegetation area are necessary to understand drivers of changes in household water consumption. Measuring vegetation change in a heterogeneous urban environment requires sub-pixel estimation of vegetation area. Mixture Tuned Match Filtering has been successfully applied to target detection for materials that only cover small portions of a satellite image pixel. There have been few successful applications of MTMF to fractional area estimation, despite theory that suggests feasibility. We use a ground truth dataset over ten times larger than that available for any previous MTMF application to estimate the bias between ground truth data and matched filter results. We find that the MTMF algorithm underestimates the fractional area of vegetation by 5-10%, and calculate that averaging over 20 to 30 pixels is necessary to correct this bias. We conclude that with a large ground truth dataset, using MTMF for fractional area estimation is possible when results can be estimated at a lower spatial resolution than the base image. When this method is applied to estimating vegetation area in Las Vegas, NV spatial and temporal trends are consistent with expectations from known population growth and policy goals.

Study of acoustic emission during mechanical tests of large flight weight tank structure

NASA Technical Reports Server (NTRS)

Nakamura, Y.; Mccauley, B. O.; Veach, C. L.

1972-01-01

A polyphenylane oxide insulated, flight weight, subscale, aluminum tank was monitored for acoustic emissions during a proof test and during 100 cycles of environmental test simulating space flights. The use of a combination of frequency filtering and appropriate spatial filtering to reduce background noise was found to be sufficient to detect acoustic emission signals of relatively small intensity expected from subcritical crack growth in the structure. Several emission source locations were identified, including the one where a flaw was detected by post-test X-ray inspections. For most source locations, however, post-test inspections did not detect flaws; this was partially attributed to the higher sensitivity of the acoustic emission technique than any other currently available NDT method for detecting flaws.

Fine Metal Mask 3-Dimensional Measurement by using Scanning Digital Holographic Microscope

NASA Astrophysics Data System (ADS)

Shin, Sanghoon; Yu, Younghun

2018-04-01

For three-dimensional microscopy, fast and high axial resolution are very important. Extending the depth of field for digital holographic is necessary for three-dimensional measurements of thick samples. We propose an optical sectioning method for optical scanning digital holography that is performed in the frequency domain by spatial filtering of a reconstructed amplitude image. We established a scanning dual-wavelength off-axis digital holographic microscope to measure samples that exhibit a large amount of coherent noise and a thickness larger than the depth of focus of the objective lens. As a demonstration, we performed a three-dimensional measurement of a fine metal mask with a reconstructed sectional phase image and filtering with a reconstructed amplitude image.

Improved line-end foreshortening and corner-rounding control in optical proximity correction using radius of curvature method

NASA Astrophysics Data System (ADS)

Mukherjee, Maharaj; Phan, Vinhthuy

2002-07-01

We describe how to generate better Optical Proximity Corrections (OPC) for line-ends and corners by using rounded anchors and serifs. These rounded serifs and anchors can be made smaller in size and shape than the traditional rectilinear anchors and serifs. The smaller size of the serifs tend to have less problems in satisfying mask-rule constraints. They also have less adverse effects on the printability of neighboring shapes. We refer to these rounded anchors and serifs as Mouse-Ears. The rounding is done by circles which are regular octagons with Ortho-45 straight lines. The main idea of this paper stems from the physical description of the lithographic process, which can be conceptualized as a low-pass filter. The low-pass filter eliminates the sharp corners of the feature which are made of high spatial-frequency components and retains the low spatial-frequency components. Since the rounded anchors and serifs have fewer high-frequency components than their rectilinear counterparts they get less deformed in the lithographic process.

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.

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.

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.

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.

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

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.

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.

Method for Pre-Conditioning a Measured Surface Height Map for Model Validation

NASA Technical Reports Server (NTRS)

Sidick, Erkin

2012-01-01

This software allows one to up-sample or down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. Because the re-sampling of a surface map is accomplished based on the analytical expressions of Zernike-polynomials and a power spectral density model, such re-sampling does not introduce any aliasing and interpolation errors as is done by the conventional interpolation and FFT-based (fast-Fourier-transform-based) spatial-filtering method. Also, this new method automatically eliminates the measurement noise and other measurement errors such as artificial discontinuity. The developmental cycle of an optical system, such as a space telescope, includes, but is not limited to, the following two steps: (1) deriving requirements or specs on the optical quality of individual optics before they are fabricated through optical modeling and simulations, and (2) validating the optical model using the measured surface height maps after all optics are fabricated. There are a number of computational issues related to model validation, one of which is the "pre-conditioning" or pre-processing of the measured surface maps before using them in a model validation software tool. This software addresses the following issues: (1) up- or down-sampling a measured surface map to match it with the gridded data format of a model validation tool, and (2) eliminating the surface measurement noise or measurement errors such that the resulted surface height map is continuous or smoothly-varying. So far, the preferred method used for re-sampling a surface map is two-dimensional interpolation. The main problem of this method is that the same pixel can take different values when the method of interpolation is changed among the different methods such as the "nearest," "linear," "cubic," and "spline" fitting in Matlab. The conventional, FFT-based spatial filtering method used to eliminate the surface measurement noise or measurement errors can also suffer from aliasing effects. During re-sampling of a surface map, this software preserves the low spatial-frequency characteristic of a given surface map through the use of Zernike-polynomial fit coefficients, and maintains mid- and high-spatial-frequency characteristics of the given surface map by the use of a PSD model derived from the two-dimensional PSD data of the mid- and high-spatial-frequency components of the original surface map. Because this new method creates the new surface map in the desired sampling format from analytical expressions only, it does not encounter any aliasing effects and does not cause any discontinuity in the resultant surface map.

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

Video quality assessment method motivated by human visual perception

NASA Astrophysics Data System (ADS)

He, Meiling; Jiang, Gangyi; Yu, Mei; Song, Yang; Peng, Zongju; Shao, Feng

2016-11-01

Research on video quality assessment (VQA) plays a crucial role in improving the efficiency of video coding and the performance of video processing. It is well acknowledged that the motion energy model generates motion energy responses in a middle temporal area by simulating the receptive field of neurons in V1 for the motion perception of the human visual system. Motivated by the biological evidence for the visual motion perception, a VQA method is proposed in this paper, which comprises the motion perception quality index and the spatial index. To be more specific, the motion energy model is applied to evaluate the temporal distortion severity of each frequency component generated from the difference of Gaussian filter bank, which produces the motion perception quality index, and the gradient similarity measure is used to evaluate the spatial distortion of the video sequence to get the spatial quality index. The experimental results of the LIVE, CSIQ, and IVP video databases demonstrate that the random forests regression technique trained by the generated quality indices is highly correspondent to human visual perception and has many significant improvements than comparable well-performing methods. The proposed method has higher consistency with subjective perception and higher generalization capability.

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.

Iterative Inverse Modeling for Reconciliation of Emission Inventories during the 2006 TexAQS Intensive Field Campaign

NASA Astrophysics Data System (ADS)

Xiao, X.; Cohan, D. S.

2009-12-01

Substantial uncertainties in current emission inventories have been detected by the Texas Air Quality Study 2006 (TexAQS 2006) intensive field program. These emission uncertainties have caused large inaccuracies in model simulations of air quality and its responses to management strategies. To improve the quantitative understanding of the temporal, spatial, and categorized distributions of primary pollutant emissions by utilizing the corresponding measurements collected during TexAQS 2006, we implemented both the recursive Kalman filter and a batch matrix inversion 4-D data assimilation (FDDA) method in an iterative inverse modeling framework of the CMAQ-DDM model. Equipped with the decoupled direct method, CMAQ-DDM enables simultaneous calculation of the sensitivity coefficients of pollutant concentrations to emissions to be used in the inversions. Primary pollutant concentrations measured by the multiple platforms (TCEQ ground-based, NOAA WP-3D aircraft and Ronald H. Brown vessel, and UH Moody Tower) during TexAQS 2006 have been integrated for the use in the inverse modeling. Firstly pseudo-data analyses have been conducted to assess the two methods, taking a coarse spatial resolution emission inventory as a case. Model base case concentrations of isoprene and ozone at arbitrarily selected ground grid cells were perturbed to generate pseudo measurements with different assumed Gaussian uncertainties expressed by 1-sigma standard deviations. Single-species inversions have been conducted with both methods for isoprene and NOx surface emissions from eight states in the Southeastern United States by using the pseudo measurements of isoprene and ozone, respectively. Utilization of ozone pseudo data to invert for NOx emissions serves only for the purpose of method assessment. Both the Kalman filter and FDDA methods show good performance in tuning arbitrarily shifted a priori emissions to the base case “true” values within 3-4 iterations even for the nonlinear responses of ozone to NOx emissions. While the Kalman filter has better performance under the situation of very large observational uncertainties, the batch matrix FDDA method is better suited for incorporating temporally and spatially irregular data such as those measured by NOAA aircraft and ship. After validating the methods with the pseudo data, the inverse technique is applied to improve emission estimates of NOx from different source sectors and regions in the Houston metropolitan area by using NOx measurements during TexAQS 2006. EPA NEI2005-based and Texas-specified Emission Inventories for 2006 are used as the a priori emission estimates before optimization. The inversion results will be presented and discussed. Future work will conduct inverse modeling for additional species, and then perform a multi-species inversion for emissions consistency and reconciliation with secondary pollutants such as ozone.