Showing papers on "Spatial filter published in 2014"

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

Abstract: 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.

Automatic Feature Learning for Spatio-Spectral Image Classification With Sparse SVM

Abstract: Including spatial information is a key step for successful remote sensing image classification. In particular, when dealing with high spatial resolution, if local variability is strongly reduced by spatial filtering, the classification performance results are boosted. In this paper, we consider the triple objective of designing a spatial/spectral classifier, which is compact (uses as few features as possible), discriminative (enhances class separation), and robust (works well in small sample situations). We achieve this triple objective by discovering the relevant features in the (possibly infinite) space of spatial filters by optimizing a margin-maximization criterion. Instead of imposing a filter bank with predefined filter types and parameters, we let the model figure out which set of filters is optimal for class separation. To do so, we randomly generate spatial filter banks and use an active-set criterion to rank the candidate features according to their benefits to margin maximization (and, thus, to generalization) if added to the model. Experiments on multispectral very high spatial resolution (VHR) and hyperspectral VHR data show that the proposed algorithm, which is sparse and linear, finds discriminative features and achieves at least the same performances as models using a large filter bank defined in advance by prior knowledge.

Effects of spatial coherence in diffraction phase microscopy

Abstract: 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.

An informed parametric spatial filter based on instantaneous direction-of-arrival estimates

Abstract: Extracting desired source signals in noisy and reverberant environments is required in many hands-free communication systems. In practical situations, where the position and number of active sources may be unknown and time-varying, conventional implementations of spatial filters do not provide sufficiently good performance. Recently, informed spatial filters have been introduced that incorporate almost instantaneous parametric information on the sound field, thereby enabling adaptation to new acoustic conditions and moving sources. In this contribution, we propose a spatial filter which generalizes the recently proposed informed linearly constrained minimum variance filter and informed minimum mean square error filter. The proposed filter uses multiple direction-of-arrival estimates and second-order statistics of the noise and diffuse sound. To determine those statistics, an optimal diffuse power estimator is proposed that outperforms state-of-the-art estimators. Extensive performance evaluation demonstrates the effectiveness of the proposed filter in dynamic acoustic conditions. For this purpose, we have considered a challenging scenario which consists of quickly moving sound sources during double-talk. The performance of the proposed spatial filter was evaluated in terms of objective measures including segmental signal-to-reverberation ratio and log spectral distance, and by means of a listening test confirming the objective results.

On the appropriate filtering of PIV measurements of turbulent shear flows

Abstract: The three-dimensional spatial filtering and measurement noise associated with experimental planar and three-dimensional (3D) particle image velocimetry (PIV) measurements is investigated using a combination of direct numerical simulations (DNS) and experimental databases. Spatial filtering velocity fields from a DNS of a zero-pressure-gradient turbulent boundary layer (TBL) at resolutions typical of PIV experiments are shown to underestimate Reynolds stresses by as much as 50 %. Comparison of experimental PIV measurement of a turbulent channel flow and 3D tomographic PIV measurements of a TBL with higher-resolution simulations and hot-wire anemometry measurements show that in real experiments, measurement noise acts to offset this effect. This is shown to produce measurements that appear to provide a good estimate of the turbulent fluctuations in the flow, when in reality the flow is spatially under-resolved and partially contaminated by noise. Means of identifying this noise are demonstrated using the one-dimensional (1D) velocity power spectra and the 1D transfer function between the power spectra of the unfiltered velocity field and the power spectra calculated from the filtered experimental measurement. This 1D transfer function differs from the commonly used sinc transfer function of PIV owing to the integrated effect of filtering in multiple directions. Failure to incorporate this difference is shown to overestimate the maximum resolved wave number in the 3D spectra of the planar PIV by close to 10 %, while conversely underestimating the maximum resolved wave number in the 3D PIV by 50 %. Appropriate spatial filtering of the experimental data is shown to remove the noise-dominated small-scale fluctuations and bring the data inline with that which should be obtained for a noiseless PIV measurement at the corresponding spatial resolution.

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

Abstract: 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 $8\times 8$ pixels per diffraction limited spot. For the LG$_{10}$ orbital angular momentum mode the calculated fidelity is $F=0.99993$, using $768\times 768$ 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.

Informed spatial filtering for sound extraction using distributed microphone arrays

Abstract: Hands-free acquisition of speech is required in many human-machine interfaces and communication systems. The signals received by integrated microphones contain a desired speech signal, spatially coherent interfering signals, and background noise. In order to enhance the desired speech signal, state-of-the-art techniques apply data-dependent spatial filters which require the second order statistics (SOS) of the desired signal, the interfering signals and the background noise. As the number of sources and the reverberation time increase, the estimation accuracy of the SOS deteriorates, often resulting in insufficient noise and interference reduction. In this paper, a signal extraction framework with distributed microphone arrays is developed. An expectation maximization (EM)-based algorithm detects the number of coherent speech sources and estimates source clusters using time-frequency (TF) bin-wise position estimates. Subsequently, the second order statistics (SOS) are estimated using bin-wise speech presence probability (SPP) and a source probability for each source. Finally, a desired source is extracted using a minimum variance distortionless response (MVDR) filter, a multichannel Wiener filter (MWF) and a parametric multichannel Wiener filter (PMWF). The same framework can be employed for source separation, where a spatial filter is computed for each source considering the remaining sources as interferers. Evaluation using simulated and measured data demonstrates the effectiveness of the framework in estimating the number of sources, clustering, signal enhancement, and source separation.

On-sky performance during verification and commissioning of the Gemini Planet Imager's adaptive optics system

Abstract: The Gemini Planet Imager instrument's adaptive optics (AO) subsystem was designed specifically to facilitate high-contrast imaging. It features several new technologies, including computationally efficient wavefront reconstruction with the Fourier transform, modal gain optimization every 8 seconds, and the spatially filtered wavefront sensor. It also uses a Linear-Quadratic-Gaussian (LQG) controller (aka Kalman filter) for both pointing and focus. We present on-sky performance results from verification and commissioning runs from December 2013 through May 2014. The efficient reconstruction and modal gain optimization are working as designed. The LQG controllers effectively notch out vibrations. The spatial filter can remove aliases, but we typically use it oversized by about 60% due to stability problems.

Twin-image problem in digital holography—a survey (Invited Paper)

Abstract: Zero-order and twin images are a serious obstacle in achieving a high-quality output in in-line digital holography (DH). They decrease the useful bandwidth of the off-axis DH. Over the years the twin image removal problem was approached both by instrumental and numerical means. The paper provides an extended survey of the proposed solutions with their pros and cons as a guide for further advance in this field. Processing of a single spatial carrier fringe pattern involves spatial filtering in the frequency domain, spatial phase-shifting (PS) or wavelet transform. A point source digital holographic microscopy (DHM), introduction of calibration measurements or various modifications of PS technique are instrumental solutions to the twin image problem for in-line DH. Numerical solutions to the same problem include iterative and non-iterative approaches, diffraction-based and inverse problem solutions, reconstruction of purely real or phase objects and of complex objects, reconstruction of plane and volume objects. Elimination only of the zero-order image relies on non-linear filtering or additional calibration measurements.

Spatial Adaptive Speckle Filtering Driven by Temporal Polarimetric Statistics and Its Application to PSI

Abstract: Persistent scatterer (PS) interferometry (PSI) techniques are designed to measure ground deformations using satellite synthetic aperture radar (SAR) data. They rely on the identification of pixels not severely affected by spatial or temporal decorrelation, which, in general, correspond to pointlike PSs commonly found in urban areas. However, in urban areas, we can find not only PSs but also distributed scatterers (DSs) whose phase information may be exploited for PSI applications. Estimation of DS parameters requires speckle filtering to be applied to the complex SAR data, but conventional speckle filtering approaches tend to mask PS information due to spatial averaging. In the context of single-polarization PSI, adaptive speckle filtering strategies based on the exploitation of amplitude temporal statistics have been proposed, which seek to avoid spatial filtering on nonhomogeneous areas. Given the growing interest on polarimetric PSI techniques, i.e., those using polarimetric diversity to increase performance over conventional single-polarization PSI, in this paper, we propose an adaptive spatial filter driven by polarimetric temporal statistics, rather than single-polarization amplitudes. The proposed approach is able to filter DS while preserving PS information. In addition, a new methodology for the joint processing of PS and DS in the context of PSI is introduced. The technique has been tested for two different urban data sets: 41 dual-polarization TerraSAR-X images of Murcia (Spain) and 31 full-polarization Radarsat-2 images of Barcelona (Spain). Results show an important improvement in terms of number of pixels with valid deformation information, hence denser area coverage.

Phase velocity tomography of surface waves using ambient noise cross correlation and array processing

Abstract: Continuous recordings of ambient seismic noise across large seismic arrays allows a new type of processing using the cross-correlation technique on broadband data. We propose to apply double beamforming (DBF) to cross correlations to extract a particular wave component of the reconstructed signals. We focus here on the extraction of the surface waves to measure phase velocity variations with great accuracy. DBF acts as a spatial filter between two distant subarrays after cross correlation of the wavefield between each single receiver pair. During the DBF process, horizontal slowness and azimuth are used to select the wavefront on both subarray sides. DBF increases the signal-to-noise ratio, which improves the extraction of the dispersive wave packets. This combination of cross correlation and DBF is used on the Transportable Array (USArray), for the central U.S. region. A standard model of surface wave propagation is constructed from a combination of the DBF and cross correlations at different offsets and for different frequency bands. The perturbation (phase shift) between each beam and the standard model is inverted. High-resolution maps of the phase velocity of Rayleigh and Love waves are then constructed. Finally, the addition of azimuthal information provided by DBF is discussed, to construct curved rays that replace the classical great-circle path assumption.

GPC light shaper: static and dynamic experimental demonstrations

Abstract: Generalized Phase Contrast (GPC) is an efficient method for generating speckle-free contiguous optical distributions useful in diverse applications such as static beam shaping, optical manipulation and, recently, for excitation in two-photon optogenetics. GPC allows efficient utilization of typical Gaussian lasers in such applications using binary-only phase modulation. In this work, we experimentally verify previously derived conditions for photon-efficient light shaping with GPC [Opt. Express22(5), 5299 (2014)]. We demonstrate a compact implementation of GPC for creating practical illumination shapes that can find use in light-efficient industrial or commercial applications. Using a dynamic spatial light modulator, we also show simple and efficient beam shaping of reconfigurable shapes geared towards materials processing, biophotonics research and other contemporary applications. Our experiments give ~80% efficiency, ~3x intensity gain, and ~90% energy savings which are in good agreement with previous theoretical estimations.

GPC Light Shaper for speckle-free one- and two-photon contiguous pattern excitation

Abstract: Generalized Phase Contrast (GPC) is an efficient method for generating speckle-free contiguous optical distributions useful in diverse applications such as static beam shaping, optical manipulation and recently, for excitation in two-photon optogenetics. To fully utilize typical Gaussian lasers in such applications, we analytically derive conditions for photon efficient light shaping with GPC. When combined with the conditions for optimal contrast developed in previous works, our analysis further simplifies GPC’s implementation. The results of our analysis are applied to practical illumination shapes, such as a circle and different rectangles commonly used in industrial or commercial applications. We also show simple and efficient beam shaping of arbitrary shapes geared towards biophotonics research and other contemporary applications. Optimized GPC configurations consistently give ~84% efficiency and ~3x intensity gain. Assessment of the energy savings when comparing to conventional amplitude masking show that ~93% of typical energy losses are saved with optimized GPC configurations.

Anamorphic optical transformation of an amplitude spatial light modulator to a complex spatial light modulator with square pixels [Invited]

Abstract: A method is proposed for the construction of a square pixel complex spatial light modulator (SLM) from a commercial oblong full-high-definition (full-HD) amplitude SLM using an anamorphic optical filter. In the proposed scheme, one half-band of the optical Fourier transform of the amplitude-only spatial light field is rejected in the optical Fourier plane and the other half-band is reformatted to be an effective complex SLM with square pixels. This has an advantage in the viewing window plane since the shape of the viewing window becomes square and more ideal for observers who watch the hologram contents through it. For optimal transformation, the amplitude computer generated hologram encoding scheme was developed. Mathematical modeling of the proposed system is described herein, and it was experimentally demonstrated that the effective complex SLM displays complex holographic three-dimensional images with a clear depth discrimination effect.

A 4-Element Phased-Array System With Simultaneous Spatial- and Frequency-Domain Filtering at the Antenna Inputs

Abstract: To reject strong interference in excess of 0 dBm, a 4- element LO-phase shifting phased-array receiver with 8-phase passive mixers terminated by baseband capacitors is presented. The passive mixers upconvert both the spatial and frequency domain filtering from baseband to RF, hence realizing blocker suppression directly at the antenna inputs. A comprehensive mathematical model provides a set of closed-form equations describing the spatial and frequency domain filtering including imperfections. A prototype is realized in 28 nm CMOS. It exploits third harmonic reception to achieve a wide RF-frequency range from 0.6–4.5 GHz at 34–119 mW power dissipation, while also providing impedance matching. Out of the band/beam, a 1 dB-compression point as high as +12/+10 dBm has been measured. The 1-element noise figure over the RF-frequency range is 4–6.3 dB, while in-beam/band IIP3 values of 0– +2.6 dBm are measured. This proposed technique can be instrumental to make RF receivers more robust for interference, while still being flexibly tunable in frequency.

Adaptive Spatio-Temporal Filtering for Movement Related Potentials in EEG-Based Brain–Computer Interfaces

Abstract: Movement related potentials (MRPs) are used as features in many brain-computer interfaces (BCIs) based on electroencephalogram (EEG). MRP feature extraction is challenging since EEG is noisy and varies between subjects. Previous studies used spatial and spatio-temporal filtering methods to deal with these problems. However, they did not optimize temporal information or may have been susceptible to overfitting when training data are limited and the feature space is of high dimension. Furthermore, most of these studies manually select data windows and low-pass frequencies. We propose an adaptive spatio-temporal (AST) filtering method to model MRPs more accurately in lower dimensional space. AST automatically optimizes all parameters by employing a Gaussian kernel to construct a low-pass time-frequency filter and a linear ridge regression (LRR) algorithm to compute a spatial filter. Optimal parameters are simultaneously sought by minimizing leave-one-out cross-validation error through gradient descent. Using four BCI datasets from 12 individuals, we compare the performances of AST filter to two popular methods: the discriminant spatial pattern filter and regularized spatio-temporal filter. The results demonstrate that our AST filter can make more accurate predictions and is computationally feasible.

Effects of Approximate Filtering on the Appearance of Bidirectional Texture Functions

Abstract: The BTF data structure was a breakthrough for appearance modeling in computer graphics. More research is needed though to make BTFs practical in rendering applications. We present the first systematic study of the effects of Approximate filtering on the appearance of BTFs, by exploring the spatial, angular and temporal domains over a varied set of stimuli. We perform our initial experiments on simple geometry and lighting, and verify our observations on more complex settings. We consider multi-dimensional filtering versus conventional mipmapping, and find that multi-dimensional filtering produces superior results. We examine the tradeoff between under- and oversampling, and find that different filtering strategies can be applied in each domain, while maintaining visual equivalence with respect to a ground truth. For example, we find that preserving contrast is more important in static than dynamic images, indicating greater levels of spatial filtering are possible for animations. We find that filtering can be performed more aggressively in the angular domain than in the spatial. Additionally, we find that high-level visual descriptors of the BTF are linked to the perceptual performance of pre-filtered approximations. In turn, some of these high-level descriptors correlate with low level statistics of the BTF. We show six different practical applications of applying our findings to improving filtering, rendering and compression strategies.

Edge extraction using a time-varying vortex beam in incoherent digital holography

Abstract: Edge extraction using a time-varying vortex beam (TV-VB) is demonstrated in optical scanning holography (OSH) operating in an incoherent mode. OSH is a two-pupil heterodyne scanning optical system. We propose that one of the pupil functions used is a delta function and the other pupil function is a spiral phase plate (SPP). The interference of these pupils creates a TV-VB to scan over an object to record the edge-only information of an object holographically. We also find that a reconstructed edge with better contrast is achieved by translating the SPP away from the pupil plane. Experimental results are compared with computer simulations and found to be in good agreement.

Spatiotemporal structure of femtosecond Bessel beams from spatial light modulators

Abstract: We numerically investigate the spatiotemporal structure of Bessel beams generated with spatial light modulators (SLMs). Grating-like phase masks enable the spatial filtering of undesired diffraction orders produced by SLMs. Pulse front tilt and temporal broadening effects are investigated. In addition, we explore the influence of phase wrapping and show that the spatiotemporal structure of SLM-generated femtosecond Bessel beams is similar to Bessel X-pulses at short propagation distance and to subluminal pulsed Bessel beams at long propagation distance.

Spatial filtering by axisymmetric photonic microstructures.

Abstract: We propose and show experimentally axisymmetric spatial (angular) filtering of two-dimensional light beams by axisymmetric photonic microstructures. Such three-dimensional microstructures (similar to photonic crystals), in gapless configuration, were recorded in bulk of glass, where the refractive index has been point-by-point modulated using tightly focused femtosecond laser pulses. Axisymmetric angular filtering of approximately 25 mrad is demonstrated experimentally.

Low-Pass Filtered Volumetric Shadows.

Abstract: We present a novel and efficient method to compute volumetric soft shadows for interactive direct volume visualization to improve the perception of spatial depth. By direct control of the softness of volumetric shadows, disturbing visual patterns due to hard shadows can be avoided and users can adapt the illumination to their personal and application-specific requirements. We compute the shadowing of a point in the data set by employing spatial filtering of the optical depth over a finite area patch pointing toward each light source. Conceptually, the area patch spans a volumetric region that is sampled with shadow rays; afterward, the resulting optical depth values are convolved with a low-pass filter on the patch. In the numerical computation, however, to avoid expensive shadow ray marching, we show how to align and set up summed area tables for both directional and point light sources. Once computed, the summed area tables enable efficient evaluation of soft shadows for each point in constant time without shadow ray marching and the softness of the shadows can be controlled interactively. We integrated our method in a GPU-based volume renderer with ray casting from the camera, which offers interactive control of the transfer function, light source positions, and viewpoint, for both static and time-dependent data sets. Our results demonstrate the benefit of soft shadows for visualization to achieve user-controlled illumination with many-point lighting setups for improved perception combined with high rendering speed.

Confocal line scanning of a Bessel beam for fast 3D imaging.

Abstract: We have developed a light-sheet illumination microscope that can perform fast 3D imaging of transparent biological samples with inexpensive visible lasers and a single galvo mirror (GM). The light-sheet is created by raster scanning a Bessel beam with a GM, with this same GM also being used to rescan the fluorescence across a chip of a camera to construct an image in real time. A slit is used to reject out-of-focus fluorescence such that the image formed in real time has minimal contribution from the sidelobes of the Bessel beam. Compared with two-photon Bessel beam excitation or other confocal line-scanning approaches, our method is of lower cost, is simpler, and does not require calibration and synchronization of multiple GMs. We demonstrated the optical sectioning and out-of-focus background rejection capabilities of this microscope by imaging fluorescently labeled actin filaments in fixed 3T3 cells.

Photon pair generation and pump filtering in nonlinear adiabatic waveguiding structures

Abstract: We propose a novel integrated scheme for generation of Bell states, which allows simultaneous spatial filtering of pump photons It is achieved through spontaneous parametric down-conversion in the system of nonlinear adiabatically coupled waveguides We perform detailed analytic study of photon-pair generation in coupled waveguides and reveal the optimal conditions for the generation of each particular Bell state Furthermore, we simulate the performance of the device under realistic assumptions and show that adiabatic coupling allows us to spatially filter the pump from modal-entangled photon pairs Finally, we demonstrate that adiabatic couplers open the possibility of maintaining the purity of generated Bell states in a relatively fabrication-fault-tolerant way

A New Approach for Edge Detection

Abstract: A problem of fundamental importance in image processing is edge detection since an edge characterizes the boundaries. Edge detection filters out useless data, noise and frequencies while preserving the important structural properties in an image for further analysis and implementation. Due to limitations of the existing techniques finding a better method for edge detection is still an active area of research.. In order to augment the high-frequency components of an image in this paper we propose a new class of filter by name ‘PSS filter’ which implies a spatial filter shape with a high positive component at the centre. It is found that sharpening with PSS filter high lights some of the fine details of an image and enhances the clarity of its boundaries. Since the perception of human of image quality is not adequate some image quality metrics like Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Average Difference (AD), Normalized Absolute Error (NAE), Structural Content (SC), Normalized Cross Correlation (NCC) and Maximum Difference (MD) were employed for measurement of image quality. Experimental results show that the proposed PSS filter displayed better performance and superior noise resilience.

Tunable orbital angular momentum mode filter based on optical geometric transformation

Abstract: 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.

Adaptive spatial filtering based on region growing for automatic analysis in digital holographic microscopy

Abstract: The adaptive spatial filtering method is commonly adopted to extract the + 1 term spectrum in digital holography for real-time dynamic analysis. However, the typical filtering method is not satisfactory for automatic analysis, because the reset of the filtering window is needed to extract the area of the + 1 term spectrum. Therefore, an adaptive spatial filtering method based on region growing and the characteristic of the spectrum separation is proposed. Its filtering window is automatically formed by region growing. The key parameters, including threshold and seed point, are set by the intensity distribution of the hologram spectrum. Then the adaptive filtering extracting the + 1 term spectrum is realized by multiplying the hologram spectrum by the filtering window. Compared to the typical filtering method, the experimental results of a microhole array and a phase step show that the proposed method has better adaptability and a higher precision. Moreover, the applicability of this method for different uses is also demonstrated by experiments with a microhole array and a phase step.

Performance Comparison of Various Image Denoising Filters under Spatial Domain

Abstract: Image denoising is very important during enhancement of image. Original Image is generally corrupted with various types of noise. The noise present in the images may appear as additive or multiplicative components. The most challenging problem is removing that noise from an Image while preserving its details. Several noise removal techniques have been developed so far each having its own advantages and disadvantages. The focus of this paper is to study various spatial filters and to compare their performance in removing different types of noise. Here quantitative measure of comparison is provided by the Peak Signal to Noise Ratio (PSNR) parameter. General Terms Image Denoising, Spatial filtering.

Spatial modulation of light to determine object length

Abstract: Spatially modulated light emanating from an object moving along a flow path is used to determine various object characteristics including object length along the flow direction. Light emanating from at least one object moving along in a flow path along a flow direction of a spatial filter is sensed. The intensity of the sensed light is time modulated according to features of the spatial filter. A time varying electrical signal is generated which includes a plurality of pulses in response to the sensed light. Pulse widths of at least some of the pulses are measured at a fraction of a local extremum of the pulses. The length of the object along the flow direction is determined based on the measured pulse widths.

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

Abstract: 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.

Smoothing of spatial filter by graph Fourier transform for EEG signals

Abstract: Spatial filtering is useful for extracting features from multichannel EEG signals. In order to enhance robustness of the spatial filter against low SNR and small samples, we propose a smoothing method for the spatial filter using spectral graph theory. This method is based on an assumption that the electrodes installed in nearby locations observe the electrical activities of the same source. Therefore the spatial filter's coefficients corresponding to the nearby electrodes are supposed to be taken similar values, that is, the coefficients should be spatially smooth. To introduce the smoothness, we define a graph whose edge weights represent the physical distances between the electrodes. The spatial filter spatially smoothed is found out in the subspace that is spanned by the smooth basis of the graph Fourier transform. We evaluate the method with artificial signals and a dataset of motor imagery brain computer interface. The smoothness of the spatial filter given by the method provides robustness of the spatial filter in the condition that the small amount of the samples is available.