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Articles 1 - 30 of 46
Full-Text Articles in Engineering
Projected Nesterov’S Proximal-Gradient Signal Recovery From Compressive Poisson Measurements, Renliang Gu, Aleksandar Dogandžić
Projected Nesterov’S Proximal-Gradient Signal Recovery From Compressive Poisson Measurements, Renliang Gu, Aleksandar Dogandžić
Aleksandar Dogandžić
We develop a projected Nesterov’s proximal-gradient (PNPG) scheme for reconstructing sparse signals from compressive Poisson-distributed measurements with the mean signal intensity that follows an affine model with known intercept. The objective function to be minimized is a sum of convex data fidelity (negative log-likelihood (NLL)) and regularization terms. We apply sparse signal regularization where the signal belongs to a nonempty closed convex set within the domain of the NLL and signal sparsity is imposed using total-variation (TV) penalty. We present analytical upper bounds on the regularization tuning constant. The proposed PNPG method employs projected Nesterov’s acceleration step, function restart, and …
Speaker Dependent Voice Recognition Using Discrete Wavelet Transform, Angelo A. Beltran Jr., Ericson D. Dimaunahan, Donde A. Deveras
Speaker Dependent Voice Recognition Using Discrete Wavelet Transform, Angelo A. Beltran Jr., Ericson D. Dimaunahan, Donde A. Deveras
Innovative Research Publications IRP India
This paper presents effective and robust method for the extracting of features in the speaker dependent voice recognition. Based on the time-frequency multi-resolution property of wavelet transform, the input speech signal is decomposed into various frequency channels. The major issues concerning the design in this paper for wavelet based speaker voice recognition system are choosing the optimal wavelets for the speech signals, decomposition level in the discrete wavelet transform, and selecting the feature vectors from the wavelet coefficients. And finally, the wavelet-based voice recognition system and its performance are discussed and highlighted.
Conversion Of English Text-To-Speech (Tts) Using Indian Speech Signal, R. Shantha Selva Kumari, R. Sangeetha
Conversion Of English Text-To-Speech (Tts) Using Indian Speech Signal, R. Shantha Selva Kumari, R. Sangeetha
Innovative Research Publications IRP India
The objective of this paper is to convert the english text into speech. The conversion of english text into speech is done by using a stored speech signal data. Text to speech conversion module is designed by the use of matlab. By the use of microphone the phonemes (alphabets, numbers, words) are recorded using a goldwave software. The recorded .wav (sounds) files are saved as a database separately. The phonemes are extracted from the text file. For text to speech conversion the concatenation method is proposed. The recorded speech are concatenated together to produce the synthesized speech. The resulting speech …
Parallel Computation In Communication And Signal Processing, Amean Al_Safi, Bradley Bazuin, Liqaa Alhafadhi
Parallel Computation In Communication And Signal Processing, Amean Al_Safi, Bradley Bazuin, Liqaa Alhafadhi
Amean S Al_Safi
The powerful computation of GPU has increased the computation speed up of many systems. This paper summarize some of the most important work in the field of communication and signal processing using GPU
Review Of Emg-Based Speech Recognition, Amean Al_Safi, Liqaa Alhafadhi
Review Of Emg-Based Speech Recognition, Amean Al_Safi, Liqaa Alhafadhi
Amean S Al_Safi
This study represents a review of the main studies in EMG-based speech recognition. Its main goal is to support the researchers in the biomedical field with a survey of the solved and unsolved problem in the direction since it has received a great attention during last decade due to its promise applications such as underwater communication and silent speech recognition. Hence this study is a very good starting point for the researchers interested in this area of research
Gradient-Based Edge Detection Using Nonlinear Edge-Enhancing Prefilters, Russell Hardie, Charles Boncelet
Gradient-Based Edge Detection Using Nonlinear Edge-Enhancing Prefilters, Russell Hardie, Charles Boncelet
Russell C. Hardie
This correspondence examines the use of nonlinear edge enhancers as prefilters for edge detectors. The filters are able to convert smooth edges to step edges and suppress noise simultaneously. Thus, false alarms due to noise are minimized and edge gradient estimates tend to be large and localized. This leads to significantly improved edge maps.
Ranking In Rp And Its Use In Multivariate Image Estimation, Russell Hardie, Gonzalo Arce
Ranking In Rp And Its Use In Multivariate Image Estimation, Russell Hardie, Gonzalo Arce
Russell C. Hardie
The extension of ranking a set of elements in R to ranking a set of vectors in a p'th dimensional space Rp is considered. In the approach presented here vector ranking reduces to ordering vectors according to a sorted list of vector distances. A statistical analysis of this vector ranking is presented, and these vector ranking concepts are then used to develop ranked-order type estimators for multivariate image fields. A class of vector filters is developed, which are efficient smoothers in additive noise and can be designed to have detail-preserving characteristics. A statistical analysis is developed for the class of …
Lum Filters: A Class Of Rank-Order-Based Filters For Smoothing And Sharpening, Russell Hardie, Charles Boncelet
Lum Filters: A Class Of Rank-Order-Based Filters For Smoothing And Sharpening, Russell Hardie, Charles Boncelet
Russell C. Hardie
A new class of rank-order-based filters, called lower-upper-middle (LUM) filters, is introduced. The output of these filters is determined by comparing a lower- and an upper-order statistic to the middle sample in the filter window. These filters can be designed for smoothing and sharpening, or outlier rejection. The level of smoothing done by the filter can range from no smoothing to that of the medianfilter. This flexibility allows the LUM filter to be designed to best balance the tradeoffs between noisesmoothing and signal detail preservation. LUM filters for enhancing edge gradients can be designed to be insensitive to low levels …
Spectral Band Selection And Classifier Design For A Multispectral Imaging Laser Radar, Russell Hardie, Mohan Vaidyanathan, Paul Mcmanamon
Spectral Band Selection And Classifier Design For A Multispectral Imaging Laser Radar, Russell Hardie, Mohan Vaidyanathan, Paul Mcmanamon
Russell C. Hardie
A statistical spectral band selection procedure and classifiers for an active multispectral laser radar (LADAR) sensor are described. The sensor will operate in the 1 to 5 mm wavelength region. The algorithms proposed are tested using library reflectance spectra for some representative background materials. The material classes considered include both natural (vegetation and soil) and man-made (camouflage cloth and tar-asphalt). The analysis includes noise statistics due to Gaussian receiver noise and target induced speckle variations in the LADAR return signal intensity. The results of this analysis are then directly applied to an artificially generated spatial template of a scene consisting …
Super-Resolution Using Adaptive Wiener Filters, Russell C. Hardie
Super-Resolution Using Adaptive Wiener Filters, Russell C. Hardie
Russell C. Hardie
The spatial sampling rate of an imaging system is determined by the spacing of the detectors in the focal plane array (FPA). The spatial frequencies present in the image on the focal plane are band-limited by the optics. This is due to diffraction through a finite aperture. To guarantee that there will be no aliasing during image acquisiton, the Nyquist criterion dictates that the sampling rate must be greater than twice the cut-off frequency of the optics. However, optical designs involve a number of trade-offs and typical imaging systems are designed with some level of aliasing. We will refer to …
Hybrid Order Statistic Filter And Its Application To Image Restoration, Elizabeth Thompson, Russell Hardie, Kenneth Barner
Hybrid Order Statistic Filter And Its Application To Image Restoration, Elizabeth Thompson, Russell Hardie, Kenneth Barner
Russell C. Hardie
We introduce a new nonlinear filter for signal and image restoration, the hybrid order statistic (HOS) filter. Because it exploits both rank- and spatial-order information, the HOS realizes the advantages of nonlinear filters in edge preservation and reduction of impulsive noise components while retaining the ability of the linear filter to suppress Gaussian noise. We show that the HOS filter exhibits improved performance over both the linear Wiener and the nonlinear L filters in reducing mean-squared error in the presence of contaminated Gaussian noise. In many cases it also performs favorably compared with the Ll and rank-conditioned rank selection filters.
Application Of Multi-Frame High-Resolution Image Reconstruction To Digital Microscopy, Frank Baxley, Russell Hardie
Application Of Multi-Frame High-Resolution Image Reconstruction To Digital Microscopy, Frank Baxley, Russell Hardie
Russell C. Hardie
A high-resolution image reconstruction algorithm previously used to improve undersampled infrared airborne imagery was applied to two different sets of digital microscopy images. One set is that of medical pap smear images, and the second set contains metallurgical micrographs. Both the pap smear images and the metallurgical micrographs are undersampled, thus causing loss of detail and aliasing artifacts. The algorithm minimizes the effects of aliasing and restores detail unobtainable through simple interpolation techniques. Both applications demonstrate improvement by use of the image reconstruction algorithm.
Robust Phase-Unwrapping Algorithm Using A Spatial Binary-Tree Image Decomposition, Russell Hardie, Md. Younus, James Blackshire
Robust Phase-Unwrapping Algorithm Using A Spatial Binary-Tree Image Decomposition, Russell Hardie, Md. Younus, James Blackshire
Russell C. Hardie
The search for fast and robust phase-unwrapping algorithms remains an important problem in the development of real-time interferometric systems. Our phase-unwrapping approach uses a spatial binary-tree image decomposition to permit maximum parallelism in implementation. At each node in the tree structure, a single unwrapping decision is made between two image blocks. The unwrapping rule is derived from a statistical-estimation framework. Specifically, a maximum-likelihood estimate of the demodulation term is used. This term can be viewed as that which minimizes a discontinuity-penalizing cost function. We show that the algorithm exhibits a high level of robustness. Quantitative measures of performance are provided, …
Scene-Based Nonuniformity Correction With Video Sequences And Registration, Russell Hardie, Majeed Hayat, Ernest Armstrong, Brian Yasuda
Scene-Based Nonuniformity Correction With Video Sequences And Registration, Russell Hardie, Majeed Hayat, Ernest Armstrong, Brian Yasuda
Russell C. Hardie
We describe a new, to our knowledge, scene-based nonuniformity correction algorithm for array detectors. The algorithm relies on the ability to register a sequence of observed frames in the presence of the fixed-pattern noise caused by pixel-to-pixel nonuniformity. In low-to-moderate levels of nonuniformity, sufficiently accurate registration may be possible with standard scene-based registration techniques. If the registration is accurate, and motion exists between the frames, then groups of independent detectors can be identified that observe the same irradiance ~or true scene value!. These detector outputs are averaged to generate estimates of the true scene values. With these scene estimates, and …
Techniques For The Regeneration Of Wideband Speech From Narrowband Speech, Jason A. Fuemmeler, Russell C. Hardie, William R. Gardner
Techniques For The Regeneration Of Wideband Speech From Narrowband Speech, Jason A. Fuemmeler, Russell C. Hardie, William R. Gardner
Russell C. Hardie
This paper addresses the problem of reconstructing wideband speech signals from observed narrowband speech signals. The goal of this work is to improve the perceived quality of speech signals which have been transmitted through narrowband channels or degraded during acquisition. We describe a system, based on linear predictive coding, for estimating wideband speech from narrowband. This system employs both previously identified and novel techniques. Experimental results are provided in order to illustrate the system’s ability to improve speech quality. Both objective and subjective criteria are used to evaluate the quality of the processed speech signals.
A Post-Processing Technique For Extending Depth Of Focus In Conventional Optical Microscopy, Taufiq Widjanarko, Russell Hardie
A Post-Processing Technique For Extending Depth Of Focus In Conventional Optical Microscopy, Taufiq Widjanarko, Russell Hardie
Russell C. Hardie
In this paper, we propose a post-processing technique to obtain optical microscope images with extended depth of focus using a conventional microscope. With the proposed technique, we collect a sequence of images focused at different depths. We then combine the in-focus regions of each acquired frame to compose a single all-in-focus image. That is, a new image with extended depth of focus is obtained. The key to such an algorithm is in selecting the “in-focus” regions from each frame. In this paper, we describe the technique used to identify the in-focus region on every depth slice. Quantitative simulation results are …
Application Of The Stochastic Mixing Model To Hyperspectral Resolution Enhancement, Michael Eismann, Russell Hardie
Application Of The Stochastic Mixing Model To Hyperspectral Resolution Enhancement, Michael Eismann, Russell Hardie
Russell C. Hardie
A maximum a posteriori (MAP) estimation method is described for enhancing the spatial resolution of a hyperspectral image using a higher resolution coincident panchromatic image. The approach makes use of a stochastic mixing model (SMM) of the underlying spectral scene content to develop a cost function that simultaneously optimizes the estimated hyperspectral scene relative to the observed hyperspectral and panchromatic imagery, as well as the local statistics of the spectral mixing model. The incorporation of the stochastic mixing model is found to be the key ingredient for reconstructing subpixel spectral information in that it provides the necessary constraints that lead …
An Algebraic Algorithm For Nonuniformity Correction In Focal-Plane Arrays, Bradley Ratliff, Majeed Hayat, Russell Hardie
An Algebraic Algorithm For Nonuniformity Correction In Focal-Plane Arrays, Bradley Ratliff, Majeed Hayat, Russell Hardie
Russell C. Hardie
A scene-based algorithm is developed to compensate for bias nonuniformity in focal-plane arrays. Nonuniformity can be extremely problematic, especially for mid- to far-infrared imaging systems. The technique is based on use of estimates of interframe subpixel shifts in an image sequence, in conjunction with a linear-interpolation model for the motion, to extract information on the bias nonuniformity algebraically. The performance of the proposed algorithm is analyzed by using real infrared and simulated data. One advantage of this technique is its simplicity; it requires relatively few frames to generate an effective correction matrix, thereby permitting the execution of frequent on-the-fly nonuniformity …
Subspace Partition Weighted Sum Filters For Image Restoration, Yong Lin, Russell Hardie, Kenneth Barner
Subspace Partition Weighted Sum Filters For Image Restoration, Yong Lin, Russell Hardie, Kenneth Barner
Russell C. Hardie
The previously proposed partition-based weighted sum (PWS) filters combine vector quantization (VQ) and linear finite impulse response (FIR) Wiener filtering concepts. By partitioning the observation space and applying a tuned Wiener filter to each partition, the PWS is spatially adaptive and has been shown to perform well in noise reduction applications. In this letter, we propose the subspace PWS (SPWS) filter and evaluate the efficacy of the SPWS filter in image deconvolution and noise reduction applications. In the SPWS filter, we project the observation vectors into a subspace using principal component analysis (PCA), or other methods, prior to partitioning. This …
A Fast Image Super-Resolution Algorithm Using An Adaptive Wiener Filter, Russell C. Hardie
A Fast Image Super-Resolution Algorithm Using An Adaptive Wiener Filter, Russell C. Hardie
Russell C. Hardie
A computationally simple super-resolution algorithm using a type of adaptive Wiener filter is proposed. The algorithm produces an improved resolution image from a sequence of low-resolution (LR) video frames with overlapping field of view. The algorithm uses subpixel registration to position each LR pixel value on a common spatial grid that is referenced to the average position of the input frames. The positions of the LR pixels are not quantized to a finite grid as with some previous techniques. The output high-resolution (HR) pixels are obtained using a weighted sum of LR pixels in a local moving window. Using a …
Hyperspectral Resolution Enhancement Using High-Resolution Multispectral Imagery With Arbitrary Response Functions, Michael Eismann, Russell Hardie
Hyperspectral Resolution Enhancement Using High-Resolution Multispectral Imagery With Arbitrary Response Functions, Michael Eismann, Russell Hardie
Russell C. Hardie
A maximum a posteriori (MAP) estimation method for improving the spatial resolution of a hyperspectral image using a higher resolution auxiliary image is extended to address several practical remote sensing situations. These include cases where: 1) the spectral response of the auxiliary image is unknown and does not match that of the hyperspectral image; 2) the auxiliary image is multispectral; and 3) the spatial point spread function for the hyperspectral sensor is arbitrary and extends beyond the span of the detector elements. The research presented follows a previously reported MAP approach that makes use of a stochastic mixing model (SMM) …
Improved Optimization Of Soft Partition Weighted Sum Filters And Their Application To Image Restoration, Yong Lin, Russell Hardie, Qin Sheng, Kenneth Barner
Improved Optimization Of Soft Partition Weighted Sum Filters And Their Application To Image Restoration, Yong Lin, Russell Hardie, Qin Sheng, Kenneth Barner
Russell C. Hardie
Soft-partition-weighted-sum (Soft-PWS) filters are a class of spatially adaptive moving-window filters for signal and image restoration. Their performance is shown to be promising. However, optimization of the Soft-PWS filters has received only limited attention. Earlier work focused on a stochastic-gradient method that is computationally prohibitive in many applications. We describe a novel radial basis function interpretation of the Soft-PWS filters and present an efficient optimization procedure. We apply the filters to the problem of noise reduction. The experimental results show that the Soft-PWS filter outperforms the standard partition-weighted-sum filter and the Wiener filter.
Scene-Based Nonuniformity Correction With Reduced Ghosting Using A Gated Lms Algorithm, Russell C. Hardie, Frank Orion Baxley, Brandon J. Brys, Patrick C. Hytla
Scene-Based Nonuniformity Correction With Reduced Ghosting Using A Gated Lms Algorithm, Russell C. Hardie, Frank Orion Baxley, Brandon J. Brys, Patrick C. Hytla
Russell C. Hardie
In this paper, we present a scene-based nouniformity correction (NUC) method using a modified adaptive least mean square (LMS) algorithm with a novel gating operation on the updates. The gating is designed to significantly reduce ghosting artifacts produced by many scene-based NUC algorithms by halting updates when temporal variation is lacking. We define the algorithm and present a number of experimental results to demonstrate the efficacy of the proposed method in comparison to several previously published methods including other LMS and constant statistics based methods. The experimental results include simulated imagery and a real infrared image sequence. We show that …
Super-Resolution For Imagery From Integrated Microgrid Polarimeters, Russell C. Hardie, Daniel A. Lemaster, Bradley Michael Ratliff
Super-Resolution For Imagery From Integrated Microgrid Polarimeters, Russell C. Hardie, Daniel A. Lemaster, Bradley Michael Ratliff
Russell C. Hardie
Imagery from microgrid polarimeters is obtained by using a mosaic of pixel-wise micropolarizers on a focal plane array (FPA). Each distinct polarization image is obtained by subsampling the full FPA image. Thus, the effective pixel pitch for each polarization channel is increased and the sampling frequency is decreased. As a result, aliasing artifacts from such undersampling can corrupt the true polarization content of the scene. Here we present the first multi-channel multi-frame super-resolution (SR) algorithms designed specifically for the problem of image restoration in microgrid polarization imagers. These SR algorithms can be used to address aliasing and other degradations, without …
Joint Wavelet Transform Correlation With Separated Target And Reference Planes, Boon Yi Soon, Mohammad A. Karim, Russell C. Hardie, Mohammad S. Alam
Joint Wavelet Transform Correlation With Separated Target And Reference Planes, Boon Yi Soon, Mohammad A. Karim, Russell C. Hardie, Mohammad S. Alam
Russell C. Hardie
In recent years, we realize the usefulness of feature extraction for optical correlator and hereby, we investigate the capability of Laplace operator in feature extraction of multiple targets. The first-order terms and the false alarm terms in the correlation output would be removed using electronic power spectrum subtraction technique. Most importantly, the entire magneto-optic SLM is completely utilized for displaying only targets in the input scene. A new cost efficient hardware implementation is proposed and aforementioned result of the proposed system is evaluated through computer simulation.
Assessment Of The Impact Of Clothing And Environmental Conditions On Visible Light 3d Scanning, Pann Ajjimaporn, Jeremy Straub, Scott Kerlin
Assessment Of The Impact Of Clothing And Environmental Conditions On Visible Light 3d Scanning, Pann Ajjimaporn, Jeremy Straub, Scott Kerlin
Jeremy Straub
The quality of models produced by visible light 3D scanners is influenced by multiple factors. To max-imize model accuracy and detail levels, the correct combination of lighting texture, subject posture and software usage must be selected. The work described herein has been performed to measure the effect of different lighting and envi-ronmental conditions on human 3D scanning results.
Small Satellite Communication System Creation At The University Of North Dakota, Michael Hlas, Jeremy Straub, Ronald Marsh
Small Satellite Communication System Creation At The University Of North Dakota, Michael Hlas, Jeremy Straub, Ronald Marsh
Jeremy Straub
Software defined radios (SDRs) are poised to significantly enhance the future of small spacecraft communications. They allow signal processing to be performed on a computer by software rather than requiring dedicated hardware. The OpenOrbiter SDR (discussed in [1] and refined in [2]) takes data from the flight computer and converts it into an analog signal that is transmitted via the spacecraft antenna. Because the signal processing is done in software, the radio can be easily reconfigured. This process is done in reverse for incoming transmissions, which are received by the SDR and decoded by software. Figures 1 and 2 provide …
Crowdsourced Earthquake Early Warning, Sarah Minson, Benjamin Brooks, Craig Glennie, Jessica Murray, John Langbein, Susan Owen, Thomas Heaton, Robert Iannucci, Darren Hauser
Crowdsourced Earthquake Early Warning, Sarah Minson, Benjamin Brooks, Craig Glennie, Jessica Murray, John Langbein, Susan Owen, Thomas Heaton, Robert Iannucci, Darren Hauser
Robert A Iannucci
Earthquake early warning (EEW) can reduce harm to people and infrastructure from earthquakes and tsunamis, but it has not been implemented in most high earthquake-risk regions because of prohibitive cost. Common consumer devices such as smartphones contain low-cost versions of the sensors used in EEW. Although less accurate than scientific-grade instruments, these sensors are globally ubiquitous. Through controlled tests of consumer devices, simulation of an Mw (moment magnitude) 7 earthquake on California’s Hayward fault, and real data from the Mw 9 Tohoku-oki earthquake, we demonstrate that EEW could be achieved via crowdsourcing.
Partition-Based Interpolation For Color Filter Array Demosaicking And Super-Resolution Reconstruction, Min Shao, Kenneth E. Barner, Russell C. Hardie
Partition-Based Interpolation For Color Filter Array Demosaicking And Super-Resolution Reconstruction, Min Shao, Kenneth E. Barner, Russell C. Hardie
Russell C. Hardie
A class of partition-based interpolators that addresses a variety of image interpolation applications are proposed. The proposed interpolators first partition an image into a finite set of partitions that capture local image structures. Missing high resolution pixels are then obtained through linear operations on neighboring pixels that exploit the captured image structure. By exploiting the local image structure, the proposed algorithm produces excellent performance on both edge and uniform regions. The presented results demonstrate that partition-based interpolation yields results superior to traditional and advanced algorithms in the applications of color filter array (CFA) demosaicking and super-resolution reconstruction.
A Map Estimator For Simultaneous Superresolution And Detector Nonunifomity Correct, Russell Hardie, Douglas Droege
A Map Estimator For Simultaneous Superresolution And Detector Nonunifomity Correct, Russell Hardie, Douglas Droege
Russell C. Hardie
During digital video acquisition, imagery may be degraded by a number of phenomena including undersampling, blur, and noise. Many systems, particularly those containing infrared focal plane array (FPA) sensors, are also subject to detector nonuniformity. Nonuniformity, or fixed pattern noise, results from nonuniform responsivity of the photodetectors that make up the FPA. Here we propose a maximuma posteriori (MAP) estimation framework for simultaneously addressing undersampling, linear blur, additive noise, and bias nonuniformity. In particular, we jointly estimate a superresolution (SR) image and detector bias nonuniformity parameters from a sequence of observed frames. This algorithm can be applied to video in …