Engineering Commons^™

Signal Flow Graph Approach To Efficient Dst I-Iv Algorithms, Sirani M. Perera

Sirani Mututhanthrige Perera

In this paper, fast and efficient discrete sine transformation (DST) algorithms are presented based on the factorization of sparse, scaled orthogonal, rotation, rotation-reflection, and butterfly matrices. These algorithms are completely recursive and solely based on DST I-IV. The presented algorithms have low arithmetic cost compared to the known fast DST algorithms. Furthermore, the language of signal flow graph representation of digital structures is used to describe these efficient and recursive DST algorithms having (n􀀀1) points signal flow graph for DST-I and n points signal flow graphs for DST II-IV.

Retrospective Data Filter, Richard J. Prengaman, Robert E. Thurber, Joe Phipps, Ronald I. Greenberg, Wai L. Hom, James F. Jaworski, Guy W. Riffle

Ronald Greenberg

In a target detection communication system, apparatus and method for determining the presence of probable targets based on contacts (which can indicate the presence of a target, noise, chatter, or objects not of interest) detected within a predefined position sector or sectors over a specified number of scans. The position of each detected contact, as a contact of interest, is compared with the positions of contacts detected at previous times or scans. Velocity profiles indicate which previous contacts support the likelihood that the contact of interest represents a target having a velocity within a defined band. The likelihood, which can …

Recursive Robust Pca Or Recursive Sparse Recovery In Large But Structured Noise, Chenlu Qiu, Namrata Vaswani, Brian Lois, Leslie Hogben

Namrata Vaswani

This paper studies the recursive robust principal components analysis problem. If the outlier is the signal-of-interest, this problem can be interpreted as one of recursively recovering a time sequence of sparse vectors, St, in the presence of large but structured noise, Lt. The structure that we assume on Lt is that Lt is dense and lies in a low-dimensional subspace that is either fixed or changes slowly enough. A key application where this problem occurs is in video surveillance where the goal is to separate a slowly changing background (Lt) from moving foreground objects (St) on-the-fly. To solve the above …

Smart Sensing Skin For Detection And Localization Of Fatigue Cracks, Sari Kharroub, Simon Laflamme, Chunhui Song, Daji Qiao, Brent M. Phares, Jian Li

Daji Qiao

Fatigue cracks on steel components may have strong consequences on the structure's serviceability and strength. Their detection and localization is a difficult task. Existing technologies enabling structural health monitoring have a complex link signal-to-damage or have economic barriers impeding large-scale deployment. A solution is to develop sensing methods that are inexpensive, scalable, with signals that can directly relate to damage. The authors have recently proposed a smart sensing skin for structural health monitoring applications to mesosystems. The sensor is a thin film soft elastomeric capacitor (SEC) that transduces strain into a measurable change in capacitance. Arranged in a network configuration, …

Overlay Protection Against Link Failures Using Network Coding, Ahmed Kamal, Aditya Ramamoorthy, Long Long, Shizheng Li

Ahmed Kamal

This paper introduces a network coding-based protection scheme against single and multiple link failures. The proposed strategy ensures that in a connection, each node receives two copies of the same data unit: one copy on the working circuit, and a second copy that can be extracted from linear combinations of data units transmitted on a shared protection path. This guarantees instantaneous recovery of data units upon the failure of a working circuit. The strategy can be implemented at an overlay layer, which makes its deployment simple and scalable. While the proposed strategy is similar in spirit to the work of …

Gaussian Nonlinear Line Attractor For Learning Multidimensional Data, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla

Vijayan K. Asari

The human brain’s ability to extract information from multidimensional data modeled by the Nonlinear Line Attractor (NLA), where nodes are connected by polynomial weight sets. Neuron connections in this architecture assumes complete connectivity with all other neurons, thus creating a huge web of connections. We envision that each neuron should be connected to a group of surrounding neurons with weighted connection strengths that reduces with proximity to the neuron. To develop the weighted NLA architecture, we use a Gaussian weighting strategy to model the proximity, which will also reduce the computation times significantly. Once all data has been trained in …

Brain Machine Interface Using Emotiv Epoc To Control Robai Cyton Robotic Arm, Daniel P. Prince, Mark J. Edmonds, Andrew J. Sutter, Matthew Thomas Cusumano, Wenjie Lu, Vijayan K. Asari

Vijayan K. Asari

The initial framework for an electroencephalography (EEG) thought recognition software suite is developed, built, and tested. This suite is designed to recognize human thoughts and pair them to actions for controlling a robotic arm. Raw EEG brain activity data is collected using an Emotiv EPOC headset. The EEG data is processed through linear discriminant analysis (LDA), where an intended action is identified. The EEG classification suite is being developed to increase the number of distinct actions that can be identified compared to the Emotiv recognition software. The EEG classifier was able to correctly distinguish between two separate physical movements. Future …

Digital Image Processing, Russell C. Hardie, Majeed M. Hayat

Russell C. Hardie

In recent years, digital images and digital image processing have become part of everyday life. This growth has been primarily fueled by advances in digital computers and the advent and growth of the Internet. Furthermore, commercially available digital cameras, scanners, and other equipment for acquiring, storing, and displaying digital imagery have become very inexpensive and increasingly powerful. An excellent treatment of digital images and digital image processing can be found in Ref. [1]. A digital image is simply a two-dimensional array of finite-precision numerical values called picture elements (or pixels). Thus a digital image is a spatially discrete (or discrete-space) …

Spatio-Spectral Sampling And Color Filter Array Design, Keigo Hirakawa, Patrick Wolfe

Keigo Hirakawa

Owing to the growing ubiquity of digital image acquisition and display, several factors must be considered when developing systems to meet future color image processing needs, including improved quality, increased throughput, and greater cost-effectiveness. In consumer still-camera and video applications, color images are typically obtained via a spatial subsampling procedure implemented as a color filter array (CFA), a physical construction whereby only a single component of the color space is measured at each pixel location. Substantial work in both industry and academia has been dedicated to post-processing this acquired raw image data as part of the so-called image processing pipeline, …

Development Of Compressive Sensing Techniques For Wideband Spectrum Scanning In Cognitive Radio Networks, Fatima Salahdine, Naima Kaabouch, Hassan El Ghazi

fatima salahdine

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 …