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At least 181 records · Page 10

Scan-Based Implementation of JPEG 2000 Extensions

JPEG 2000 Part 2 (Extensions) contains a number of technologies that are of potential interest in remote sensing applications. These include arbitrary wavelet transforms, techniques to limit boundary artifacts in tiles, multiple component transforms, and trellis-coded quantization (TCQ). We are investigating the addition of these features to the low-memory (scan-based) implementation of JPEG 2000 Part 1. A scan-based implementation of TCQ has been realized and tested, with a very small performance loss as compared with the full image (frame-based) version. A proposed amendment to JPEG 2000 Part 2 will effect the syntax changes required to make scan-based TCQ compatible with the standard.

Rountree, Janet C.↗

A Foreign Object Damage Event Detector Data Fusion System for Turbofan Engines

A Data Fusion System designed to provide a reliable assessment of the occurrence of Foreign Object Damage (FOD) in a turbofan engine is presented. The FOD-event feature level fusion scheme combines knowledge of shifts in engine gas path performance obtained using a Kalman filter, with bearing accelerometer signal features extracted via wavelet analysis, to positively identify a FOD event. A fuzzy inference system provides basic probability assignments (bpa) based on features extracted from the gas path analysis and bearing accelerometers to a fusion algorithm based on the Dempster-Shafer-Yager Theory of Evidence. Details are provided on the wavelet transforms used to extract the foreign object strike features from the noisy data and on the Kalman filter-based gas path analysis. The system is demonstrated using a turbofan engine combined-effects model (CEM), providing both gas path and rotor dynamic structural response, and is suitable for rapid-prototyping of control and diagnostic systems. The fusion of the disparate data can provide significantly more reliable detection of a FOD event than the use of either method alone. The use of fuzzy inference techniques combined with Dempster-Shafer-Yager Theory of Evidence provides a theoretical justification for drawing conclusions based on imprecise or incomplete data.

Turso, James A.↗

Oscillatory Hierarchy Controlling Cortical Excitability and Stimulus Integration

Cortical gamma band oscillations have been recorded in sensory cortices of cats and monkeys, and are thought to aid in perceptual binding. Gamma activity has also been recorded in the rat hippocampus and entorhinal cortex, where it has been shown, that field gamma power is modulated at theta frequency. Since the power of gamma activity in the sensory cortices is not constant (gamma-bursts). we decided to examine the relationship between gamma power and the phase of low frequency oscillation in the auditory cortex of the awake macaque. Macaque monkeys were surgically prepared for chronic awake electrophysiological recording. During the time of the experiments. linear array multielectrodes were inserted in area AI to obtain laminar current source density (CSD) and multiunit activity profiles. Instantaneous theta and gamma power and phase was extracted by applying the Morlet wavelet transformation to the CSD. Gamma power was averaged for every 1 degree of low frequency oscillations to calculate power-phase relation. Both gamma and theta-delta power are largest in the supragranular layers. Power modulation of gamma activity is phase locked to spontaneous, as well as stimulus-related local theta and delta field oscillations. Our analysis also revealed that the power of theta oscillations is always largest at a certain phase of delta oscillation. Auditory stimuli produce evoked responses in the theta band (Le., there is pre- to post-stimulus addition of theta power), but there is also indication that stimuli may cause partial phase re-setting of spontaneous delta (and thus also theta and gamma) oscillations. We also show that spontaneous oscillations might play a role in the processing of incoming sensory signals by 'preparing' the cortex.

Shah, A. S.↗

ICER-3D: A Progressive Wavelet-Based Compressor for Hyperspectral Images

ICER-3D is a progressive, wavelet-based compressor for hyperspectral images. ICER-3D is derived from the ICER image compressor. ICER-3D can provide lossless and lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The three-dimensional wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of hyperspectral data sets, while facilitating elimination of spectral ringing artifacts. Correlation is further exploited by a context modeler that effectively exploits spectral dependencies in the wavelet-transformed hyperspectral data. Performance results illustrating the benefits of these features are presented.

Kiely, A.↗

Characteristic Lifelength of Coherent Structure in the Turbulent Boundary Layer

A characteristic lifelength is defined by which a Gaussian distribution is fit to data correlated over a 3 sensor array sampling streamwise sidewall pressure. The data were acquired at subsonic, transonic and supersonic speeds aboard a Tu-144. Lifelengths are estimated using the cross spectrum and are shown to compare favorably with Efimtsov's prediction of correlation space scales. Lifelength distributions are computed in the time/frequency domain using an interval correlation technique on the continuous wavelet transform of the original time data. The median values of the lifelength distributions are found to be very close to the frequency averaged result. The interval correlation technique is shown to allow the retrieval and inspection of the original time data of each event in the lifelength distribution, thus providing a means to locate and study the nature of the coherent structure in the turbulent boundary layer. The lifelength data can be converted to lifetimes using the convection velocity. The lifetime of events in the time/frequency domain are displayed in Lifetime Maps. The primary purpose of the paper is to validate these new analysis techniques so that they can be used with confidence to further characterize coherent structure in the turbulent boundary layer.

Palumbo, Daniel L.↗

(abstract) An All Sky Cirrus Confusion Noise Map for WIRE

The Wide Field Infrared Explorer (WIRE) is a Small Explorer (SMEX) satellite scheduled for launch in 1998 which will carry out a sky survey of at least 100 square degrees in the wavelength regions of 9-15(micro)m and 21-27(micro)m with spatial resolution of approximately 20 arcsec and sensitivity exceeding 0.6mJy. At this sensitivity level WIRE observations can be seriously affected by the confusion noise contribution from the infrared cirrus emission, so the WIRE survey must be planned with some knowledge of the expected level of cirrus confusion. Production of a cirrus confusion noise map with 0.5 degree resolution based on the spatial power spectral density of the cirrus emission in the IRAS ISSA data is in progess using the method described by Gauthier, et al. Spectrally resolved power spectra density data is obtained from the ISSA maps with a wavelet transform technique.

Wide Field Infrared Explorer WIRE infrared sky sur↗

Deriving Lifetime Maps in the Time/Frequency Domain of Coherent Structures in the Turbulent Boundary Layer

The lifetimes of coherent structures are derived from data correlated over a 3 sensor array sampling streamwise sidewall pressure at high Reynolds number (> 10(exp 8)). The data were acquired at subsonic, transonic and supersonic speeds aboard a Tupolev Tu-144. The lifetimes are computed from a variant of the correlation length termed the lifelength. Characteristic lifelengths are estimated by fitting a Gaussian distribution to the sensors cross spectra and are shown to compare favorably with Efimtsov s prediction of correlation space scales. Lifelength distributions are computed in the time/frequency domain using an interval correlation technique on the continuous wavelet transform of the original time data. The median values of the lifelength distributions are found to be very close to the frequency averaged result. The interval correlation technique is shown to allow the retrieval and inspection of the original time data of each event in the lifelength distributions, thus providing a means to locate and study the nature of the coherent structure in the turbulent boundary layer. The lifelength data are converted to lifetimes using the convection velocity. The lifetime of events in the time/frequency domain are displayed in Lifetime Maps. The primary purpose of the paper is to validate these new analysis techniques so that they can be used with confidence to further characterize the behavior of coherent structures in the turbulent boundary layer.

Palumbo, Dan↗

Pattern-Recognition System for Approaching a Known Target

A closed-loop pattern-recognition system is designed to provide guidance for maneuvering a small exploratory robotic vehicle (rover) on Mars to return to a landed spacecraft to deliver soil and rock samples that the spacecraft would subsequently bring back to Earth. The system could be adapted to terrestrial use in guiding mobile robots to approach known structures that humans could not approach safely, for such purposes as reconnaissance in military or law-enforcement applications, terrestrial scientific exploration, and removal of explosive or other hazardous items. The system has been demonstrated in experiments in which the Field Integrated Design and Operations (FIDO) rover (a prototype Mars rover equipped with a video camera for guidance) is made to return to a mockup of Mars-lander spacecraft. The FIDO rover camera autonomously acquires an image of the lander from a distance of 125 m in an outdoor environment. Then under guidance by an algorithm that performs fusion of multiple line and texture features in digitized images acquired by the camera, the rover traverses the intervening terrain, using features derived from images of the lander truss structure. Then by use of precise pattern matching for determining the position and orientation of the rover relative to the lander, the rover aligns itself with the bottom of ramps extending from the lander, in preparation for climbing the ramps to deliver samples to the lander. The most innovative aspect of the system is a set of pattern-recognition algorithms that govern a three-phase visual-guidance sequence for approaching the lander. During the first phase, a multifeature fusion algorithm integrates the outputs of a horizontal-line-detection algorithm and a wavelet-transform-based visual-area-of-interest algorithm for detecting the lander from a significant distance. The horizontal-line-detection algorithm is used to determine candidate lander locations based on detection of a horizontal deck that is part of the lander.

Huntsberger, Terrance↗

Image Compression Algorithm Altered to Improve Stereo Ranging

A report discusses a modification of the ICER image-data-compression algorithm to increase the accuracy of ranging computations performed on compressed stereoscopic image pairs captured by cameras aboard the Mars Exploration Rovers. (ICER and variants thereof were discussed in several prior NASA Tech Briefs articles.) Like many image compressors, ICER was designed to minimize a mean-square-error measure of distortion in reconstructed images as a function of the compressed data volume. The present modification of ICER was preceded by formulation of an alternative error measure, an image-quality metric that focuses on stereoscopic-ranging quality and takes account of image-processing steps in the stereoscopic-ranging process. This metric was used in empirical evaluation of bit planes of wavelet-transform subbands that are generated in ICER. The present modification, which is a change in a bit-plane prioritization rule in ICER, was adopted on the basis of this evaluation. This modification changes the order in which image data are encoded, such that when ICER is used for lossy compression, better stereoscopic-ranging results are obtained as a function of the compressed data volume.

Kiely, Aaron↗

Reconfigurable Hardware for Compressing Hyperspectral Image Data

High-speed, low-power, reconfigurable electronic hardware has been developed to implement ICER-3D, an algorithm for compressing hyperspectral-image data. The algorithm and parts thereof have been the topics of several NASA Tech Briefs articles, including Context Modeler for Wavelet Compression of Hyperspectral Images (NPO-43239) and ICER-3D Hyperspectral Image Compression Software (NPO-43238), which appear elsewhere in this issue of NASA Tech Briefs. As described in more detail in those articles, the algorithm includes three main subalgorithms: one for computing wavelet transforms, one for context modeling, and one for entropy encoding. For the purpose of designing the hardware, these subalgorithms are treated as modules to be implemented efficiently in field-programmable gate arrays (FPGAs). The design takes advantage of industry- standard, commercially available FPGAs. The implementation targets the Xilinx Virtex II pro architecture, which has embedded PowerPC processor cores with flexible on-chip bus architecture. It incorporates an efficient parallel and pipelined architecture to compress the three-dimensional image data. The design provides for internal buffering to minimize intensive input/output operations while making efficient use of offchip memory. The design is scalable in that the subalgorithms are implemented as independent hardware modules that can be combined in parallel to increase throughput. The on-chip processor manages the overall operation of the compression system, including execution of the top-level control functions as well as scheduling, initiating, and monitoring processes. The design prototype has been demonstrated to be capable of compressing hyperspectral data at a rate of 4.5 megasamples per second at a conservative clock frequency of 50 MHz, with a potential for substantially greater throughput at a higher clock frequency. The power consumption of the prototype is less than 6.5 W. The reconfigurability (by means of reprogramming) of the FPGAs makes it possible to effectively alter the design to some extent to satisfy different requirements without adding hardware. The implementation could be easily propagated to future FPGA generations and/or to custom application-specific integrated circuits.

Aranki, Nazeeh↗

Multi-Stage System for Automatic Target Recognition

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Chao, Tien-Hsin↗

Compressing Image Data While Limiting the Effects of Data Losses

ICER is computer software that can perform both lossless and lossy compression and decompression of gray-scale-image data using discrete wavelet transforms. Designed for primary use in transmitting scientific image data from distant spacecraft to Earth, ICER incorporates an error-containment scheme that limits the adverse effects of loss of data and is well suited to the data packets transmitted by deep-space probes. The error-containment scheme includes utilization of the algorithm described in "Partitioning a Gridded Rectangle Into Smaller Rectangles " (NPO-30479), NASA Tech Briefs, Vol. 28, No. 7 (July 2004), page 56. ICER has performed well in onboard compression of thousands of images transmitted from the Mars Exploration Rovers.

Kiely, Aaron↗

Automatic Focus Adjustment of a Microscope

AUTOFOCUS is a computer program for use in a control system that automatically adjusts the position of an instrument arm that carries a microscope equipped with an electronic camera. In the original intended application of AUTOFOCUS, the imaging microscope would be carried by an exploratory robotic vehicle on a remote planet, but AUTOFOCUS could also be adapted to similar applications on Earth. Initially control software other than AUTOFOCUS brings the microscope to a position above a target to be imaged. Then the instrument arm is moved to lower the microscope toward the target: nominally, the target is approached from a starting distance of 3 cm in 10 steps of 3 mm each. After each step, the image in the camera is subjected to a wavelet transform, which is used to evaluate the texture in the image at multiple scales to determine whether and by how much the microscope is approaching focus. A focus measure is derived from the transform and used to guide the arm to bring the microscope to the focal height. When the analysis reveals that the microscope is in focus, image data are recorded and transmitted.

Huntsberger, Terrance↗

Wavenumber Imaging For Damage Detection and Measurement

This paper presents a method for analyzing ultrasonic wavefield data using the Continuous Wavelet Transform (CWT) applied in the spatial domain. Unlike data obtained by sparse arrays of transducers, full wavefield data contains information local to the structure and can be used to obtain more detailed measurements of damage type, location, size, etc. By calculating the CWT of the wavefield in the spatial domain, the wavenumber spectrum is determined for the inspected locations. Because wavenumber is affected by the local geometry and material properties of the structure through which Lamb waves propagate, the wavenumber spectrum can be analyzed to assess the location, severity, and size of damage. The technique is first applied to experimental wavefield data obtained using a laser Doppler vibrometer and automated positioning stage. The out-of-plane velocity along the length of a composite stringer was measured to detect the presence of delaminations within the composite overwrap. Next, simulated corrosion is detected and measured within an aluminum plate using the two dimensional CWT. The experimental results show the usefulness of the technique for vehicle structure inspection applications.

Rogge, Matthew D.↗

NASA Tech Briefs, November 2005

Topics covered include: Laser System for Precise, Unambiguous Range Measurements; Flexible Cryogenic Temperature and Liquid-Level Probes; Precision Cryogenic Dilatometer; Stroboscopic Interferometer for Measuring Mirror Vibrations; Some Improvements in H-PDLCs; Multiple-Bit Differential Detection of OQPSK; Absolute Position Encoders With Vertical Image Binning; Flexible, Carbon-Based Ohmic Contacts for Organic Transistors; GaAs QWIP Array Containing More Than a Million Pixels; AutoChem; Virtual Machine Language; Two-Dimensional Ffowcs Williams/Hawkings Equation Solver; Full Multigrid Flow Solver; Doclet To Synthesize UML; Computing Thermal Effects of Cavitation in Cryogenic Liquids; GUI for Computational Simulation of a Propellant Mixer; Control Program for an Optical-Calibration Robot; SQL-RAMS; Distributing Data from Desktop to Hand-Held Computers; Best-Fit Conic Approximation of Spacecraft Trajectory; Improved Charge-Transfer Fluorescent Dyes; Stability-Augmentation Devices for Miniature Aircraft; Tool Measures Depths of Defects on a Case Tang Joint; Two Heat-Transfer Improvements for Gas Liquefiers; Controlling Force and Depth in Friction Stir Welding; Spill-Resistant Alkali-Metal-Vapor Dispenser; A Methodology for Quantifying Certain Design Requirements During the Design Phase; Measuring Two Key Parameters of H3 Color Centers in Diamond; Improved Compression of Wavelet-Transformed Images; NASA Interactive Forms Type Interface - NIFTI; Predicting Numbers of Problems in Development of Software; Hot-Electron Photon Counters for Detecting Terahertz Photons; Magnetic Variations Associated With Solar Flares; and Artificial Intelligence for Controlling Robotic Aircraft.

Source record↗

Bit-Serial Adder Based on Quantum Dots

A proposed integrated circuit based on quantum-dot cellular automata (QCA) would function as a bit-serial adder. This circuit would serve as a prototype building block for demonstrating the feasibility of quantum-dots computing and for the further development of increasingly complex and increasingly capable quantum-dots computing circuits. QCA-based bit-serial adders would be especially useful in that they would enable the development of highly parallel and systolic processors for implementing fast Fourier, cosine, Hartley, and wavelet transforms. The proposed circuit would complement the QCA-based circuits described in "Implementing Permutation Matrices by Use of Quantum Dots" (NPO-20801), NASA Tech Briefs, Vol. 25, No. 10 (October 2001), page 42 and "Compact Interconnection Networks Based on Quantum Dots" (NPO-20855), which appears elsewhere in this issue. Those articles described the limitations of very-large-scale-integrated (VLSI) circuitry and the major potential advantage afforded by QCA. To recapitulate: In a VLSI circuit, signal paths that are required not to interact with each other must not cross in the same plane. In contrast, for reasons too complex to describe in the limited space available for this article, suitably designed and operated QCA-based signal paths that are required not to interact with each other can nevertheless be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes. To enable a meaningful description of the proposed bit-serial adder, it is necessary to further recapitulate the description of a quantum-dot cellular automation from the first-mentioned prior article: A quantum-dot cellular automaton contains four quantum dots positioned at the corners of a square cell. The cell contains two extra mobile electrons that can tunnel (in the quantum-mechanical sense) between neighboring dots within the cell. The Coulomb repulsion between the two electrons tends to make them occupy antipodal dots in the cell. For an isolated cell, there are two energetically equivalent arrangements (denoted polarization states) of the extra electrons. The cell polarization is used to encode binary information. Because the polarization of a nonisolated cell depends on Coulomb-repulsion interactions with neighboring cells, universal logic gates and binary wires could be constructed, in principle, by arraying QCA of suitable design in suitable patterns. Again, for reasons too complex to describe here, in order to ensure accuracy and timeliness of the output of a QCA array, it is necessary to resort to an adiabatic switching scheme in which the QCA array is divided into subarrays, each controlled by a different phase of a multiphase clock signal. In this scheme, each subarray is given time to perform its computation, then its state is frozen by raising its inter-dot potential barriers and its output is fed as the input to the successor subarray. The successor subarray is kept in an unpolarized state so it does not influence the calculation of preceding subarray. Such a clocking scheme is consistent with pipeline computation in the sense that each different subarray can perform a different part of an overall computation. In other words, QCA arrays are inherently suitable for pipeline and, moreover, systolic computations. This sequential or pipeline aspect of QCA would be utilized in the proposed bit-serial adders.

Fijany, Amir↗

Estimation of Time-Varying Pilot Model Parameters

Human control behavior is rarely completely stationary over time due to fatigue or loss of attention. In addition, there are many control tasks for which human operators need to adapt their control strategy to vehicle dynamics that vary in time. In previous studies on the identification of time-varying pilot control behavior wavelets were used to estimate the time-varying frequency response functions. However, the estimation of time-varying pilot model parameters was not considered. Estimating these parameters can be a valuable tool for the quantification of different aspects of human time-varying manual control. This paper presents two methods for the estimation of time-varying pilot model parameters, a two-step method using wavelets and a windowed maximum likelihood estimation method. The methods are evaluated using simulations of a closed-loop control task with time-varying pilot equalization and vehicle dynamics. Simulations are performed with and without remnant. Both methods give accurate results when no pilot remnant is present. The wavelet transform is very sensitive to measurement noise, resulting in inaccurate parameter estimates when considerable pilot remnant is present. Maximum likelihood estimation is less sensitive to pilot remnant, but cannot detect fast changes in pilot control behavior.

Zaal, Peter M. T.↗

Neural Network Target Identification System for False Alarm Reduction

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

ATR↗