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At least 343 records · Page 19

Development of Collaborative Research Initiatives to Advance the Aerospace Sciences-via the Communications, Electronics, Information Systems Focus Group

The primary goal of the Adaptive Vision Laboratory Research project was to develop advanced computer vision systems for automatic target recognition. The approach used in this effort combined several machine learning paradigms including evolutionary learning algorithms, neural networks, and adaptive clustering techniques to develop the E-MOR.PH system. This system is capable of generating pattern recognition systems to solve a wide variety of complex recognition tasks. A series of simulation experiments were conducted using E-MORPH to solve problems in OCR, military target recognition, industrial inspection, and medical image analysis. The bulk of the funds provided through this grant were used to purchase computer hardware and software to support these computationally intensive simulations. The payoff from this effort is the reduced need for human involvement in the design and implementation of recognition systems. We have shown that the techniques used in E-MORPH are generic and readily transition to other problem domains. Specifically, E-MORPH is multi-phase evolutionary leaming system that evolves cooperative sets of features detectors and combines their response using an adaptive classifier to form a complete pattern recognition system. The system can operate on binary or grayscale images. In our most recent experiments, we used multi-resolution images that are formed by applying a Gabor wavelet transform to a set of grayscale input images. To begin the leaming process, candidate chips are extracted from the multi-resolution images to form a training set and a test set. A population of detector sets is randomly initialized to start the evolutionary process. Using a combination of evolutionary programming and genetic algorithms, the feature detectors are enhanced to solve a recognition problem. The design of E-MORPH and recognition results for a complex problem in medical image analysis are described at the end of this report. The specific task involves the identification of vertebrae in x-ray images of human spinal columns. This problem is extremely challenging because the individual vertebra exhibit variation in shape, scale, orientation, and contrast. E-MORPH generated several accurate recognition systems to solve this task. This dual use of this ATR technology clearly demonstrates the flexibility and power of our approach.

Knasel, T. Michael↗

Algorithm for Wavefront Sensing Using an Extended Scene

A recently conceived algorithm for processing image data acquired by a Shack-Hartmann (SH) wavefront sensor is not subject to the restriction, previously applicable in SH wavefront sensing, that the image be formed from a distant star or other equivalent of a point light source. That is to say, the image could be of an extended scene. (One still has the option of using a point source.) The algorithm can be implemented in commercially available software on ordinary computers. The steps of the algorithm are the following: 1. Suppose that the image comprises M sub-images. Determine the x,y Cartesian coordinates of the centers of these sub-images and store them in a 2xM matrix. 2. Within each sub-image, choose an NxN-pixel cell centered at the coordinates determined in step 1. For the ith sub-image, let this cell be denoted as si(x,y). Let the cell of another subimage (preferably near the center of the whole extended-scene image) be designated a reference cell, denoted r(x,y). 3. Calculate the fast Fourier transforms of the sub-sub-images in the central NxN portions (where N < N and both are preferably powers of 2) of r(x,y) and si(x,y). 4. Multiply the two transforms to obtain a cross-correlation function Ci(u,v), in the Fourier domain. Then let the phase of Ci(u, v) constitute a phase function, phi(u,v). 5. Fit u and v slopes to phi (u,v) over a small u,v subdomain. 6. Compute the fast Fourier transform, Si(u,v) of the full NxN cell si(x,y). Multiply this transform by the u and phase slopes obtained in step 4. Then compute the inverse fast Fourier transform of the product. 7. Repeat steps 4 through 6 in an iteration loop, cumulating the u and slopes, until a maximum iteration number is reached or the change in image shift becomes smaller than a predetermined tolerance. 8. Repeat steps 4 through 7 for the cells of all other sub-images.

Sidick, Erkin↗

Stellar spectrum classifier

Stellar classification is accomplished by correlating holograms of classified spectra with the Fourier transform of the spectral images to be classified.

Reid, J. H.↗

Exploration of Mars by Mariner 9 - Television sensors and image processing.

Two cameras equipped with selenium sulfur slow scan vidicons were used in the orbital reconnaissance of Mars by the U.S. Spacecraft Mariner 9 and the performance characteristics of these devices are presented. Digital image processing techniques have been widely applied in the analysis of images of Mars and its satellites. Photometric and geometric distortion corrections, image detail enhancement and transformation to standard map projection have been routinely employed. More specializing applications included picture differencing, limb profiling, solar lighting corrections, noise removal, line plots and computer mosaics. Information on enhancements as well as important picture geometric information was stored in a master library. Display of the library data in graphic or numerical form was accomplished by a data management computer program.

Cutts, J. A.↗

Laser Doppler velocimeter system simulation for sensing aircraft wake vortices

A hydrodynamic model of aircraft vortex wakes in an irregular wind shear field near the ground is developed and used as a basis for modeling the characteristics of a laser Doppler detection and vortex location system. The trailing vortex sheet and the wind shear are represented by discrete free vortices distributed over a two-dimensional grid. The time dependent hydrodynamic equations are solved by direct numerical integration in the Boussinesq approximation. The ground boundary is simulated by images, and fast Fourier Transform techniques are used to evaluate the vorticity stream function. The atmospheric turbulence was simulated by constructing specific realizations at time equal to zero, assuming that Kolmogoroff's law applies, and that the dissipation rate is constant throughout the flow field. The response of a simulated laser Doppler velocimeter is analyzed by simulating the signal return from the flow field as sensed by a simulation of the optical/electronic system.

Thomson, J. A. L.↗

Digital processing of the Mariner 10 images of Venus and Mercury

An extensive effort was devoted to the digital processing of the Mariner 10 images of Venus and Mercury at the Image Processing Laboratory of the Jet Propulsion Laboratory. This effort was designed to optimize the display of the considerable quantity of information contained in the images. Several image restoration, enhancement, and transformation procedures were applied; examples of these techniques are included. A particular task was the construction of large mosaics which characterize the surface of Mercury and the atmospheric structure of Venus.

Soha, J. M.↗

Image and numerical display aids for manual interpretation

Four color image display techniques, developed to aid in interpreting LANDSAT imagery, are described. These are the cluster image, the principal component transformation, the principal component greenness transformation, and the color-coded spectral plot. Experimental results show that the four techniques are useful in selecting and/or identifying representative samples of signatures in a given LANDSAT scene.

Abotteen, R. A.↗

A forester's look at the application of image manipulation techniques to multitemporal Landsat data

Registered, multitemporal Landsat data of a study area in central Pennsylvania were analyzed to detect and assess changes in the forest canopy resulting from insect defoliation. Images taken July 19, 1976, and June 27, 1977, were chosen specifically to represent forest canopy conditions before and after defoliation, respectively. Several image manipulation and data transformation techniques, developed primarily for estimating agricultural and rangeland standing green biomass, were applied to these data. The applicability of each technique for estimating the severity of forest canopy defoliation was then evaluated. All techniques tested had highly correlated results. In all cases, heavy defoliation was discriminated from healthy forest. Areas of moderate defoliation were confused with healthy forest on northwest (NW) aspects, but were distinct from healthy forest conditions on southeast (SE)-facing slopes.

Williams, D. L.↗

Geometrical rectification of spin-scan images from Pioneer 11

Images of Saturn received from Pioneer 11 suffer from geometrical distortions due to the curvilinear scan lines and the unequal sampling intervals in orthogonal directions, which are inherent in spin-scan imaging. In this paper geometrical image rectification by polynomial transformation based on control points is discussed. Factors that affect the accuracy of reconstruction are shown to include the spatial distribution and spatial density of control points, and the order of the polynomial distortion model. A computer implementation of the technique is described.

Strickland, R. N.↗

Optimal spatial filtering and transfer function for SAR ocean wave spectra

The impulse response of the SAR system is not a delta function and the spectra represent the product of the underlying image spectrum with the transform of the impulse response which must be removed. A digitally computed spectrum of SEASAT imagery of the Atlantic Ocean east of Cape Hatteras was smoothed with a 5 x 5 convolution filter and the trend was sampled in a direction normal to the predominant wave direction. This yielded a transform of a noise-like process. The smoothed value of this trend is the transform of the impulse response. This trend is fit with either a second- or fourth-order polynomial which is then used to correct the entire spectrum. A 16 x 16 smoothing of the spectrum shows the presence of two distinct swells. Correction of the effects of speckle is effected by the subtraction of a bias from the spectrum.

Beal, R. C.↗

Spatial heterodyne spectroscopy - Interferometric performance at any wavelength without scanning

Spatial heterodyne spectroscopy (SHS) employing a two-beam dispersive interferometer producing a Fizeau fringe pattern having wavelength-dependent spatial frequencies is presented. The pattern is recorded on an imaging detector and Fourier transformed to recover the input stream. It is pointed out that spectrometers operating on the SHS principle can achieve the theoretical resolution limit of the gratings without scanning, retaining at the same time the large angular input tolerance and multiplexing properties of conventional scanning Fourier-transform spectrometers. Additionally, broad spectral coverages can be achieved, and field widening can be accomplished without moving parts.

Roesler, F. L.↗

Integrated topology and shape optimization in structural design

Structural optimization procedures usually start from a given design topology and vary its proportions or boundary shapes to achieve optimality under various constraints. Two different categories of structural optimization are distinguished in the literature, namely sizing and shape optimization. A major restriction in both cases is that the design topology is considered fixed and given. Questions concerning the general layout of a design (such as whether a truss or a solid structure should be used) as well as more detailed topology features (e.g., the number and connectivities of bars in a truss or the number of holes in a solid) have to be resolved by design experience before formulating the structural optimization model. Design quality of an optimized structure still depends strongly on engineering intuition. This article presents a novel approach for initiating formal structural optimization at an earlier stage, where the design topology is rigorously generated in addition to selecting shape and size dimensions. A three-phase design process is discussed: an optimal initial topology is created by a homogenization method as a gray level image, which is then transformed to a realizable design using computer vision techniques; this design is then parameterized and treated in detail by sizing and shape optimization. A fully automated process is described for trusses. Optimization of two dimensional solid structures is also discussed. Several application-oriented examples illustrate the usefulness of the proposed methodology.

Bremicker, M.↗

A VLSI implementation of DCT using pass transistor technology

A VLSI design for performing the Discrete Cosine Transform (DCT) operation on image blocks of size 16 x 16 in a real time fashion operating at 34 MHz (worst case) is presented. The process used was Hewlett-Packard's CMOS26--A 3 metal CMOS process with a minimum feature size of 0.75 micron. The design is based on Multiply-Accumulate (MAC) cells which make use of a modified Booth recoding algorithm for performing multiplication. The design of these cells is straight forward, and the layouts are regular with no complex routing. Two versions of these MAC cells were designed and their layouts completed. Both versions were simulated using SPICE to estimate their performance. One version is slightly faster at the cost of larger silicon area and higher power consumption. An improvement in speed of almost 20 percent is achieved after several iterations of simulation and re-sizing.

Kamath, S.↗

A photogrammetric solution to a particular problem

A closed-form mathematical solution to the classical photogrammetric problem is presented. Although quite general, the solution is more applicable to problems in which the image-space conjugates are very difficult to match but one of the elements of the pair is not. Additionally, observations are made that should make the solution to the general problem of automatic matching less computationally intensive. This approach was used to analyze flow visualization data for the F-18 High Alpha Research Vehicle. The conditions for this analysis were less than ideal for image-to-object-space transformation.

Hedgley, David R., Jr.↗

Perceptually Lossless Wavelet Compression

The Discrete Wavelet Transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter, which we call DWT uniform quantization noise. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2(exp -1), where r is display visual resolution in pixels/degree, and L is the wavelet level. Amplitude thresholds increase rapidly with spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from low-pass to horizontal/vertical to diagonal. We propose a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a 'perceptually lossless' quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.

Watson, Andrew B.↗

Visibility of Wavelet Quantization Noise

The Discrete Wavelet Transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter, which we call DWT uniform quantization noise. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2(exp)-L , where r is display visual resolution in pixels/degree, and L is the wavelet level. Amplitude thresholds increase rapidly with spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from low-pass to horizontal/vertical to diagonal. We describe a mathematical model to predict DWT noise detection thresholds as a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.

Watson, Andrew B.↗

Visualization of Computational Fluid Dynamics

Scientific visualization serves the dual purpose of exploration and exposition of the results of numerical simulations of fluid flow. Along with the basic visualization process which transforms source data into images, there are four additional components to a complete visualization system: Source Data Processing, User Interface and Control, Presentation, and Information Management. The requirements imposed by the desired mode of operation (i.e. real-time, interactive, or batch) and the source data have their effect on each of these visualization system components. The special requirements imposed by the wide variety and size of the source data provided by the numerical simulation of fluid flow presents an enormous challenge to the visualization system designer. We describe the visualization system components including specific visualization techniques and how the mode of operation and source data requirements effect the construction of computational fluid dynamics visualization systems.

Gerald-Yamasaki, Michael↗

Pulse Phase Thermography for Defect Detection and Visualization

Pulse Phase Thermography (PPT) has been reported as a novel powerful technique of the thermal NDE. It employs application of the Discrete Fourier Transform (DFT) to thermal images obtained following flash heating of the front surface of a specimen. The computed phasegrams are excellent for defect visualization in a wide range of materials. This is in part due to their low sensitivity to uneven heating. This work is an attempt to analyze advantages and limitations of PPT. Results of application of the DFT to simulated temperature decays are presented. The temperature evolution on a surface has been simulated based on an analytical solution of the one-dimensional heat diffusion problem. A more sophisticated study has been done for different sizes of defects using numerical solution of the three-dimensional mathematical model. Capabilities of PPT for in-depth scanning and for monitoring of the material loss are discussed. The recommendations for the practical application of the PPT are presented. Experimental results obtained following these recommendations are reported.

Marinetti, Sergio↗