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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Platform for Postprocessing Waveform-Based NDE

Taking advantage of the similarities that exist among all waveform-based non-destructive evaluation (NDE) methods, a common software platform has been developed containing multiple- signal and image-processing techniques for waveforms and images. The NASA NDE Signal and Image Processing software has been developed using the latest versions of LabVIEW, and its associated Advanced Signal Processing and Vision Toolkits. The software is useable on a PC with Windows XP and Windows Vista. The software has been designed with a commercial grade interface in which two main windows, Waveform Window and Image Window, are displayed if the user chooses a waveform file to display. Within these two main windows, most actions are chosen through logically conceived run-time menus. The Waveform Window has plots for both the raw time-domain waves and their frequency- domain transformations (fast Fourier transform and power spectral density). The Image Window shows the C-scan image formed from information of the time-domain waveform (such as peak amplitude) or its frequency-domain transformation at each scan location. The user also has the ability to open an image, or series of images, or a simple set of X-Y paired data set in text format. Each of the Waveform and Image Windows contains menus from which to perform many user actions. An option exists to use raw waves obtained directly from scan, or waves after deconvolution if system wave response is provided. Two types of deconvolution, time-based subtraction or inverse-filter, can be performed to arrive at a deconvolved wave set. Additionally, the menu on the Waveform Window allows preprocessing of waveforms prior to image formation, scaling and display of waveforms, formation of different types of images (including non-standard types such as velocity), gating of portions of waves prior to image formation, and several other miscellaneous and specialized operations. The menu available on the Image Window allows many further image processing and analysis operations, some of which are found in commercially-available image-processing software programs (such as Adobe Photoshop), and some that are not (removing outliers, Bscan information, region-of-interest analysis, line profiles, and precision feature measurements).

Roth, Don↗
NASA NTRS1994

Wavelet analysis applied to the IRAS cirrus

The structure of infrared cirrus clouds is analyzed with Laplacian pyramid transforms, a form of non-orthogonal wavelets. Pyramid and wavelet transforms provide a means to decompose images into their spatial frequency components such that all spatial scales are treated in an equivalent manner. The multiscale transform analysis is applied to IRAS 100 micrometer maps of cirrus emission in the north Galactic pole region to extract features on different scales. In the maps we identify filaments, fragments and clumps by separating all connected regions. These structures are analyzed with respect to their Hausdorff dimension for evidence of the scaling relationships in the cirrus clouds.

Langer, William D.↗
NASA NTRS1984

Rapid extraction of relative topography from Viking orbiter images. 2: Application to irregular topographic features

The ratio and flat field photoclinometric methods for determining crater form topography are described. Both methods compensate for the effects of atmospheric scattering by subtracting a haze value from all brightness values. Algorithms were altered to derive relative topographic data for irregular features such as ejecta blankets, lava flows, graben and ridge scarps, dune forms, and stratified materials. After the elevations along the profiles are obtained by integration of the photometric function, a matrix transformation is applied to the image coordinates of each pixel within each profile, utilizing each pixel's integral height, to produce a projection of each profile line onto the surface. Pixel brightness values are then resampled along the projected track of each profile to determine a more correct height value for each pixel. Precision of the methods is discussed.

Davis, P. A.↗
NASA NTRS1988

Millimeter-wave Sensor Image Enhancement

Images of an airborne scanning radiometer operating at a frequency of 98 GHz were analyzed. The mm wave images were obtained using the JPL mm wave imaging sensor. The goal was to enhance the information content of these images and make their interpretation easier for human analysis. A visual interpretative approach was used for information extraction from the images. This included application of nonlinear transform techniques for noise reduction and for color, contrast, and edge enhancement. Results of the techniques on selected mm wave images are shown.

Wilson, William J.↗
NASA NTRS2001

Compression of echocardiographic scan line data using wavelet packet transform

An efficient compression strategy is indispensable for digital echocardiography. Previous work has suggested improved results utilizing wavelet transforms in the compression of 2D echocardiographic images. Set partitioning in hierarchical trees (SPIHT) was modified to compress echocardiographic scanline data based on the wavelet packet transform. A compression ratio of at least 94:1 resulted in preserved image quality.

Non-NASA Center↗
NASA NTRS2010

Automatic Feature Extraction from Planetary Images

With the launch of several planetary missions in the last decade, a large amount of planetary images has already been acquired and much more will be available for analysis in the coming years. The image data need to be analyzed, preferably by automatic processing techniques because of the huge amount of data. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to planetary data that often present low contrast and uneven illumination characteristics. Different methods have already been presented for crater extraction from planetary images, but the detection of other types of planetary features has not been addressed yet. Here, we propose a new unsupervised method for the extraction of different features from the surface of the analyzed planet, based on the combination of several image processing techniques, including a watershed segmentation and the generalized Hough Transform. The method has many applications, among which image registration and can be applied to arbitrary planetary images.

Troglio, Giulia↗
NASA NTRS1989

Millimeter-wave sensor image analysis

Images of an airborne, scanning, radiometer operating at a frequency of 98 GHz, have been analyzed. The mm-wave images were obtained in 1985/1986 using the JPL mm-wave imaging sensor. The goal of this study was to enhance the information content of these images and make their interpretation easier for human analysis. In this paper, a visual interpretative approach was used for information extraction from the images. This included application of nonlinear transform techniques for noise reduction and for color, contrast and edge enhancement. Results of the techniques on selected mm-wave images are presented.

Wilson, William J.↗
NASA NTRS1996

Soot Precursor Material: Spatial Location via Simultaneous LIF-LII Imaging and Characterization via TEM

The chemical and physical transformation between gaseous fuel pyrolysis products and solid carbonaceous soot represents a critical step in soot formation. In this paper, simultaneous two-dimensional LIF-LII (laser-induced fluorescence - laser-induced incandescence) images identify the spatial location where the earliest identifiable chemical and physical transformation of material towards solid carbonaceous soot occurs along the axial streamline in a normal diffusion flame. The identification of the individual LIF and LII signals is achieved by examining both the excitation wavelength dependence and characteristic temporal decay of each signal. Spatially precise thermophoretic sampling measurements are guided by the LIF-LII images with characterization of the sampled material accomplished via both bright and dark field TEM. Both bright and dark field TEM measurements support the observed changes in photophysical properties which account for conversion of fluorescence to incandescence as fuel pyrolysis products evolve towards solid carbonaceous soot.

VanderWal, Randall L.↗
NASA NTRS2000

Little Homunculus with in the Homunculus of Eta Carinae

The famous HST/WFPC2 images of Eta Carinae provide a two-dimensional projection of the bipolar nebula that is really a three-dimensional structure. Much is hidden in subtle, projected details that a velocity-tuned instrument can pull apart. We have used the HST/STIS with a 52" x 0.1" aperture and with about 5000 spectral resolving power to examine the kinetic information contained within emission/absorption features. By velocity tuning, we can translate this information into spatial structures. The spectroscopic datasets have been transformed to a set of images, spaced at half instrumental line width steps, 15 - 20 km/s , and with a spatial resolution of 0.1 x 0.1 arcsec near Balmer beta and 0.25 x 0.1 arcsec near Balmer alpha. We examined these narrow-band images and individual spectra to characterize the nature of an internal nebula (formerly known as the Integral nebula). The shape of this nebulosity is an bipolar nebula, deeply embedded within the Homunculus, the well-known bipolar nebula surrounding Eta Carinae. The internal nebula is shaped nearly identically to the Homunculus. It is best described as a "little Homunculus within the Homunculus". Indeed, it is reminiscent of the Russian dolls, known as Matryoshka dolls, that successively nest within each larger doll. For that reason, we call this internal nebula the Matryoshka nebula. This was performed as one of the STIS GTO key projects and was funded by the HST project. Observations were done through the STScI.

Ishibashi, Kazunori↗
NASA NTRS1989

Millimeter-wave sensor image enhancement

Images from an airborne, scanning radiometer operating at a frequency of 98 GHz have been analyzed. The millimeter-wave images were obtained in 1985-1986 using the JPL millimeter-wave imaging sensor. The goal of this study was to enhance the information content of these images and make their interpretation easier. A visual-interpretative approach was used for information extraction from the images. This included application of nonlinear transform techniques for noise reduction and for color, contrast, and edge enhancement. Results of using the techniques on selected millimeter-wave images are discussed.

Wilson, William J.↗
NASA NTRS2009

Automatic Extraction of Planetary Image Features

With the launch of several Lunar missions such as the Lunar Reconnaissance Orbiter (LRO) and Chandrayaan-1, a large amount of Lunar images will be acquired and will need to be analyzed. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to Lunar data that often present low contrast and uneven illumination characteristics. In this paper, we propose a new method for the extraction of Lunar features (that can be generalized to other planetary images), based on the combination of several image processing techniques, a watershed segmentation and the generalized Hough Transform. This feature extraction has many applications, among which image registration.

Troglio, G.↗
NASA NTRS1993

Expansion-based passive ranging

This paper describes a new technique of passive ranging which is based on utilizing the image-plane expansion experienced by every object as its distance from the sensor decreases. This technique belongs in the feature/object-based family. The motion and shape of a small window, assumed to be fully contained inside the boundaries of some object, is approximated by an affine transformation. The parameters of the transformation matrix are derived by initially comparing successive images, and progressively increasing the image time separation so as to achieve much larger triangulation baseline than currently possible. Depth is directly derived from the expansion part of the transformation. To a first approximation, image-plane expansion is independent of image-plane location with respect to the focus of expansion (FOE) and of platform maneuvers. Thus, an expansion-based method has the potential of providing a reliable range in the difficult image area around the FOE. In areas far from the FOE the shift parameters of the affine transformation can provide more accurate depth information than the expansion alone, and can thus be used similarly to the way they have been used in conjunction with the Inertial Navigation Unit (INU) and Kalman filtering. However, the performance of a shift-based algorithm, when the shifts are derived from the affine transformation, would be much improved compared to current algorithms because the shifts--as well as the other parameters--can be obtained between widely separated images. Thus, the main advantage of this new approach is that, allowing the tracked window to expand and rotate, in addition to moving laterally, enables one to correlate images over a very long time span which, in turn, translates into a large spatial baseline resulting in a proportionately higher depth accuracy.

Barniv, Yair↗
NASA NTRS1993

Expansion-based passive ranging

A new technique of passive ranging which is based on utilizing the image-plane expansion experienced by every object as its distance from the sensor decreases is described. This technique belongs in the feature/object-based family. The motion and shape of a small window, assumed to be fully contained inside the boundaries of some object, is approximated by an affine transformation. The parameters of the transformation matrix are derived by initially comparing successive images, and progressively increasing the image time separation so as to achieve much larger triangulation baseline than currently possible. Depth is directly derived from the expansion part of the transformation. To a first approximation, image-plane expansion is independent of image-plane location with respect to the focus of expansion (FOE) and of platform maneuvers. Thus, an expansion-based method has the potential of providing a reliable range in the difficult image area around the FOE. In areas far from the FOE the shift parameters of the affine transformation can provide more accurate depth information than the expansion alone, and can thus be used similarly to the way they were used in conjunction with the Inertial Navigation Unit (INU) and Kalman filtering. However, the performance of a shift-based algorithm, when the shifts are derived from the affine transformation, would be much improved compared to current algorithms because the shifts - as well as the other parameters - can be obtained between widely separated images. Thus, the main advantage of this new approach is that, allowing the tracked window to expand and rotate, in addition to moving laterally, enables one to correlate images over a very long time span which, in turn, translates into a large spatial baseline - resulting in a proportionately higher depth accuracy.

Barniv, Yair↗
NASA NTRS2003

In-Flight MTF Analysis of ADAR 5500 Aircraft Sensor

The Modulation Transfer Function (MTF) of an imaging system is one parameter that can be used to describe the spatial resolution or the image quality of an imaging system. MTF is the system's frequency response to an input. The MTF at a specific frequency normally ranges from 0-1, where 0 indicates no frequency response and 1 indicates perfect frequency response. The MTF value at Nyquist frequency is calculated because the Nyquist frequency is the maximum sampling frequency of the system. MTF analysis was performed on data acquired with an ADAR 5500 flown by Positive Systems on September 13-14, 2000 over Brookings, SD. Four edges from ground targets were used as inputs to the system. The system's MTF was calculated using a Matlab-based algorithm, which applied edge detection, numerical differentiation, and Fourier transformation methods to the target images.

Zanoni, Vicki↗
NASA NTRS1986

Development of a numerical procedure to map a general 3-d body onto a near-circle

Conformal mapping is a classical technique utilized for solving problems in aerodynamics and hydrodynamics. Conformal mapping is utilized in the construction of grids around airfoils, engine inlets and other aircraft configurations. These shapes are transformed onto a near-circle image for which the equations of fluid motion are discretized on the mapped plane and solved numerically by utilizing the appropriate techniques. In comparison to other grid-generation techniques such as algerbraic or differential type, conformal mapping offers an analytical and accurate form even if the grid deformation is large. One of the most appealing features is that the grid can be constrained to remain orthogonal to the body after the transformation. Hence, the grid is suitable for analyzing the supersonic flow past a blunt object. The associated shock as a coordinate surface adjusts its position in the course of computation until convergence is reached. The present work applied conformal mapping to 3-D bodies with no axis of symmetry such as the Aerobraking Flight Experiment (AFE) vehicle, transforming the AFE shape onto a near-circle image. A numerical procedure and code are used to generate grids around the AFE body.

Hommel, M. J.↗
NASA NTRS1994

An image assessment study of image acceptability of the Galileo low gain antenna mission

This paper describes a study conducted by NASA Ames Research Center (ARC) in collaboration with the Jet Propulsion Laboratory (JPL), Pasadena, California on the image acceptability of the Galileo Low Gain Antenna mission. The primary objective of the study is to determine the impact of the Integer Cosine Transform (ICT) compression algorithm on Galilean images of atmospheric bodies, moons, asteroids and Jupiter's rings. The approach involved fifteen volunteer subjects representing twelve institutions involved with the Galileo Solid State Imaging (SSI) experiment. Four different experiment specific quantization tables (q-table) and various compression stepsizes (q-factor) to achieve different compression ratios were used. It then determined the acceptability of the compressed monochromatic astronomical images as evaluated by Galileo SSI mission scientists. Fourteen different images were evaluated. Each observer viewed two versions of the same image side by side on a high resolution monitor, each was compressed using a different quantization stepsize. They were requested to select which image had the highest overall quality to support them in carrying out their visual evaluations of image content. Then they rated both images using a scale from one to five on its judged degree of usefulness. Up to four pre-selected types of images were presented with and without noise to each subject based upon results of a previously administered survey of their image preferences. Fourteen different images in seven image groups were studied. The results showed that: (1) acceptable compression ratios vary widely with the type of images; (2) noisy images detract greatly from image acceptability and acceptable compression ratios; and (3) atmospheric images of Jupiter seem to have higher compression ratios of 4 to 5 times that of some clear surface satellite images.

Chuang, S. L.↗
NASA NTRS1990

Computation and parallel implementation for early vision

The problem of early vision is to transform one or more retinal illuminance images-pixel arrays-to image representations built out of such primitive visual features such as edges, regions, disparities, and clusters. These transformed representations form the input to later vision stages that perform higher level vision tasks including matching and recognition. Researchers developed algorithms for: (1) edge finding in the scale space formulation; (2) correlation methods for computing matches between pairs of images; and (3) clustering of data by neural networks. These algorithms are formulated for parallel implementation of SIMD machines, such as the Massively Parallel Processor, a 128 x 128 array processor with 1024 bits of local memory per processor. For some cases, researchers can show speedups of three orders of magnitude over serial implementations.

Gualtieri, J. Anthony↗
NASA NTRS1981

The magnifying glass - A feature space local expansion for visual analysis

The Magnifying Glass Transformation (MGT) technique is proposed, as a multichannel spectral operation yielding visual imagery which is enhanced in a specified spectral vicinity, guided by the statistics of training samples. An application example is that in which the discrimination among spectral neighbors within an interactive display may be increased without altering distant object appearances or overall interpretation. A direct histogram specification technique is applied to the channels within the multispectral image so that a subset of the spectral domain occupies an increased fraction of the domain. The transformation is carried out by obtaining the training information, establishing the condition of the covariance matrix, determining the influenced solid, and initializing the lookup table. Finally, the image is transformed.

Juday, R. D.↗