Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Image representation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Image recovery from edge primitives

A method for extracting edge primitives from Mach-band patterns is presented together with a method for recovering image representations of features outlined by the edge boundaries. The accuracy, stability, and resolution of these representations are assessed. Since these representations are most commonly used in characterizing targets, this method of low-level processing offers new opportunities for computer vision and high data-compressing coding. Two bandpass filters are considered, the spatially invariant Laplacian of Gaussian filter and spatially variant intensity-dependent spatial (IDS) summation. It is shown that the recovery from the IDS bandpass data is particularly advantageous in applications for which robustness to local and temporal variations in illumination is important. It is concluded that the edge primitives extracted from bandpassed images can be an efficient way to store, transmit, and represent images.

Alter-Gartenberg, Rachel↗
NASA NTRS2001

Detection and Characterization of Imperfections in Composite Pressure Vessels

The thermographic evaluation of composite structures for delaminations, disbonds, inclusions, porosity and microcracking has proven to be a valuable asset in the field of nondestructive testing. Coupling large area coverage, variable sensitivity and minimal surface contact with a photographic type image representation of structural anomalies; thermography has become a primary inspection method for composite structures. Thermography works well for locating both surface and subsurface defects in most composite systems ranging in thickness of up to 0.25 inch (0.64 cm) or more. The thermographic method for inspection of composite structures typically involves applying an external source of heat to the structure and then recording the changes in the surface heat profile manifested by embedded defects or by material property variations. If these temperature variations are large enough and an infrared camera with sufficient sensitivity is used, then the material or structural abnormality can be detected and referred back to its source. Interpreting the information given in a thermogram, can be a difficult task under ideal circumstances and extremely challenging in a real world setting. Variables including depth, thermal conductivity, orientation and size of the abnormality can all have a great influence on how its heat pattern will be seen by the imager. The work discussed in this paper illustrates how the microstructure of several commonly found defects in composite structures relate to their thermographic image counterpart. Two test cases are studied herein, including a large graphite/epoxy RP-1 fuel tank and a graphite composite cryogenic fuel feedline. The structures used in this study were designed to serve as manufacturing proof of concept specimens and to undergo hydroburst testing to verify manufacturing practices and structural design. Prior to hydrostatic testing the structures underwent 100% thermographic evaluation to ensure that no manufacturing or handling damage was present. Due to a large inclusion found in the feedline, it was pulled from service and dissected without performing the hydroproof The thermographic indications found in the RP-1 tank were below critical limits so it underwent a complete hydroproof loading series and finally a hydroburst. Following the hydroburst samples were cut from the tank in regions where thermography had located damage before the test. These regions were thermographically and then were cross-sectioned and photomicrographed.

Walker, James L.↗
NASA NTRS1983

Improving our understanding of the remote sensing process

Plans for two fundamental research programs aimed at improving an understanding of the physics and mathematics of remote sensing are discussed. The first program, Scene Radiation and Atmospheric Research Program, is concerned with developing the capability to determine biophysical attributes of terrestrial scenes through an improved understanding of the relationships between those properties and remotely sensed radiation. The research issues in the second program, Mathematical Pattern Recognition and Image Analysis, are discussed with reference to the following five categories: preprocessing, digital image representation, object scene inference, computational structures, and continuing studies.

Calabrese, M. A.↗
NASA NTRS1996

Holographic Imaging In Dense Artificial Fog

Artificial fog serves as volume-projection medium for display of three-dimensional image. Projection technique enables display of images for variety of purposes, possibly including entertainment, indoor and outdoor advertising, medical diagnostics and image representations for surgical procedures, and education.

Liu, Hua-Kuang↗
NASA NTRS1995

Filtering Image Records Using Wavelets and the Zakai Equation

Consider the problem of detecting and localizing a faint object moving In an "essentially stationary" background, using a sequence of two-dimensional low-SNR images of the scene. A natural approach consists of "digitizing" each snapshot into a discrete set of observations, sufficiently (perhaps not exactly) matched to the object In question, then tracking the object using an appropriate stochastic filter. The tracking would be expected to make up for the low signal-to-noise ratio, this allowing one to "coherently" process successive images in order to beat down the noise and localize the object. Thus, "tracking" here does not refer to the usual notion of detecting then tracking: rather, we track in order to detect The problem then becomes one of choosing the appropriate image representation as well as the optimal (and necessarily nonlinear filter. We propose exact and approximate solutions using wavelets and the Zakai equation. The smoothness of the wavelets used is required in the derivation of the evolution equation for the conditional density giving the filter, and their orthogonality makes it possible to carry out actual computations of the Ito- and change-of-gauge-terms in the algorithm effectively.

Haddad, Ziad S.↗
NASA NTRSDate not supplied

Analyzing Natural Language Context in Human-Machine Teaming using Supervised Machine Learning

Building a foundation for trustworthiness and trust verification in multi-asset teaming is the research challenge of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR). The Design Reference Mission (DRM) for ATTRACTOR is a search and rescue mission objective governed by a multi-member team consisting of human and machine operators. A crucial component to the effort is the communication between humans and autonomous agents throughout both planning and execution stages of the mission. Intuitive communication methods and modalities are posited as critical enablers for certifying trust and trustworthiness. This paper reports on the data collection and analysis conducted in support of the Human Informed Natural-language GANs Evaluation (HINGE)project to attain explainable and trusted communication between human-machine assets. Two identically curated image description datasets were acquired for HINGE, both consisting of two unique input modalities (typed vs. verbal) and retrieved in two distinct contexts (general vs. specific). The gathered datasets were assessed and compared using Parts-of-Speech (POS)features, sentence similarity metrics, and linguistic analysis. Then, the datasets were modeled and tested separately and in combination with one another using machine learning algorithms. The comparison and testing results reveal a superior dataset, by which a preferred context and input is understood, for generating image representations of missing persons using a Generative Adversarial Network (GAN).

Bryan A Barrows↗
NASA NTRS1975

Spline function approximation techniques for image geometric distortion representation

Least squares approximation techniques were developed for use in computer aided correction of spatial image distortions for registration of multitemporal remote sensor imagery. Polynomials were first used to define image distortion over the entire two dimensional image space. Spline functions were then investigated to determine if the combination of lower order polynomials could approximate a higher order distortion with less computational difficulty. Algorithms for generating approximating functions were developed and applied to the description of image distortion in aircraft multispectral scanner imagery. Other applications of the techniques were suggested for earth resources data processing areas other than geometric distortion representation.

Anuta, P. E.↗
NASA NTRS1988

Autonomous image data reduction by analysis and interpretation

Image data is a critical component of the scientific information acquired by space missions. Compression of image data is required due to the limited bandwidth of the data transmission channel and limited memory space on the acquisition vehicle. This need becomes more pressing when dealing with multispectral data where each pixel may comprise 300 or more bytes. An autonomous, real time, on-board image analysis system for an exploratory vehicle such as a Mars Rover is developed. The completed system will be capable of interpreting image data to produce reduced representations of the image, and of making decisions regarding the importance of data based on current scientific goals. Data from multiple sources, including stereo images, color images, and multispectral data, are fused into single image representations. Analysis techniques emphasize artificial neural networks. Clusters are described by their outlines and class values. These analysis and compression techniques are coupled with decision making capacity for determining importance of each image region. Areas determined to be noise or uninteresting can be discarded in favor of more important areas. Thus limited resources for data storage and transmission are allocated to the most significant images.

Eberlein, Susan↗
NASA NTRS1988

Autonomous image data reduction by analysis and interpretation

Image data is a critical component of the scientific information acquired by space missions. Compression of image data is required due to the limited bandwidth of the data transmission channel and limited memory space on the acquisition vehicle. This need becomes more pressing when dealing with multispectral data where each pixel may comprise 300 or more bytes. An autonomous, real time, on-board image analysis system for an exploratory vehicle such as a Mars Rover is developed. The completed system will be capable of interpreting image data to produce reduced representations of the image, and of making decisions regarding the importance of data based on current scientific goals. Data from multiple sources, including stereo images, color images, and multispectral data, are fused into single image representations. Analysis techniques emphasize artificial neural networks. Clusters are described by their outlines and class values. These analysis and compression techniques are coupled with decision-making capacity for determining importance of each image region. Areas determined to be noise or uninteresting can be discarded in favor of more important areas. Thus limited resources for data storage and transmission are allocated to the most significant images.

Eberlein, Susan↗
NASA NTRS1979

Computer image processing and recognition

A systematic introduction to the concepts and techniques of computer image processing and recognition is presented. Consideration is given to such topics as image formation and perception; computer representation of images; image enhancement and restoration; reconstruction from projections; digital television, encoding, and data compression; scene understanding; scene matching and recognition; and processing techniques for linear systems.

Hall, E. L.↗
NASA NTRS1993

Fractal image compression: A resolution independent representation for imagery

A deterministic fractal is an image which has low information content and no inherent scale. Because of their low information content, deterministic fractals can be described with small data sets. They can be displayed at high resolution since they are not bound by an inherent scale. A remarkable consequence follows. Fractal images can be encoded at very high compression ratios. This fern, for example is encoded in less than 50 bytes and yet can be displayed at resolutions with increasing levels of detail appearing. The Fractal Transform was discovered in 1988 by Michael F. Barnsley. It is the basis for a new image compression scheme which was initially developed by myself and Michael Barnsley at Iterated Systems. The Fractal Transform effectively solves the problem of finding a fractal which approximates a digital 'real world image'.

Sloan, Alan D.↗
NASA NTRS1989

High compression image and image sequence coding

The digital representation of an image requires a very large number of bits. This number is even larger for an image sequence. The goal of image coding is to reduce this number, as much as possible, and reconstruct a faithful duplicate of the original picture or image sequence. Early efforts in image coding, solely guided by information theory, led to a plethora of methods. The compression ratio reached a plateau around 10:1 a couple of years ago. Recent progress in the study of the brain mechanism of vision and scene analysis has opened new vistas in picture coding. Directional sensitivity of the neurones in the visual pathway combined with the separate processing of contours and textures has led to a new class of coding methods capable of achieving compression ratios as high as 100:1 for images and around 300:1 for image sequences. Recent progress on some of the main avenues of object-based methods is presented. These second generation techniques make use of contour-texture modeling, new results in neurophysiology and psychophysics and scene analysis.

Kunt, Murat↗
NASA NTRS1995

Prototype Videodisk-Based Part-Task Thermal Imaging Trainer

Thermal images, or infrared images, are representations of the world based on heat, instead of visible light. Research has shown that the resulting thermal image results in perceptual differences leading to difficulties in interpretation (e.g., the determination of slope angle, concavity/convexity), or increased identification latencies. A joint research project between the United States (NASA and U.S. Army) and Israel (Ministry of Defense and Israel Air Force) has resulted in the development of a prototype part-task trainer for the acquisition of perceptual skills associated with thermal imaging usage. This prototype system is videodisk-based under computer control, using recordings of thermal images. A lesson section introduces declarative knowledge, in which the basic physics and heuristics of thermal imagery are taught. An exercise section teaches procedural knowledge, with the user viewing dynamic, actual imagery, with an interactive detection/location determination task. The general philosophy and design of the trainer will be demonstrated.

Brickner, Michael S.↗
NASA NTRS1989

Image gathering and restoration - Information and visual quality

A method is investigated for optimizing the end-to-end performance of image gathering and restoration for visual quality. To achieve this objective, one must inevitably confront the problems that the visual quality of restored images depends on perceptual rather than mathematical considerations and that these considerations vary with the target, the application, and the observer. The method adopted in this paper is to optimize image gathering informationally and to restore images interactively to obtain the visually preferred trade-off among fidelity resolution, sharpness, and clarity. The results demonstrate that this method leads to significant improvements in the visual quality obtained by the traditional digital processing methods. These traditional methods allow a significant loss of visual quality to occur because they treat the design of the image-gathering system and the formulation of the image-restoration algorithm as two separate tasks and fail to account for the transformations between the continuous and the discrete representations in image gathering and reconstruction.

Mccormick, Judith A.↗
NASA NTRS1989

Image wavelet decomposition and applications

The general problem of computer vision has been investigated for more that 20 years and is still one of the most challenging fields in artificial intelligence. Indeed, taking a look at the human visual system can give us an idea of the complexity of any solution to the problem of visual recognition. This general task can be decomposed into a whole hierarchy of problems ranging from pixel processing to high level segmentation and complex objects recognition. Contrasting an image at different representations provides useful information such as edges. An example of low level signal and image processing using the theory of wavelets is introduced which provides the basis for multiresolution representation. Like the human brain, we use a multiorientation process which detects features independently in different orientation sectors. So, images of the same orientation but of different resolutions are contrasted to gather information about an image. An interesting image representation using energy zero crossings is developed. This representation is shown to be experimentally complete and leads to some higher level applications such as edge and corner finding, which in turn provides two basic steps to image segmentation. The possibilities of feedback between different levels of processing are also discussed.

Treil, N.↗
NASA NTRS1991

Image gathering and digital restoration for fidelity and visual quality

The fidelity and resolution of the traditional Wiener restorations given in the prevalent digital processing literature can be significantly improved when the transformations between the continuous and discrete representations in image gathering and display are accounted for. However, the visual quality of these improved restorations also is more sensitive to the defects caused by aliasing artifacts, colored noise, and ringing near sharp edges. In this paper, these visual defects are characterized, and methods for suppressing them are presented. It is demonstrated how the visual quality of fidelity-maximized images can be improved when (1) the image-gathering system is specifically designed to enhance the performance of the image-restoration algorithm, and (2) the Wiener filter is combined with interactive Gaussian smoothing, synthetic high edge enhancement, and nonlinear tone-scale transformation. The nonlinear transformation is used primarily to enhance the spatial details that are often obscurred when the normally wide dynamic range of natural radiance fields is compressed into the relatively narrow dynamic range of film and other displays.

Huck, Friedrich O.↗