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NASA NTRS1989

Context dependent anti-aliasing image reconstruction

Image Reconstruction has been mostly confined to context free linear processes; the traditional continuum interpretation of digital array data uses a linear interpolator with or without an enhancement filter. Here, anti-aliasing context dependent interpretation techniques are investigated for image reconstruction. Pattern classification is applied to each neighborhood to assign it a context class; a different interpolation/filter is applied to neighborhoods of differing context. It is shown how the context dependent interpolation is computed through ensemble average statistics using high resolution training imagery from which the lower resolution image array data is obtained (simulation). A quadratic least squares (LS) context-free image quality model is described from which the context dependent interpolation coefficients are derived. It is shown how ensembles of high-resolution images can be used to capture the a priori special character of different context classes. As a consequence, a priori information such as the translational invariance of edges along the edge direction, edge discontinuity, and the character of corners is captured and can be used to interpret image array data with greater spatial resolution than would be expected by the Nyquist limit. A Gibb-like artifact associated with this super-resolution is discussed. More realistic context dependent image quality models are needed and a suggestion is made for using a quality model which now is finding application in data compression.

Beaudet, Paul R.↗

NASA NTRS1989

Neural networks for data compression and invariant image recognition

An approach to invariant image recognition (I2R), based upon a model of biological vision in the mammalian visual system (MVS), is described. The complete I2R model incorporates several biologically inspired features: exponential mapping of retinal images, Gabor spatial filtering, and a neural network associative memory. In the I2R model, exponentially mapped retinal images are filtered by a hierarchical set of Gabor spatial filters (GSF) which provide compression of the information contained within a pixel-based image. A neural network associative memory (AM) is used to process the GSF coded images. We describe a 1-D shape function method for coding of scale and rotationally invariant shape information. This method reduces image shape information to a periodic waveform suitable for coding as an input vector to a neural network AM. The shape function method is suitable for near term applications on conventional computing architectures equipped with VLSI FFT chips to provide a rapid image search capability.

Gardner, Sheldon↗

NASA NTRS1989

A programmable image compression system

A programmable image compression system which has the necessary flexibility to address diverse imaging needs is described. It can compress and expand single frame video images (monochrome or color) as well as documents and graphics (black and white or color) for archival or transmission applications. Through software control, the compression mode can be set for lossless or controlled quality coding; the image size and bit depth can be varied; and the image source and destination devices can be readily changed. Despite the large combination of image data types, image sources, and algorithms, the system provides a simple consistent interface to the programmer. This system (OPTIPAC) is based on the TITMS320C25 digital signal processing (DSP) chip and has been implemented as a co-processor board for an IBM PC-AT compatible computer. The underlying philosophy can readily be applied to different hardware platforms. By using multiple DSP chips or incorporating algorithm specific chips, the compression and expansion times can be significantly reduced to meet performance requirements.

Farrelle, Paul M.↗

NASA NTRS1990

Satellite image analysis using neural networks

The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, SIANN (Satellite Image Analysis using Neural Networks) that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed was completed and applied to climatological data.

Sheldon, Roger A.↗

NASA NTRS1990

Synthetic-aperture-radar imaging of the ocean surface using the slightly-rough facet model and a full surface-wave spectrum

A new model of synthetic-aperture-radar (SAR) imaging of ocean waves is described. The model is based on mapping individual, slightly-rough surface facets through the SAR processor into the image and responses of the facets in the image domain are added together coherently to give the composite image. A windowing technique allows both the orbital motion and the phase velocity of the long waves to be included. It is determined that the azimuthal cut-off is due to a smearing of the response of the facets in the image induced by the random orbital motion of the intermediate large-scale waves and that the focus adjustment that gives the greatest image contrast is half the phase velocity of the dominant long wave. The optimal processing technique, however, may consist of spatially offsetting the multiple looks on the image domain to compensate the propagation of long waves during the integration time of the SAR.

West, James C.↗

NASA NTRS1990

Recognition of simple visual images using a sparse distributed memory: Some implementations and experiments

Previously, a method was described of representing a class of simple visual images so that they could be used with a Sparse Distributed Memory (SDM). Herein, two possible implementations are described of a SDM, for which these images, suitably encoded, will serve both as addresses to the memory and as data to be stored in the memory. A key feature of both implementations is that a pattern that is represented as an unordered set with a variable number of members can be used as an address to the memory. In the 1st model, an image is encoded as a 9072 bit string to be used as a read or write address; the bit string may also be used as data to be stored in the memory. Another representation, in which an image is encoded as a 256 bit string, may be used with either model as data to be stored in the memory, but not as an address. In the 2nd model, an image is not represented as a vector of fixed length to be used as an address. Instead, a rule is given for determining which memory locations are to be activated in response to an encoded image. This activation rule treats the pieces of an image as an unordered set. With this model, the memory can be simulated, based on a method of computing the approximate result of a read operation.

Jaeckel, Louis A.↗

NASA NTRS1991

Infrared imaging - A validation technique for computational fluid dynamics codes used in STOVL applications

The need for a validation technique for computational fluid dynamics (CFD) codes in STOVL applications has led to research efforts to apply infrared thermal imaging techniques to visualize gaseous flow fields. Specifically, a heated, free-jet test facility was constructed. The gaseous flow field of the jet exhaust was characterized using an infrared imaging technique in the 2 to 5.6 micron wavelength band as well as conventional pitot tube and thermocouple methods. These infrared images are compared to computer-generated images using the equations of radiative exchange based on the temperature distribution in the jet exhaust measured with the thermocouple traverses. Temperature and velocity measurement techniques, infrared imaging, and the computer model of the infrared imaging technique are presented and discussed. From the study, it is concluded that infrared imaging techniques coupled with the radiative exchange equations applied to CFD models are a valid method to qualitatively verify CFD codes used in STOVL applications.

Hardman, R. R.↗

NASA NTRS1990

Information theoretical assessment of digital imaging systems

The end-to-end performance of image gathering, coding, and restoration as a whole is considered. This approach is based on the pivotal relationship that exists between the spectral information density of the transmitted signal and the restorability of images from this signal. The information-theoretical assessment accounts for (1) the information density and efficiency of the acquired signal as a function of the image-gathering system design and the radiance-field statistics, and (2) the improvement in information efficiency and data compression that can be gained by combining image gathering with coding to reduce the signal redundancy and irrelevancy. It is concluded that images can be restored with better quality and from fewer data as the information efficiency of the data is increased. The restoration correctly explains the image gathering and coding processes and effectively suppresses the image-display degradations.

John, Sarah↗

NASA NTRS1991

Restoration of color images by multichannel Kalman filtering

A Kalman filter for optimal restoration of multichannel images is presented. This filter is derived using a multichannel semicausal image model that includes between-channel degradation. Both stationary and nonstationary image models are developed. This filter is implemented in the Fourier domain and computation is reduced from O(Lambda3N3M4) to O(Lambda3N3M2) for an M x M N-channel image with degradation length Lambda. Color (red, green, and blue (RGB)) images are used as examples of multichannel images, and restoration in the RGB and YIQ domains is investigated. Simulations are presented in which the effectiveness of this filter is tested for different types of degradation and different image model estimates.

Galatsanos, Nikolas P.↗

NASA NTRS1993

Software For Computing Image Ratios

RATIO_TOOL is interactive computer program for viewing and analyzing large sets of multispectral image data created by imaging spectrometer. Uses ratios between intensities in different spectral bands in order to spot significant areas of interest within multispectral image. Each image band viewed iteratively, or selected image band of set of data requested and displayed. When image ratios computed, result displayed as grayscale image. Written in C Language.

Yates, Gigi L.↗

NASA NTRS1993

Study of optical techniques for the Ames unitary wind tunnel: Digital image processing, part 6

A survey of digital image processing techniques and processing systems for aerodynamic images has been conducted. These images covered many types of flows and were generated by many types of flow diagnostics. These include laser vapor screens, infrared cameras, laser holographic interferometry, Schlieren, and luminescent paints. Some general digital image processing systems, imaging networks, optical sensors, and image computing chips were briefly reviewed. Possible digital imaging network systems for the Ames Unitary Wind Tunnel were explored.

Lee, George↗

NASA NTRS1993

Wide-field direct CCD observations supporting the Astro-1 Space Shuttle mission's Ultraviolet Imaging Telescope

Wide field direct CCD observations are being obtained to support and complement the vacuum-ultraviolet (VUV) images provided by Astro's Ultraviolet Imaging Telescope (UIT) during a Space Shuttle flight in December 1990. Because of the wide variety of projects addressed by UIT, the fields observed include (1) galactic supernova remnants such as the Cygnus Loop and globular clusters such as Omega Cen and M79; (2) the Magellanic Clouds, M33, M81, and other galaxies in the Local Group; and (3) rich clusters of galaxies, principally the Perseus cluster and Abell 1367. Ground-based observations have been obtained for virtually all of the Astro-1 UIT fields. The optical images allow identification of individual UV sources in each field and provide the long baseline in wavelength necessary for accurate analysis of UV-bright sources. To facilitate use of our optical images for analysis of UIT data and other projects, we plan to archive them, with the UIT images, at the National Space Science Data Center (NSSDC), where they will be universally accessible via anonymous FTP. The UIT, one of three telescopes comprising the Astro spacecraft, is a 38-cm f/9 Ritchey-Chretien telescope on which high quantum efficiency, solar-blind image tubes are used to record VUV images on photographic film. Five filters with passbands centered between 1250A and 2500A provide both VUV colors and a measurement of extinction via the 2200A dust feature. The resulting calibrated VUV pictures are 40 arcminutes in diameter at 2.5 arcseconds resolution. The capabilities of UIT, therefore, complement HST's WFPC: the latter has 40 times greater collecting area, while UIT's usable field has 170 times WFPC's field area.

Hintzen, Paul↗

NASA NTRS1993

Filtering Interpolators for Image Comparison Algorithms

Comparing two or more images, either by differencing or ratioing, is important to many remote sensing problems. Because the pixel sample points for the images are (almost) always separated by some nonzero shift, a resampling, or interpolation, process must be performed if one image is to be accurately compared to another. Considered in Fourier space, an interpolator acts as a filter that attenuates some frequencies (usually high) of the image. Thus, when the shifted and unshifted images are compared, the former has been filtered, while the latter has not; the effect of this difference is called interpolation error. The key idea of this paper is to apply a filter to the unshifted image that matches the filtering effect of applying the interpolator to the shifted image, thereby drastically reducing interpolation error. The resulting interpolators, called filtering interpolators, are derived and discussed in detail elsewhere. Basic results will be given in this presentation.

Lucke, R. L.↗

NASA NTRS1993

Near- and mid-infrared imaging of the planetary nebulae BD +30 deg 3639 and IC 418

We present near- and mid-IR images of the planetary nebulae BD +30 deg 3639 and IC 418, with a unique combination of high spatial and spectral resolution. The mid-IR images were obtained with MIRAC, a new IR array camera. For BD +30 deg 3639, the mid-IR images at 10.0, 11.2, 12.4, 12.8, and 13.2 microns have allowed us to separate the various spectral emission components such as the broad UIR features, the 12.8-micron forbidden Ne II emission feature, and continuum emission, to determine the distribution of these components in the nebula. For IC 418, we have obtained high-resolution images in both the near- and mid-IR. The images in the near-IR at J, H, and K are important for determining the source of the IR excess; one component of the excess is located near the central star. We have also imaged the halo emission at H and K, which has been detected in earlier studies, and have determined its spatial extent. The mid-IR images at 9.8 and 11.7 microns show continuum emission coincident with the ionized zone and suggest that SiC emission originates from the region near the central star.

Hora, Joseph L.↗

NASA NTRS1991

Multiresponse imaging system design for improved resolution

Multiresponse imaging is a process that acquires A images, each with a different optical response, and reassembles them into a single image with an improved resolution that can approach 1/sq rt A times the photodetector-array sampling lattice. Our goals are to optimize the performance of this process in terms of the resolution and fidelity of the restored image and to assess the amount of information required to do so. The theoretical approach is based on the extension of both image restoration and rate-distortion theories from their traditional realm of signal processing to image processing which includes image gathering and display.

Alter-Gartenberg, Rachel↗

NASA NTRS1994

Computer Program Helps Enhance Images

Pixel Pusher is Macintosh application program for viewing and performing minor enhancements on imagery. Works with color images digitized to 8 bits. Reads image files in JPL's two primary image formats VICAR and PDS as well as in Macintosh PICT format. VICAR (NPO-18076) handles array of image-processing capabilities used for variety of applications, including processing of biomedical images, cartography, imaging of Earth resources, and geological exploration. Pixel Pusher also imports color lookup tables in VICAR format for viewing images in pseudocolor (256 colors). Written in Symantec's Think C.

Stanfill, Daniel F., IV↗

NASA NTRS1993

Data analysis for GOPEX image frames

The data analysis based on the image frames received at the Solid State Imaging (SSI) camera of the Galileo Optical Experiment (GOPEX) demonstration conducted between 9-16 Dec. 1992 is described. Laser uplink was successfully established between the ground and the Galileo spacecraft during its second Earth-gravity-assist phase in December 1992. SSI camera frames were acquired which contained images of detected laser pulses transmitted from the Table Mountain Facility (TMF), Wrightwood, California, and the Starfire Optical Range (SOR), Albuquerque, New Mexico. Laser pulse data were processed using standard image-processing techniques at the Multimission Image Processing Laboratory (MIPL) for preliminary pulse identification and to produce public release images. Subsequent image analysis corrected for background noise to measure received pulse intensities. Data were plotted to obtain histograms on a daily basis and were then compared with theoretical results derived from applicable weak-turbulence and strong-turbulence considerations. Processing steps are described and the theories are compared with the experimental results. Quantitative agreement was found in both turbulence regimes, and better agreement would have been found, given more received laser pulses. Future experiments should consider methods to reliably measure low-intensity pulses, and through experimental planning to geometrically locate pulse positions with greater certainty.

Levine, B. M.↗

NASA NTRS1993

Earth imaging results from Galileo's second encounter

The recent flyby of the Galileo spacecraft en route to Jupiter contributes a unique perspective to our view of our home planet. Imaging activities conducted during the second Earth encounter provide an important opportunity to assess new methods and approaches on familiar territory. These include unique multispectral observations, low light-level imaging (searches for aurorae, lightning and artificial lights on the nightside) and experiments with multiple exposure times to extend the effective radiometric resolution and dynamic range of the camera system. Galileo imaging data has the potential to make important contributions to terrestrial remote sensing. This is because the particular set of filters included in the Solid State Imaging system are not presently incorporated in any currently operating Earth-orbiting sensor system. The visible/near-infrared bandpasses of the SSI filters are well suited to remote sensing of geological, glaciological, botanical, and meteorological phenomena. Data from this and the previous Earth encounter may provide an extremely valuable reference point in time for comparison with similar data expected from EOS or other systems in the future, contributing directly to our knowledge of global change. The highest resolution imaging (0.2 km/pixel) during the December, 1992 encounter occurred over the central Andes; a five filter mosaic of visible and near infrared bands displays the remarkable spectral heterogeneity of this geologically diverse region. As Galileo departed the Earth, cooperative imaging with the Near Infrared Mapping Spectrometer (NIMS) instrument targeted Antarctica, Australia, and Indonesia at 1.0 to 2.5 km/pixel resolutions in the early morning local times near the terminator. The Antarctic data are of particular interest, potentially allowing ice grain size mapping using the 889 and 968 nm filters and providing an important means of calibrating the technique for application to the Galilean satellites. As the spacecraft receded further, regional scale imaging provided data which, along with data from the previous encounter, will enable the production of global multispectral mosaics of Earth in each of the SSI filters.

Greenberg, R.↗