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All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Dependence of image grey values on topography in SIR-B images

This paper focuses on the use of a high resolution digital elevation model (DEM) to aid in rectifying and enhancing synthetic aperture radar images. Using a synthetic backscatter image, the SIR-B images are manually rectified and resampled to remove geometric distortions caused by topography. In a second step, an improved reflectance function of incidence angle is derived from the DEM and the rectified image and this function is used to reduce radiometric effects of topography yielding an albedo image which clearly shows the thematic, as opposed to topographic content of the image. The procedure is tested on four SIR-B images of a scene in Argentina (crossover point) that is imaged under different azimuth and incidence angles. The similarity of the resulting images indicates that the procedure effectively reduces artefacts from the images that are dependent on topography.

Domik, G.↗
NASA NTRS1989

Image understanding and interpretation in microwave diversity imaging

The authors investigate microwave imaging of metallic objects using a diversity method and interpret and predict the reconstructed image from an approach based on analysis of the scattering mechanism and a back-projection algorithm used in image retrieval. The connection between the various scattering mechanisms and the reconstructed images is discussed, what the images represent is interpreted, and a prediction is made as to what the image will look like over given spectral and angular windows. A brief description is given of the microwave diversity imaging system and the formulation of the microwave diversity imaging based on the physical optics approximation. The scattering mechanism of a complex shaped metallic object is then briefly reviewed and an alternate approach to interpreting the reconstructed image based on the understanding of the scattering mechanism and the reconstruction algorithm is given. Several numerical and experimental examples are included to support this interpretation approach.

Li, Hsueh-Jyh↗
NASA NTRS1994

An adaptive technique to maximize lossless image data compression of satellite images

Data compression will pay an increasingly important role in the storage and transmission of image data within NASA science programs as the Earth Observing System comes into operation. It is important that the science data be preserved at the fidelity the instrument and the satellite communication systems were designed to produce. Lossless compression must therefore be applied, at least, to archive the processed instrument data. In this paper, we present an analysis of the performance of lossless compression techniques and develop an adaptive approach which applied image remapping, feature-based image segmentation to determine regions of similar entropy and high-order arithmetic coding to obtain significant improvements over the use of conventional compression techniques alone. Image remapping is used to transform the original image into a lower entropy state. Several techniques were tested on satellite images including differential pulse code modulation, bi-linear interpolation, and block-based linear predictive coding. The results of these experiments are discussed and trade-offs between computation requirements and entropy reductions are used to identify the optimum approach for a variety of satellite images. Further entropy reduction can be achieved by segmenting the image based on local entropy properties then applying a coding technique which maximizes compression for the region. Experimental results are presented showing the effect of different coding techniques for regions of different entropy. A rule-base is developed through which the technique giving the best compression is selected. The paper concludes that maximum compression can be achieved cost effectively and at acceptable performance rates with a combination of techniques which are selected based on image contextual information.

Stewart, Robert J.↗
NASA NTRS2019

GOES-R Solar UltraViolet Imager Extended Coronal Imaging

GOES-16 and GOES-17 each hosts a Solar UltraViolet Imager (SUVI) that images the Sun in six extreme ultraviolet (EUV) wavelengths: 9.4 nm, 13.1nm, 17.1nm, 19.5nm, 28.4nm, and 30.4nm. The SUVI is nominally Sun-pointed and has a four-minute imaging sequence covering all the channels and meeting the dynamic range requirements. Based on the SUVI capabilities observed on-orbit, a campaign to image the extended solar corona was undertaken in 2018. This was performed by off-pointing the SUVI line-of-sight to the left and right of the Sun and producing a composite image by stitching together the off-pointed and the Sun-centered images. The imaging area in the composite is about three times the nominal image area in the East-West direction (about 5 RSun versus 1.8 RSun for nominal images). The campaign was conducted in February (4 hours), June (72 hours), and August-September of 2018 (5 weeks). Results from the campaign indicated the presence of solar corona to three solar radii, even in the quiet Sun part of the solar cycle. NOAA can operationalize this concept by tasking the SUVI on one of GOES-E and GOES-W. Such long-term operation will provide data that is needed to establish the much needed connectivity between the EUV and white light coronagraph data for the CME events.

Extended Coronal↗
NASA NTRS1981

APPLEPIPS /Apple Personal Image Processing System/ - An interactive digital image processing system for the Apple II microcomputer

Recent developments related to microprocessor-based personal computers have made low-cost digital image processing systems a reality. Image analysis systems built around these microcomputers provide color image displays for images as large as 256 by 240 pixels in sixteen colors. Descriptive statistics can be computed for portions of an image, and supervised image classification can be obtained. The systems support Basic, Fortran, Pascal, and assembler language. A description is provided of a system which is representative of the new microprocessor-based image processing systems currently on the market. While small systems may never be truly independent of larger mainframes, because they lack 9-track tape drives, the independent processing power of the microcomputers will help alleviate some of the turn-around time problems associated with image analysis and display on the larger multiuser systems.

Masuoka, E.↗
NASA NTRS1984

Laboratory demonstration of image reconstruction for coherent optical system of modular imaging collectors (COSMIC)

The first physical demonstration of the principle of image reconstruction using a set of images from a diffraction-blurred elongated aperture is reported. This is an optical validation of previous theoretical and numerical simulations of the COSMIC telescope array (coherent optical system of modular imaging collectors). The present experiment utilizes 17 diffraction blurred exposures of a laboratory light source, as imaged by a lens covered by a narrow-slit aperture; the aperture is rotated 10 degrees between each exposure. The images are recorded in digitized form by a CCD camera, Fourier transformed, numerically filtered, and added; the sum is then filtered and inverse Fourier transformed to form the final image. The image reconstruction process is found to be stable with respect to uncertainties in values of all physical parameters such as effective wavelength, rotation angle, pointing jitter, and aperture shape. Future experiments will explore the effects of low counting rates, autoguiding on the image, various aperture configurations, and separated optics.

Traub, W. A.↗
NASA NTRS1987

Combined optimization of image-gathering and image-processing systems for scene feature detection

The relationship between the image gathering and image processing systems for minimum mean squared error estimation of scene characteristics is investigated. A stochastic optimization problem is formulated where the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled and noisy image data. An analytical solution for the optimal characteristic image processor is developed. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristic is scene restoration. Optimal edge detection is investigated using the Laplacian operator x G as the desired characteristic, where G is a two dimensional Gaussian distribution function. It is shown that the optimal edge detector compensates for the blurring introduced by the image gathering optics, and notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition. The optimal image gathering optical transfer function is also investigated and the results of a sensitivity analysis are shown.

Halyo, Nesim↗
NASA NTRS1989

Image interpretation and prediction in microwave diversity imaging

The microwave image of a metallic object is interpreted from a point of view based on the understanding of the interconnection between the scattering mechanisms, the data acquisition system, and the image reconstruction algorithm. From this understanding it is possible to interpret and predict microwave images reconstructed from data collected over specified and angular windows. The connection between a special scattering mechanism, edge diffraction, and its reconstructed image is established. The microwave image of an edge is two bright points whose locations correspond to the end points of the edge if the normal aspect angle is not included in the angular windows; otherwise a line joining the two end points and representing the edge will appear in the image. Experimental images of a trihedral reflector constructed from data collected over different angular windows support this approach to image interpretation and prediction.

Li, Hsueh-Jyh↗
NASA NTRS2016

Image Navigation and Registration Performance Assessment Tool Set for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24-hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24-hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Navigation↗
NASA NTRS2016

Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24 hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Registration↗
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 NTRS1992

Astro-1 ultraviolet imaging of the 30 Doradus and SN 1987A fields with the Ultraviolet Imaging Telescope

A preliminary analysis of Ultraviolet Imaging Telescope (UIT) images in the 30 Doradus region is reported. Photometry was obtained for the 30 Doradus cluster and its UV-bright core, R136, in various UIT bandpasses. It is found that about 14 percent of the total FUV light and about 16 percent of the total near-UV light of the 3-arcmin diameter 30 Doradus cluster originates from the region within 5 arcsec of R136. The UV magnitudes and colors of R136 and other known O and Wolf-Rayet WN stars in the same field were measured. The UIT data, combined with published observations at longer wavelengths, indicate that R136a1, the brightest component of R136, is not a supermassive stars. A qualitative comparison between the UIT images, Einstein X-ray data, IRAS HiRes images, and ground-based CCD images in forbidden O III 5007 A, H-alpha, B, R, U, and Stromgren u is performed. The extended diffuse UV feature detected in the UIT images is correlated with the IR structure seen in the IRAS 60-micron HiRes image, which suggests the existence of large amounts of widely distributed dust in this region.

Cheng, Kwang-Ping↗
NASA NTRS1992

Instrument requirements for imaging the magnetosphere in extreme-ultraviolet and energetic neutral atoms derived from computer-simulated images

Scientific requirements for He(+)(304 A) and energetic neutral atom (ENA) magnetospheric imaging, as well as the derived instrumental requirements are presented. Both ENA imaging of the hot plasma and EUV imaging of the cold plasma are highlighted. The question of the accuracy with which physically significant parameters can be extracted from actual images using computerized algorithms is addressed. An example of an ENA image analyzed by means of the Powell minimization algorithm is given. Automated unfolding of global magnetospheric images is also discussed. A Mercator projection of a model INA image is shown.

Roelof, Edmond C.↗
NASA NTRS1995

Combining image-processing and image compression schemes

An investigation into the combining of image-processing schemes, specifically an image enhancement scheme, with existing compression schemes is discussed. Results are presented on the pyramid coding scheme, the subband coding scheme, and progressive transmission. Encouraging results are demonstrated for the combination of image enhancement and pyramid image coding schemes, especially at low bit rates. Adding the enhancement scheme to progressive image transmission allows enhanced visual perception at low resolutions. In addition, further progressing of the transmitted images, such as edge detection schemes, can gain from the added image resolution via the enhancement.

Greenspan, H.↗
NASA NTRS1996

Single Transducer Ultrasonic Imaging Method that Eliminates the Effect of Plate Thickness Variation in the Image

This article describes a single transducer ultrasonic imaging method that eliminates the effect of plate thickness variation in the image. The method thus isolates ultrasonic variations due to material microstructure. The use of this method can result in significant cost savings because the ultrasonic image can be interpreted correctly without the need for machining to achieve precise thickness uniformity during nondestructive evaluations of material development. The method is based on measurement of ultrasonic velocity. Images obtained using the thickness-independent methodology are compared with conventional velocity and c-scan echo peak amplitude images for monolithic ceramic (silicon nitride), metal matrix composite and polymer matrix composite materials. It was found that the thickness-independent ultrasonic images reveal and quantify correctly areas of global microstructural (pore and fiber volume fraction) variation due to the elimination of thickness effects. The thickness-independent ultrasonic imaging method described in this article is currently being commercialized under a cooperative agreement between NASA Lewis Research Center and Sonix, Inc.

Roth, Don J.↗
NASA NTRS2007

Beam Combination for Stellar Imager and its Application to Full-Aperture Imaging

Stellar Imager (SI) will be a Space-Based telescope consisting of 20 to 30 separated apertures. It is designed for UV/Optical imaging of stellar surfaces and asteroseismology. This report describes details of an alternative optical design for the beam combiner, dubbed the Spatial Frequency Remapper (SFR). It sacrifices the large field of view of the Fizeau combiner. In return, spectral resolution is obtained with a diffraction grating rather than an array of energy-resolving detectors. The SFR design works in principle and has been implemented with MIRC at CHARA for a small number of apertures. Here, we show the number of optical surfaces can be reduced and the concept scales gracefully to the large number of apertures needed for Stellar Imager. We also describe a potential application of this spatial frequency remapping to improved imaging with filled aperture systems. For filled-aperture imaging, the SFR becomes the core of an improved aperture masking system. To date, aperture-masking has produced the best images with ground-based telescopes but at the expense of low sensitivity due to short exposures and discarding most of the light collected by the telescope. This design eliminates the light-loss problem previously claimed to be inherent in all aperture-masking designs. We also argue that at least in principle, the short-integration time limit can also be overcome. With these improvements, it becomes an ideal camera for TPF-C; since it can form speckle-free images in the presence of wavefront errors, it should significantly relax the stability requirements of the current designs.

Mozurkewich, D.↗
NASA NTRS1975

Temporal registration of multispectral digital satellite images using their edge images

An algorithm is described which will form an edge image by detecting the edges of features in a particular spectral band of a digital satellite image. It is capable also of forming composite multispectral edge images. In addition, an edge image correlation algorithm is presented which performs rapid automatic registration of the edge images and, consequently, the grey level images.

Nack, M. L.↗