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NASA NTRS1989

Cloud cover determination in polar regions from satellite imagery

The objectives are to develop a suitable validation data set for evaluating the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) algorithm for cloud retrieval in polar regions, to identify limitations of current procedures and to explore potential means to remedy them using textural classifiers, and to compare synoptic cloud data from model runs with observations. Toward the first goal, a polar data set consisting of visible, thermal, and passive microwave data was developed. The AVHRR and SMMR data were digitally merged to a polar stereographic projection with an effective pixel size of 5 sq km. With this data set, two unconventional methods of classifying the imagery for the analysis of polar clouds and surfaces were examined: one based on fuzzy sets theory and another based on a trained neural network. An algorithm for cloud detection was developed from an early test version of the ISCCP algorithm. This algorithm includes the identification of surface types with passive microwave, then temporal tests at each pixel location in the cloud detection phase. Cloud maps and clear sky radiance composites for 5 day periods are produced. Algorithm testing and validation was done with both actural AVHRR/SMMR data, and simulated imagery. From this point in the algorithm, groups of cloud pixels are examined for their spectral and textural characteristics, and a procedure is developed for the analysis of cloud patterns utilizing albedo, IR temperature, and texture. In a completion of earlier work, empirical analyses of arctic cloud cover were explored through manual interpretations of DMSP imagery and compared to U.S. Air Force 3D-nephanalysis. Comparisons of observed cloudiness from existing climatologies to patterns computed by the GISS climate model were also made.

Barry, R. G.↗
NASA NTRS1990

Motion detection in astronomical and ice floe images

Two approaches are presented for establishing correspondence between small areas in pairs of successive images for motion detection. The first one, based on local correlation, is used on a pair of successive Voyager images of the Jupiter which differ mainly in locally variable translations. This algorithm is implemented on a sequential machine (VAX 780) as well as the Massively Parallel Processor (MPP). In the case of the sequential algorithm, the pixel correspondence or match is computed on a sparse grid of points using nonoverlapping windows (typically 11 x 11) by local correlations over a predetermined search area. The displacement of the corresponding pixels in the two images is called the disparities to cubic surfaces. The disparities at points where the error between the computed values and the surface values exceeds a particular threshold are replaced by the surface values. A bilinear interpolation is then used to estimate disparities at all other pixels between the grid points. When this algorithm was applied at the red spot in the Jupiter image, the rotating velocity field of the storm was determined. The second method of motion detection is applicable to pairs of images in which corresponding areas can experience considerable translation as well as rotation.

Manohar, M.↗
NASA NTRS1990

The analysis of polar clouds from AVHRR satellite data using pattern recognition techniques

The cloud cover in a set of summertime and wintertime AVHRR data from the Arctic and Antarctic regions was analyzed using a pattern recognition algorithm. The data were collected by the NOAA-7 satellite on 6 to 13 Jan. and 1 to 7 Jul. 1984 between 60 deg and 90 deg north and south latitude in 5 spectral channels, at the Global Area Coverage (GAC) resolution of approximately 4 km. This data embodied a Polar Cloud Pilot Data Set which was analyzed by a number of research groups as part of a polar cloud algorithm intercomparison study. This study was intended to determine whether the additional information contained in the AVHRR channels (beyond the standard visible and infrared bands on geostationary satellites) could be effectively utilized in cloud algorithms to resolve some of the cloud detection problems caused by low visible and thermal contrasts in the polar regions. The analysis described makes use of a pattern recognition algorithm which estimates the surface and cloud classification, cloud fraction, and surface and cloudy visible (channel 1) albedo and infrared (channel 4) brightness temperatures on a 2.5 x 2.5 deg latitude-longitude grid. In each grid box several spectral and textural features were computed from the calibrated pixel values in the multispectral imagery, then used to classify the region into one of eighteen surface and/or cloud types using the maximum likelihood decision rule. A slightly different version of the algorithm was used for each season and hemisphere because of differences in categories and because of the lack of visible imagery during winter. The classification of the scene is used to specify the optimal AVHRR channel for separating clear and cloudy pixels using a hybrid histogram-spatial coherence method. This method estimates values for cloud fraction, clear and cloudy albedos and brightness temperatures in each grid box. The choice of a class-dependent AVHRR channel allows for better separation of clear and cloudy pixels than does a global choice of a visible and/or infrared threshold. The classification also prevents erroneous estimates of large fractional cloudiness in areas of cloudfree snow and sea ice. The hybrid histogram-spatial coherence technique and the advantages of first classifying a scene in the polar regions are detailed. The complete Polar Cloud Pilot Data Set was analyzed and the results are presented and discussed.

Smith, William L.↗
NASA NTRS1988

On-line object feature extraction for multispectral scene representation

A new on-line unsupervised object-feature extraction method is presented that reduces the complexity and costs associated with the analysis of the multispectral image data and data transmission, storage, archival and distribution. The ambiguity in the object detection process can be reduced if the spatial dependencies, which exist among the adjacent pixels, are intelligently incorporated into the decision making process. The unity relation was defined that must exist among the pixels of an object. Automatic Multispectral Image Compaction Algorithm (AMICA) uses the within object pixel-feature gradient vector as a valuable contextual information to construct the object's features, which preserve the class separability information within the data. For on-line object extraction the path-hypothesis and the basic mathematical tools for its realization are introduced in terms of a specific similarity measure and adjacency relation. AMICA is applied to several sets of real image data, and the performance and reliability of features is evaluated.

Ghassemian, Hassan↗
NASA NTRS1990

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

Key, J.↗
NASA NTRS1989

High resolution decoding techniques and single-chip decoders for multi-anode microchannel arrays

While the pixel size in a standard multianode microchannel array (MAMA) photon-counting detector is determined by the spacing of the anode array, the factor most fundamentally limiting pixel resolution is the spacing of the channels in the microchannel plate. Detector resolution can be improved by means of digitization followed by a centroiding procedure. The decoding hardware and the techniques for enhanced pixel resolution are presently discussed with a view to the factors of speed and complexity. A single-chip CMOS gate-array implementation of the decoder is devised and compared with existing multichip decoders' performance.

Kasle, David B.↗
NASA NTRS1989

Satellite mapping of Nile Delta coastal changes

Multitemporal, multispectral scanner (MSS) landsat data have been used to monitor erosion and sedimentation along the Rosetta Promontory of the Nile Delta. These processes have accelerated significantly since the completion of the Aswan High Dam in 1964. Digital differencing of four MSS data sets, using standard algorithms, show that changes observed over a single year period generally occur as strings of single mixed pixels along the coast. Therefore, these can only be used qualitatively to indicate areas where changes occur. Areas of change recorded over a multi-year period are generally larger and thus identified by clusters of pixels; this reduces errors introduced by mixed pixels. Satellites provide a synoptic perspective utilizing data acquired at frequent time intervals. This permits multiple year monitoring of delta evolution on a regional scale.

Blodget, H. W.↗
NASA NTRS1990

Deep narrow band imagery of the diffuse ISM in M33

Very deep narrow band images were obtained for several fields in the local group spiral galaxy M33 using a wide field reimaging Charge Coupled Device (CCD) camera on the 1.5 m telescope at Palomar Observatory. The reimaging system uses a 306 mm collimator and a 58 mm camera lens to put a 16 minute by 16 minute field onto a Texas Instruments 800 x 800 pixel CCD at a resolution of 1.2 arcseconds pixel (-1). The overall system is f/1.65. Images were obtained in the light of H alpha (S II) lambda lambda 6717, 6731, (O III) lambda 5007, and line-free continuum bands 100A wide, centered at 6450A and 5100A. Assuming a distance of 600 kpc to M33 (Humphreys 1980, Ap. J., 241, 587), this corresponds to a linear scale of 3.5 pc pixel (-1), and a field size of 2.8 kpc x 2.8 kpc. Researchers discuss the H alpha imagery of a field centered approx. equal to 8 minutes NE of the nucleus, including the supergiant HII region complex NGC 604. Two 2000 second H alpha images and two 300 second red continuum images were obtained of two slightly offset fields. The fields were offset to allow for discrimination between real emission and possible artifacts in the images. All images were resampled to align them with one of the H alpha frames. The continuum images were normalized to the line images using the results of aperture photometry on a grid of stars in the field, then the rescaled continuum data were directly subtracted from the line data.

Hester, J. Jeff↗
NASA NTRS1991

The dust coma of Comet Austin (1989c1)

Thermal-infrared (10 and 20 micron) images of Comet Austin were obtained on UT 30.6 Apr., 1.8, 2.8, and 3.6 May 1990. The NASA-Marshall Space Flight Center 20 pixel bolometer array at the NASA 3 meter Infrared Telescope Facility in Hawaii was used. The 10.8 micron (FWHM = 5.3 microns) maps were obtained with maximum dimensions of 113 arcsec (57,500 km) in RA and 45 arcsec (23,000 km) in declination, with a pixel size of 4.2 x 4.2 arcsec. A smaller, 45 x 18 arcsec, map was obtained in the 19.2 micron (FWHM = 5.2 microns) bandpass. At the time of these observations Comet Austin's heliocentric and geocentric distances were 0.7 and 0.5 AU respectively. The peak flux density (within the brightest pixel) was 23 + or - 2 Janskys for the first three dates and only marginally lower the last day; i.e., within the observational uncertainties no evidence was found for day-to-day variability like that observed in Comet Halley. A dynamical analysis of the morphology of the extended dust emission is used to constrain the size distribution and production rate of the dust particles. The results of this analysis are compared with similar studies carried out on comets P/Giacobini-Zinner, P/Brorsen-Metcalf, P/Halley, P/Tempel 2, and Wilson (1987).

Campins, Humberto↗
NASA NTRS1990

The effects of stellar age and metallicity on the infrared emission in the Magellanic Clouds

Infrared Astronomical Satellite (IRAS) maps of the Magellanic Clouds smoothed to a 5-min angular resolution and young star catalogs are used to study the effects of stellar age and metallicity on the infrared emission of these galaxies. The construction of the stellar catalog is described, along with the conversion from the observational to the theoretical temperature-luminosity diagram and the derivation of stellar ages. The infrared color-color diagram of the Clouds is investigated, and the effect of stellar age on their infrared emission is investigated. The effects of the UV radiation field and of the metallicity on the infrared emission are also considered with emphasis on the influence of such parameters as gas-to-dust ratio on the infrared colors. It is shown that the far-infrared fluxes of individual pixels in the Clouds' maps follow the same behavior as the integrated emission of normal galaxies in the IRAS color-color diagram and that the precise position of a particular pixel depends on the age of the youngest star in that pixel.

Sauvage, M.↗
NASA NTRS1991

Multiple image SAR shape-from-shading

A technique for combining radar image shape-from-shading with stereo radargrammetry to produce terrain surface models using multiple SAR images is described. This technique is expected to be of use to reconstruct surface shape from Magellan images of planet Venus, and to refine the results of terrestrial radar measurements. Local variation in pixel shading is an indicator of terrain slope changes. This variation in pixel shading offers an opportunity for increasing the detail of terrain mapping over that which is available from stereo radargrammetry alone. Shape-from-shading can potentially provide a relative change in height at each pixel. This leads to a dense set of height measurements and a more faithful rendition of the local terrain shapes. However, shape-from-shading needs some type of boundary values or external terrain low-frequency information to succeed. These can be obtained from stereo or from altimeter measurements.

Thomas, J.↗
NASA NTRS1990

Functional relation among subpixel canopy cover, ground shadow, and illuminated ground at large sampling scales

The functional relation among subpixel canopy cover, illuminated soil, and shadowed soil, which progressively develops with increasing pixel size, is investigated for Poisson distributed plants using a geometric canopy simulation model. An analytical relation among cover components is shown to be applicable when the scale of the pixel is much larger than the scale of the plant and ground shadow. The analysis is facilitated through the use of a nondimensional solar-geometric similarity parameter, eta, equal to the ratio of the area of one plant canopy to its associated ground shadow area, as viewed from nadir. A sampling scale ratio, defined as the ratio of the area of the pixel to the mean area of a single plant shadow, is tested as a quantitative criterion to evaluate when the functional relation among subpixel components occurs. The results of a remote sensing experiment over a natural conifer landscape provide preliminary confirmation of the theoretical analysis.

Jasinski, Michael F.↗
NASA NTRS1990

Scientific grade CCDs from EG & G Reticon

The design and performance of three scientific grade CCDs are summarized: a 1200 x 400 astronomical array of 27 x 27 sq micron pixels, a 512 x 512 scientific array of 27 x 27 sq micron pixels and a 404 x 64 VNIR array of 52 x 52 sq micron pixels. Each of the arrays is fabricated using a four phase, double poly, buried n-channel, multi-pinned phase CCD process. Performance data for each sensor is presented.

Cizdziel, Philip J.↗
NASA NTRS1991

Using image area to control CCD systematic errors in spaceborne photometric and astrometric time-series measurements

The effect of some systematic errors for high-precision time-series spaceborne photometry and astrometry has been investigated with a CCD as the detector. The 'pixelization' of the images causes systematic error in astrometric measurements. It is shown that this pixelization noise scales as image radius r exp -3/2. Subpixel response gradients, not correctable by the 'flat field', and in conjunction with telescope pointing jitter, introduce further photometric and astrometric errors. Subpixel gradients are modeled using observed properties of real flat fields. These errors can be controlled by having an image span enough pixels. Large images are also favored by CCD dynamic range considerations. However, magnified stellar images can overlap, thus introducing another source of systematic error. An optimum image size is therefore a compromise between these competing factors.

Buffington, Andrew↗
NASA NTRS1992

Optical Correlator With Complex Holographic Filter

Experimental real-time optical correlator includes complex-valued holographic filter computed from one of two input scenes. Made more tolerant of errors in patterns to be recognized. Filter function essentially coded hologram computed by Burchhardt's method, in which complex value of each pixel of fast Fourier transform of image represented by three real, nonnegative numbers. In generating optical correlator according to method, phasor of each pixel in Fourier transform represented by intensities in three adjacent pixels.

Chao, Tien-Hsin↗
NASA NTRS1991

Programmable remapper for image processing

A video-rate coordinate remapper includes a memory for storing a plurality of transformations on look-up tables for remapping input images from one coordinate system to another. Such transformations are operator selectable. The remapper includes a collective processor by which certain input pixels of an input image are transformed to a portion of the output image in a many-to-one relationship. The remapper includes an interpolative processor by which the remaining input pixels of the input image are transformed to another portion of the output image in a one-to-many relationship. The invention includes certain specific transforms for creating output images useful for certain defects of visually impaired people. The invention also includes means for shifting input pixels and means for scrolling the output matrix.

Juday, Richard D.↗
NASA NTRS1992

A 5-18 micron array camera for high-background astronomical imaging

A new infrared array camera system using a Hughes/SBRC 58 x 62 pixel hybrid Si:Ga array detector has been successfully applied to high-background 5-18-micron astronomical imaging observations. The off-axis reflective optical system minimizes thermal background loading and produces diffraction-limited images with negligible spatial distortion. The noise equivalent flux density (NEFD) of the camera at 10 microns on the 3.0-m NASA/Infrared Telescope Facility with broadband interference filters and 0.26 arcsec pixel is NEFD = 0.01 Jy/sq rt min per pixel (1sigma), and it operates at a frame rate of 30 Hz with no compromise in observational efficiency. The electronic and optical design of the camera, its photometric characteristics, examples of observational results, and techniques for successful array imaging in a high- background astronomical application are discussed.

Gezari, Daniel Y.↗
NASA NTRS1993

An investigative study of multispectral data compression for remotely-sensed images using vector quantization and difference-mapped shift-coding

A study is conducted to investigate the effects and advantages of data compression techniques on multispectral imagery data acquired by NASA's airborne scanners at the Stennis Space Center. The first technique used was vector quantization. The vector is defined in the multispectral imagery context as an array of pixels from the same location from each channel. The error obtained in substituting the reconstructed images for the original set is compared for different compression ratios. Also, the eigenvalues of the covariance matrix obtained from the reconstructed data set are compared with the eigenvalues of the original set. The effects of varying the size of the vector codebook on the quality of the compression and on subsequent classification are also presented. The output data from the Vector Quantization algorithm was further compressed by a lossless technique called Difference-mapped Shift-extended Huffman coding. The overall compression for 7 channels of data acquired by the Calibrated Airborne Multispectral Scanner (CAMS), with an RMS error of 15.8 pixels was 195:1 (0.41 bpp) and with an RMS error of 3.6 pixels was 18:1 (.447 bpp). The algorithms were implemented in software and interfaced with the help of dedicated image processing boards to an 80386 PC compatible computer. Modules were developed for the task of image compression and image analysis. Also, supporting software to perform image processing for visual display and interpretation of the compressed/classified images was developed.

Jaggi, S.↗