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At least 379 records · Page 21

Evaluation of Airborne Visible/Infrared Imaging Spectrometer Data of the Mountain Pass, California carbonatite complex

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data of the Mountain Pass, California carbonatite complex were examined to evaluate the AVIRIS instrument performance and to explore alternative methods of data calibration. Although signal-to-noise estimates derived from the data indicated that the A, B, and C spectrometers generally met the original instrument design objectives, the S/N performance of the D spectrometer was below expectations. Signal-to-noise values of 20 to 1 or lower were typical of the D spectrometer and several detectors in the D spectrometer array were shown to have poor electronic stability. The AVIRIS data also exhibited periodic noise, and were occasionally subject to abrupt dark current offsets. Despite these limitations, a number of mineral absorption bands, including CO3, Al-OH, and unusual rare earth element bands, were observed for mine areas near the main carbonatite body. To discern these bands, two different calibration procedures were applied to remove atmospheric and solar components from the remote sensing data. The two procedures, referred to as the single spectrum and the flat field calibration methods gave distinctly different results. In principle, the single spectrum method should be more accurate; however, additional fieldwork is needed to rigorously determine the degree of calibration success.

Crowley, James↗

The Spectral Image Processing System (SIPS) - Interactive visualization and analysis of imaging spectrometer data

The Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, has developed a prototype interactive software system called the Spectral Image Processing System (SIPS) using IDL (the Interactive Data Language) on UNIX-based workstations. SIPS is designed to take advantage of the combination of high spectral resolution and spatial data presentation unique to imaging spectrometers. It streamlines analysis of these data by allowing scientists to rapidly interact with entire datasets. SIPS provides visualization tools for rapid exploratory analysis and numerical tools for quantitative modeling. The user interface is X-Windows-based, user friendly, and provides 'point and click' operation. SIPS is being used for multidisciplinary research concentrating on use of physically based analysis methods to enhance scientific results from imaging spectrometer data. The objective of this continuing effort is to develop operational techniques for quantitative analysis of imaging spectrometer data and to make them available to the scientific community prior to the launch of imaging spectrometer satellite systems such as the Earth Observing System (EOS) High Resolution Imaging Spectrometer (HIRIS).

Kruse, F. A.↗

Characterization and comparison of Landsat-4 and Landsat-5 Thematic Mapper data

Engineering analyses of Thematic Mapper (TM) image data have been conducted, giving particular attention to the radiometric characterization of the sensor. While the data in general were found to be excellent, anomalies do exist in the data from both Landsat-4 and Landsat-5 TM. A summary is provided of the Landsat-4 TM image data. The present paper concentrates, however, on recent analyses of Landsat-5 TM data and comparisons of the radiometry of the two sensors. One of the specific topics covered is within-line droop, a phenomenon whereby the signal levels of the sensor change systematically during the active scan. Attention is also given to scan-correlated level shifts, an effect which raises or lowers the signal level of all pixels in a scan line or set of scan lines. A comparison of Landsat-4 and Landsat-5 radiometric corrections is also discussed.

Metzler, M. D.↗

Characterization and Comparison of LANDSAT-4 and LANDSAT-5 Thematic Mapper Data

Engineering analyses of Thematic Mapper (TM) image data have been conducted, giving particular attention to the radiometric characterization of the sensor. While the data in general were found to be excellent, anomalies do exist in the data from both LANDSAT-4 and LANDSAT-5 TM. A summary is provided of the LANDSAT-5 TM image data. Recent analyses of LANDSAT-5 TM data and comparisons of the radiometry of the two sensors are emphasized. One of the specific topics covered is within-line droop, a phenomenon whereby the signal levels of the sensor change systematically during the active scan. Attention is also given to scan-correlated level shifts, an effect which raises or lowers the signal level of all pixels in a scan line or set of scan lines. A comparison of LANDSAT-4 and LANDSAT-5 radiometric corrections is also discussed.

Malila, W. A.↗

Measuring the Conditional Luminosity and Stellar Mass Functions of Galaxies by Combining the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 Data

In this investigation, we leverage the combination of the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 data sets to estimate the conditional luminosity functions and conditional stellar mass functions (CLFs and CSMFs) of galaxies across various halo mass bins and redshift ranges. To support our analysis, we utilize a realistic DESI mock galaxy redshift survey (MGRS) generated from a high-resolution Jiutian simulation. An extended halo-based group finder is applied to both MGRS catalogs and DESI observation. By comparing the r- and z-band luminosity functions (LFs) and stellar mass functions (SMFs) derived using both photometric and spectroscopic data, we quantified the impact of photometric redshift (photo-z) errors on the galaxy LFs and SMFs, especially in the low-redshift bin at the low-luminosity/mass end. By conducting prior evaluations of the group finder using MGRS, we successfully obtain a set of CLF and CSMF measurements from observational data. We find that at low redshift, the faint-end slopes of CLFs and CSMFs below ~10 9 h –2 L ⊙ (or h –2 M ⊙ ) evince a compelling concordance with the subhalo mass functions. After correcting the cosmic variance effect of our local Universe following Chen et al., the faint-end slopes of the LFs/SMFs turn out to also be in good agreement with the slope of the halo mass function.

79 ASTRONOMY AND ASTROPHYSICS↗

Holographic, particle imaging and data reduction at Spectron Development Laboratores

Spectron has been deeply involved in the development and use of a wide variety of particle and flow diagnostic, electro optical instruments. Holography and imaging systems have played an important role in this work, but the extraction of data from images and holograms have always presented a limit to their use. Systems and techniques were devised to speed up and automate the extraction of data from holographic and conventional interferograms, particle images and holograms, and other types of optical flow visualization techniques. An IBM/AI based image analyzer was developed that is capable of automatically analyzing many useful image types including interferograms. A key feature of this system is the low total cost of the required hardware. In the particle field work, a commercial diffraction field analyzer was adopted to the image reconstructed from a hologram. This could expand the use of holography in particle diagnostics greatly.

Trolinger, James D.↗

Comparison of Landsat Thematic Mapper and Geophysical and Environmental Research Imaging Spectrometer data for the Cuprite mining district, Esmeralda, and Nye counties, Nevada

Landsat TM images and Geophysical and Environmental Research Imaging Spectrometer (GERIS) data were analyzed for the Cuprite mining district and compared to available geologic and alteration maps of the area. The TM data, with 30 m resolution and 6 broadbands, allowed discrimination of general mineral groups. Clay minerals, playa deposits, and unaltered rocks were mapped as discrete spectral units using the TM data, but specific minerals were not determined, and definition of the individual alteration zones was not possible. The GERIS, with 15 m spatial resolution and 63 spectral bands, permitted construction of complete spectra and identification of specific minerals. Detailed spectra extracted from the images provided the ability to identify the minerals alunite, kaolinite, hematite, and buddingtonite by their spectral characteristics. The GERIS data show a roughly concentrically zoned hydrothermal system. The mineralogy mapped with the aircraft system conforms to previous field and multispectral image mapping. However, identification of individual minerals and spatial display of the dominant mineralogy add information that can be used to help determine the morphology and genetic origin of the hydrothermal system.

Kierein-Young, Kathryn S.↗

Digital visual communications using a Perceptual Components Architecture

The next era of space exploration will generate extraordinary volumes of image data, and management of this image data is beyond current technical capabilities. We propose a strategy for coding visual information that exploits the known properties of early human vision. This Perceptual Components Architecture codes images and image sequences in terms of discrete samples from limited bands of color, spatial frequency, orientation, and temporal frequency. This spatiotemporal pyramid offers efficiency (low bit rate), variable resolution, device independence, error-tolerance, and extensibility.

Watson, Andrew B.↗

Subband/Transform MATLAB Functions For Processing Images

SUBTRANS software is package of routines implementing image-data-processing functions for use with MATLAB*(TM) software. Provides capability to transform image data with block transforms and to produce spatial-frequency subbands of transformed data. Functions cascaded to provide further decomposition into more subbands. Also used in image-data-compression systems. For example, transforms used to prepare data for lossy compression. Written for use in MATLAB mathematical-analysis environment.

Glover, D.↗

Autocorrelation and regularization in digital images. I - Basic theory

Spatial structure occurs in remotely sensed images when the imaged scenes contain discrete objects that are identifiable in that their spectral properties are more homogeneous within than between them and other scene elements. The spatial structure introduced is manifest in statistical measures such as the autocovariance function and variogram associated with the scene, and it is possible to formulate these measures explicitly for scenes composed of simple objects of regular shapes. Digital images result from sensing scenes by an instrument with an associated point spread function (PSF). Since there is averaging over the PSF, the effect, termed regularization, induced in the image data by the instrument will influence the observable autocovariance and variogram functions of the image data. It is shown how the autocovariance or variogram of an image is a composition of the underlying scene covariance convolved with an overlap function, which is itself a convolution of the PSF. The functional form of this relationship provides an analytic basis for scene inference and eventual inversion of scene model parameters from image data.

Jupp, David L. B.↗

Application of Cloude's target decomposition theorem to polarimetric imaging radar data

We apply Cloude's decomposition to imaging radar polarimetry. We derive the general expressions for the eigenvalues and eigenvectors for the case of terrain with reflection symmetry, and show in detail how the decomposition results can guide the interpretation of scattering from vegetated areas. For multi-frequency polarimetric radar measurements of a clear-cut area, the decomposition leads us to conclude that the vegetation is probably thin compared to even the C-band radar wavelength of 6 cm. For a forested area, we notice an increased amount of even number of reflection scattering at P-band and L-band, probably the result of penetration through the coniferous canopy resulting in trunk-ground double reflection scattering. The scattering for the forested area is still dominated by scattering from randomly oriented cylinders, however. It is found that these cylinders are thicker than in the case of clear-cut areas, leading us to conclude that scattering from the branches probably dominate in this case.

Vanzyl, Jakob J.↗

Synthetic Foveal Imaging Technology

Synthetic Foveal imaging Technology (SyFT) is an emerging discipline of image capture and image-data processing that offers the prospect of greatly increased capabilities for real-time processing of large, high-resolution images (including mosaic images) for such purposes as automated recognition and tracking of moving objects of interest. SyFT offers a solution to the image-data processing problem arising from the proposed development of gigapixel mosaic focal-plane image-detector assemblies for very wide field-of-view imaging with high resolution for detecting and tracking sparse objects or events within narrow subfields of view. In order to identify and track the objects or events without the means of dynamic adaptation to be afforded by SyFT, it would be necessary to post-process data from an image-data space consisting of terabytes of data. Such post-processing would be time-consuming and, as a consequence, could result in missing significant events that could not be observed at all due to the time evolution of such events or could not be observed at required levels of fidelity without such real-time adaptations as adjusting focal-plane operating conditions or aiming of the focal plane in different directions to track such events. The basic concept of foveal imaging is straightforward: In imitation of a natural eye, a foveal-vision image sensor is designed to offer higher resolution in a small region of interest (ROI) within its field of view. Foveal vision reduces the amount of unwanted information that must be transferred from the image sensor to external image-data-processing circuitry. The aforementioned basic concept is not new in itself: indeed, image sensors based on these concepts have been described in several previous NASA Tech Briefs articles. Active-pixel integrated-circuit image sensors that can be programmed in real time to effect foveal artificial vision on demand are one such example. What is new in SyFT is a synergistic combination of recent advances in foveal imaging, computing, and related fields, along with a generalization of the basic foveal-vision concept to admit a synthetic fovea that is not restricted to one contiguous region of an image.

Hoenk, Michael↗

Methods and decision making on a Mars rover for identification of fossils

A system for automated fusion and interpretation of image data from multiple sensors, including multispectral data from an imaging spectrometer is being developed. Classical artificial intelligence techniques and artificial neural networks are employed to make real time decision based on current input and known scientific goals. Emphasis is placed on identifying minerals which could indicate past life activity or an environment supportive of life. Multispectral data can be used for geological analysis because different minerals have characteristic spectral reflectance in the visible and near infrared range. Classification of each spectrum into a broad class, based on overall spectral shape and locations of absorption bands is possible in real time using artificial neural networks. The goal of the system is twofold: multisensor and multispectral data must be interpreted in real time so that potentially interesting sites can be flagged and investigated in more detail while the rover is near those sites; and the sensed data must be reduced to the most compact form possible without loss of crucial information. Autonomous decision making will allow a rover to achieve maximum scientific benefit from a mission. Both a classical rule based approach and a decision neural network for making real time choices are being considered. Neural nets may work well for adaptive decision making. A neural net can be trained to work in two steps. First, the actual input state is mapped to the closest of a number of memorized states. After weighing the importance of various input parameters, the net produces an output decision based on the matched memory state. Real time, autonomous image data analysis and decision making capabilities are required for achieving maximum scientific benefit from a rover mission. The system under development will enhance the chances of identifying fossils or environments capable of supporting life on Mars

Eberlein, Susan↗

Automated Reduction of Data from Images and Holograms

Laser techniques are widely used for the diagnostics of aerodynamic flow and particle fields. The storage capability of holograms has made this technique an even more powerful. Over 60 researchers in the field of holography, particle sizing and image processing convened to discuss these topics. The research program of ten government laboratories, several universities, industry and foreign countries were presented. A number of papers on holographic interferometry with applications to fluid mechanics were given. Several papers on combustion and particle sizing, speckle velocimetry and speckle interferometry were given. A session on image processing and automated fringe data reduction techniques and the type of facilities for fringe reduction was held.

Lee, G.↗

Unreal Engine Testbed for Computer Vision of Tall Lunar Tower Assembly

The Tall Lunar Tower project at the NASA Langley Research Center is focused on the design, modeling, fabrication, and testing of a supervised autonomously assembly engineering development unit for tall lunar towers. The lunar south pole environment poses many challenges for robotic assembly of the tall tower, particularly to computer vision camera systems due to a high-contrast lighting environment. This paper will present an Unreal Engine 5 video game engine Lunar South Pole Lighting Testbed to simulate realistic lunar lighting conditions for synthetic image generation. The fidelity of the simulation environment is investigated by comparing the accuracy of computer vision models trained using synthetic image data and trained from real image data collected in a lunar analog environment.

Unreal Engine↗