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At least 181 records · Page 10

A visual detection model for DCT coefficient quantization

The discrete cosine transform (DCT) is widely used in image compression and is part of the JPEG and MPEG compression standards. The degree of compression and the amount of distortion in the decompressed image are controlled by the quantization of the transform coefficients. The standards do not specify how the DCT coefficients should be quantized. One approach is to set the quantization level for each coefficient so that the quantization error is near the threshold of visibility. Results from previous work are combined to form the current best detection model for DCT coefficient quantization noise. This model predicts sensitivity as a function of display parameters, enabling quantization matrices to be designed for display situations varying in luminance, veiling light, and spatial frequency related conditions (pixel size, viewing distance, and aspect ratio). It also allows arbitrary color space directions for the representation of color. A model-based method of optimizing the quantization matrix for an individual image was developed. The model described above provides visual thresholds for each DCT frequency. These thresholds are adjusted within each block for visual light adaptation and contrast masking. For given quantization matrix, the DCT quantization errors are scaled by the adjusted thresholds to yield perceptual errors. These errors are pooled nonlinearly over the image to yield total perceptual error. With this model one may estimate the quantization matrix for a particular image that yields minimum bit rate for a given total perceptual error, or minimum perceptual error for a given bit rate. Custom matrices for a number of images show clear improvement over image-independent matrices. Custom matrices are compatible with the JPEG standard, which requires transmission of the quantization matrix.

Ahumada, Albert J., Jr.↗

A visual detection model for DCT coefficient quantization

The discrete cosine transform (DCT) is widely used in image compression, and is part of the JPEG and MPEG compression standards. The degree of compression, and the amount of distortion in the decompressed image are determined by the quantization of the transform coefficients. The standards do not specify how the DCT coefficients should be quantized. Our approach is to set the quantization level for each coefficient so that the quantization error is at the threshold of visibility. Here we combine results from our previous work to form our current best detection model for DCT coefficient quantization noise. This model predicts sensitivity as a function of display parameters, enabling quantization matrices to be designed for display situations varying in luminance, veiling light, and spatial frequency related conditions (pixel size, viewing distance, and aspect ratio). It also allows arbitrary color space directions for the representation of color.

Ahumada, Albert J., Jr.↗

NASA Tech Briefs, December 2008

Topics covered include: Crew Activity Analyzer; Distributing Data to Hand-Held Devices in a Wireless Network; Reducing Surface Clutter in Cloud Profiling Radar Data; MODIS Atmospheric Data Handler; Multibeam Altimeter Navigation Update Using Faceted Shape Model; Spaceborne Hybrid-FPGA System for Processing FTIR Data; FPGA Coprocessor for Accelerated Classification of Images; SiC JFET Transistor Circuit Model for Extreme Temperature Range; TDR Using Autocorrelation and Varying-Duration Pulses; Update on Development of SiC Multi-Chip Power Modules; Radio Ranging System for Guidance of Approaching Spacecraft; Electromagnetically Clean Solar Arrays; Improved Short-Circuit Protection for Power Cells in Series; Electromagnetically Clean Solar Arrays; Logic Gates Made of N-Channel JFETs and Epitaxial Resistors; Improved Short-Circuit Protection for Power Cells in Series; Communication Limits Due to Photon-Detector Jitter; System for Removing Pollutants from Incinerator Exhaust; Sealing and External Sterilization of a Sample Container; Converting EOS Data from HDF-EOS to netCDF; HDF-EOS 2 and HDF-EOS 5 Compatibility Library; HDF-EOS Web Server; HDF-EOS 5 Validator; XML DTD and Schemas for HDF-EOS; Converting from XML to HDF-EOS; Simulating Attitudes and Trajectories of Multiple Spacecraft; Specialized Color Function for Display of Signed Data; Delivering Alert Messages to Members of a Work Force; Delivering Images for Mars Rover Science Planning; Oxide Fiber Cathode Materials for Rechargeable Lithium Cells; Electrocatalytic Reduction of Carbon Dioxide to Methane; Heterogeneous Superconducting Low-Noise Sensing Coils; Progress toward Making Epoxy/Carbon-Nanotube Composites; Predicting Properties of Unidirectional-Nanofiber Composites; Deployable Crew Quarters; Nonventing, Regenerable, Lightweight Heat Absorber; Miniature High-Force, Long-Stroke SMA Linear Actuators; "Bootstrap" Configuration for Multistage Pulse-Tube Coolers; Reducing Liquid Loss during Ullage Venting in Microgravity; Ka-Band Transponder for Deep-Space Radio Science; Replication of Space-Shuttle Computers in FPGAs and ASICs; Demisable Reaction-Wheel Assembly; Spatial and Temporal Low-Dimensional Models for Fluid Flow; Advanced Land Imager Assessment System; Range Imaging without Moving Parts.

Source record↗

Toward Long-Term Aquatic Science Products from Heritage Landsat Missions

This paper aims at generating a long-term consistent record of Landsat-derived remote sensing reflectance (Rrs) products, which are central for producing downstream aquatic science products (e.g., concentrations of total suspended solids). The products are derived from Landsat-5 and Landsat-7 observations leading to Landsat-8 era to enable retrospective analyses of inland and nearshore coastal waters. In doing so, the data processing was built into the SeaWiFS Data Analysis System (SeaDAS) followed by vicariously calibrating Landsat-7 and -5 data using reference in situ measurements and near-concurrent ocean color products, respectively. The derived Rrs products are then validated using (a) matchups using the Aerosol Robotic Network (AERONET) data measured by in situ radiometers, i.e., AERONET-OC, and (b) ocean color products at select sites in North America. Following the vicarious calibration adjustments, it is found that the overall biases in Rrs products are significantly reduced. The root-mean-square errors (RMSE), however, indicate noticeable uncertainties due to random and systematic noise. Long-term (since 1984) seasonal Rrs composites over 12 coastal and inland systems are further evaluated to explore the utility of Landsat archive processed via SeaDAS. With all the qualitative and quantitative assessments, it is concluded that with careful algorithm developments, it is possible to discern natural variability in historic water quality conditions using heritage Landsat missions. This requires the changes in Rrs exceed maximum expected uncertainties, i.e., 0.0015 [1/sr], estimated from mean RMSEs associated with the matchups and intercomparison analyses. It is also anticipated that Landsat-5 products will be less susceptible to uncertainties in turbid waters with Rrs(660) > 0.004 [1/sr], which is equivalent of ~1.2% reflectance. Overall, end-users may utilize heritage Rrs products with "fitness-for-purpose" concept in mind, i.e., products could be valuable for one application but may not be viable for another. Further research should be dedicated to enhancing atmospheric correction to account for non-negligible near-infrared reflectance in CDOM-rich and extremely turbid waters.

Pahlevan, Nima↗

Quasi-Periodic Oscillations in Black Hole Candidates as an Indicator of Transition Between Low and High States

By comparing positions on a spectral color-color diagram from 10 black hole candidates (BHCS) observed with Ginga (1354-64, 1826-24, 1630-47, LMC X-1, LMC X-3, GS 2000+25, GS 2023+33, GS 1124-68, Cyg X-1, and GX 339-4) with the observed broadband noise (BBN) (0.001-64 Hz) and quasi-periodic oscillation (QPO) variability, we find that the "very high state" is spectrally intermediate to the soft/high state and hard/low state. We find a transition point in spectral hardness where the dependence of the BHC QPO centroid frequency (of GS 1124-68 and GX 339-4) on spectral hardness switches from a correlation to an anticorrelation; where the BBN variability switches from high state to low state; and where the spectral hardness of the QPO relative to that of the BBN variability is a maximum. This coincidence of changing behavior in both the QPO and the broadband variability leads us to hypothesize that the QPO is due to interaction between the physical components which dominate the behaviors of BHCs when they occupy the hard/low and soft/high states. We conclude that these QPOs should be observed from BHCs during transition between these two states. Comparison with QPO and BBN behavior observed during the 1996 transition of Cyg X-1 supports this hypothesis. We also report 1-3 Hz QPOs observed in GS 2000+25 and Cyg X-1 in the hard/low state, and we compare these to the QPOs observed in GS 1124-68 and GX 339-4.

Rutledge, Robert E.↗

Exploring Sentinel-1 and Sentinel-2 diversity for Flood inundation mapping using deep learning

Identification of flood water extent from satellite images has historically relied on either synthetic aperture radar (SAR) or multi-spectral (MS) imagery. MS sensors are limited to cloud free conditions, whereas SAR imagery is plagued by noise-like speckle. Prior studies that use combinations of MS and SAR data to overcome individual limitations of these sensors have not fully examined sensitivity of flood mapping performance to different combinations of SAR and MS derived spectral indices or band transformations in color space. This study explores the use of diverse bands of Sentinel 2 (S2) through well-established water indices and Sentinel 1 (S1) derived SAR imagery along with their combinations to assess their capability for generating accurate flood inundation maps. The robustness in performance of S-1 and S-2 band combinations was evaluated using 446 hand labeled flood inundation images spanning across 11 flood events from Sen1Floods11 dataset which are highly diverse in terms of land cover as well as location. A modified K-fold cross validation approach is used to evaluate the performance of 32 combinations of S1 and S2 bands using a fully connected deep convolutional neural network known as U-Net. Our results indicated that usage of elevation information has improved the capability of S1 imagery to produce more accurate flood inundation maps. Compared to a median F1 score of 0.62 when using only S1 bands, the combined use of S1 and elevation information led to an improved median F1 score of 0.73. Water extraction indices based on S2 bands have a statistically significant superior performance in comparison to S1. Among all the band combinations, HSV (Hue, Saturation, Value) transformation of S2 bands provides a median F1 score of 0.9, outperforming the commonly used water spectral indices owing to HSV’s transformation’s superior contrast distinguishing abilities. Additionally, U-Net algorithm was able to learn the relationship between raw S2 based water extraction indices and their corresponding raw S2 bands, but not of HSV owing to relatively complex computation involved in the latter. Results of the paper establishes important benchmarks for the extension of S1 and S2 data-based flood inundation mapping efforts over large spatial extents.

Goutam Konapala↗

Modeling and investigative studies of Jovian low frequency emissions

Jovian decametric (DAM) and hectometric (HOM) emissions were first observed over the entire spectrum by the Voyager 1 and 2 flybys of the planet. They display unusual arc-like structures on frequency-versus-time spectrograms. Software for the modeling of the Jovian plasma and magnetic field environment was performed. In addition, an extensive library of programs was developed for the retrieval of Voyager Planetary Radio Astronomy (PRA) data in both the high and low frequency bands from new noise-free, recalibrated data tapes. This software allows the option of retrieving data sorted with respect to particular sub-Io longitudes. This has proven to be invaluable in the analyses of the data. Graphics routines were also developed to display the data on color spectrograms.

Menietti, J. D.↗

Observation of Kilohertz Quasiperiodic Oscillations from the Atoll Source 4U 1702-429 by RXTE

We present results of Rossi X-Ray Timing Explorer (RXTE) observations of the atoll source 4U 1702-429 in the middle of its luminosity range. Kilohertz-range quasiperiodic oscillations (QPOS) were observed first as a narrow (FWHM approximately 7 Hz) peak near 900 Hz, and later as a pair consisting of a narrow peak in the range 625 825 Hz and a faint broad (FWHM 91 Hz) peak. When the two peaks appeared simultaneously the separation was 333 +/- 5 Hz. Six type I thermonuclear bursts were detected, of which five exhibited almost coherent oscillations near 330 Hz, which makes 4U 1702-429 only the second source to show burst oscillations very close to the kilohertz QPO separation frequency. The energy spectrum and color-color diagram indicate that the source executed variations in the range between the "island" and "lower banana" atoll states. In addition to the kilohertz variability, oscillations at approximately 10, approximately 35, and 80 Hz were also detected at various times, superimposed on a red noise continuum. The centroid of the approximately 35 Hz QPO tracks the frequency of the kilohertz oscillation when they were both present. A Lense-Thirring gravitomagnetic precession interpretation appears more plausible in this case, compared to other atoll sources with low frequency QPOs.

Markwardt, C. B.↗

A framework for quantitative analysis of spectral data in two channels

Simultaneous acquisition of emission intensity from two channels in dual-color fluorescence measurements can be used to determine the spectral properties of an emitter. We detail a method to extract quantitative information from dual-color measurements by considering two models: a single spectral component model for peak wavelength determination and a dual spectral component model for relative strength determination. The former model is useful for spectral characterization and establishing heterogeneity within an emitter species, while the latter model is useful for analyzing energy transfer efficiency. Both models are formalized to yield probability distributions that reflect uncertainties due to shot noise. We applied these analysis tools to single-particle measurements of CdSe/CdS quantum dots. Isolated emitters had narrow spectral-intensity distributions that reflected their static emission profiles and fluorescence stability. Small assemblies of mixed donor/acceptor particles exhibited dynamic behavior where emission configuration changes reveal different spectral characteristics due to energy transfer.

36 MATERIALS SCIENCE↗

A study of image quality for radar image processing

Methods developed for image quality metrics are reviewed with focus on basic interpretation or recognition elements including: tone or color; shape; pattern; size; shadow; texture; site; association or context; and resolution. Seven metrics are believed to show promise as a way of characterizing the quality of an image: (1) the dynamic range of intensities in the displayed image; (2) the system signal-to-noise ratio; (3) the system spatial bandwidth or bandpass; (4) the system resolution or acutance; (5) the normalized-mean-square-error as a measure of geometric fidelity; (6) the perceptual mean square error; and (7) the radar threshold quality factor. Selective levels of degradation are being applied to simulated synthetic radar images to test the validity of these metrics.

King, R. W.↗

Quasi-Periodic Oscillations in Black Hole Candidates as an Indicator of Transition Between Low and High States

By comparing positions on a spectral color-color diagram from 10 black hole candidates (BHCS) observed with Ginga (1354-64, 1826-24, 1630-47, LMC X-1, LMC X-3, GS 2000+25, GS 2023+33, GS 1124-68, Cyg X-1, and GX 339-4) with the observed broad-band noise (0.001- 64 Hz; BBN) and quasi-periodic oscillation (QPO) variability, we find that the so-called "Very High State" is spectrally intermediate to the Soft/High-State and Hard/Low-State. We find a transition point in spectral hardness where the dependence of the BHC QPO centroid frequency (of GS 1124-68 and GX 339-4) on spectral hardness switches from a correlation to an anti-correlation; where the BBN variability switches from High-State to Low-State; and where the spectral hardness of the QPO relative to that of the BBN variability is a maximum. This coincidence of changing behavior in both the QPO and the broad-band variability leads us to hypothesize that the QPO is due to interaction between the physical components which dominate the behaviors of BHCs when they occupy the Hard/Low and Soft/High States. We conclude that these QPO should be observed from BHCs during transition between these two states. Comparison with QPO and BBN behavior observed during the 1996 transition of Cyg X-1 supports this hypothesis. We also report 1-3 Hz QPO observed in GS 2000+25 and Cyg X-1 in the Hard/Low State, and we compare these to the QPO observed in GS 1124-68 and GX 339-4.

Rutledge, Robert E↗

On-Orbit OCI Characterization Measurements from the first 6 Months of the PACE Mission

The Ocean Color Instrument (OCI) on NASA’s Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission has been providing data to the science community since April 2024. OCI is a hyperspectral imager, providing almost daily global coverage, at a spatial resolution of 1.2km. Its design specifications were optimized for ocean color and atmospheric applications, but terrestrial studies could benefit from its hyperspectral coverage as well. The ocean color requirements called for very high radiometric accuracy, which could benefit a wide variety of applications. This paper presents results from the first 6 months of on-orbit calibration and characterization measurements, including absolute calibration, spectral registration, temporal trending of radiometric sensitivity, signal to noise ratio, and linearity, with a focus on the commissioning results obtained in the first 2 months after launch.

calibration↗

On-Orbit OCI Characterization Measurements from the first 6 Months of the PACE Mission

The Ocean Color Instrument (OCI) on NASA’s Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission has been providing data to the science community since April 2024. OCI is a hyperspectral imager, providing almost daily global coverage, at a spatial resolution of 1.2km. Its design specifications were optimized for ocean color and atmospheric applications, but terrestrial studies could benefit from its hyperspectral coverage as well. The ocean color requirements called for very high radiometric accuracy, which could benefit a wide variety of applications. This paper presents results from the first 6 months of on-orbit calibration and characterization measurements, including absolute calibration, spectral registration, temporal trending of radiometric sensitivity, signal to noise ratio, and linearity, with a focus on the commissioning results obtained in the first 2 months after launch.

calibration↗

Clustering of the Diffuse Infrared Light from the COBE DIRBE Maps: Power Spectrum Analysis and Excess Isotropic Component of Fluctuations - 3

The cosmic infrared background (CIB) radiation is the cosmic repository for energy release throughout the history of the universe. The spatial fluctuations of the CIB resulting from galaxy clustering are expected to be at least a few percent on scales of a degree, depending on the luminosity and clustering history of the early universe. Using the all-sky data from the COBE DIRBE instrument at wavelengths 1.25 - 100 microns we attempt to measure the CIB fluctuations. In the near-IR, foreground emission is dominated by small scale structure due to stars in the Galaxy. There we find a strong correlation between the amplitude of the fluctuations and Galactic latitude after removing bright foreground stars. Using data outside the Galactic plane (absolute value of b > 20 deg) and away from the center (90 deg < l < 270 deg) we extrapolate the amplitude of the fluctuations to cosec absolute value of b = 0. We find a positive intercept of delta.F(sub rms) = 15.5(sup +3.7, sub -7.0), 5.9(sup +1.6, sub -3.7), 2.4(sup +0.5, sub -0.9), 2.0(sup +0.25, sub -0.5) nW/sq m.sr at 1.25, 2.2, 3.5 and 4.9 microns respectively, where the errors are the range of 92% confidence limits. For color subtracted maps between band 1 and 2 we find the isotropic part of the fluctuations at 7.6(sup +1.2, sub -2.4) nW/sq m.sr. Based on detailed numerical and analytic models, this residual is not likely to originate from the Galaxy, our clipping algorithm, or instrumental noise. We demonstrate that the residuals from the fit used in the extrapolation are distributed isotropically and suggest that this extra variance may result from structure in the CIB. We also obtain a positive intercept from a linear combination of maps at 1.25 and 2.2 microns. For 2 deg < theta < 15 deg, a power-spectrum analysis yields limits of (theta/5 deg) x delta.F(sub rms)(theta) < 6, 2.5, 0.8, 0.5 nW/sq m.sr at 1.25, 2.2, 3.5 and 4.9 microns respectively. From 10 - 100 microns, the dominant foregrounds are emission by dust in the Solar system and the Galaxy. There the upper limits on the CIB fluctuations are below 1 nW/sq m.sr and are lowest (< equal 0.5 nW/sq m.sr) at 25 microns.

Kashlinsky, A.↗

Spectral Correlation in MODIS Water-Leaving Reflectance Retrieval Uncertainty

Spectral remote sensing reflectance, Rrs(λ) (sr−1), is the fundamental quantity used to derive a host of bio-optical and biogeochemical properties of the water column from satellite ocean color measurements. Estimation of uncertainty in those derived geophysical products is therefore dependent on knowledge of the uncertainty in satellite-retrieved R rs . Furthermore, since the associated algorithms require R rs at multiple spectral bands, the spectral (i.e., band-to-band)error covariance in R rs is needed to accurately estimate the uncertainty in those derived properties. This study establishes a derivative-based approach for propagating instrument random noise, instrument systematic uncertainty, and forward model uncertainty into R rs as retrieved using NASA’s multiple-scattering epsilon (MSEPS) atmospheric correction algorithm, to generate pixel-level error covariance in R rs . The approach is applied to measurements from Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite and verified using Monte Carlo (MC) analysis. We also make use of this full spectral error covariance in R rs to calculate uncertainty in phytoplankton pigment chlorophyll-a concentration (chl a , mg/m 3 ) and diffuse attenuation coefficient of downwelling irradiance at 490 nm (K d (490), m -1 ). Accounting for the error covariance in R rs generally reduces the estimated relative uncertainty in chl a by ∼1-2% (absolute value) in waters with chl a < 0.25 mg/m 3 where the color index (CI) algorithm is used. The reduction is ∼5-10% in waters with chl a > 0.35 mg/m 3 where the blue-green ratio (OCX) algorithm is used. Such reduction can be higher than 30% in some regions. For K d (490), the reduction by error covariance is generally ∼2%, but can be higher than 20% in some regions. The error covariance in R rs is further verified through forward-calculating chl a from MODIS-retrieved and in situ R rs and comparing estimated uncertainty with observed differences. An 8-day global composite of propagated uncertainty shows that the goal of 35% uncertainty in chl a can be achieved over deep ocean waters (chl a ≤ 0.1 mg/m3). While the derivative-based approach generates reasonable error covariance in R rs some assumptions should be updated as our knowledge improves. These include the inter-band error correlation in top-of-atmosphere reflectance, and uncertainties in the calibration of MODIS 869 nm band, in ancillary data, and in the in situ data used for system vicarious calibration.

Ocean color↗

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↗

X-Ray and Near-Infrared Observations of the Middle-aged Pulsar B1055-52, Its Multiwavelength Spectrum, and Proper Motion

Previous observations of the middle-aged γ-ray, X-ray, and radio pulsar B1055–52 indicated some peculiarities, such as a suspected changing of the X-ray flux and spectral parameters, a large excess of the alleged thermal component of the UV spectrum over the Rayleigh–Jeans extension of the X-ray thermal spectrum, and a possible double break in the nonthermal spectral component between the optical and X-ray bands. We observed PSR B1055–52 with the XMM-Newton observatory in X-rays and the Hubble Space Telescope in near-infrared (NIR). The analysis of the XMM-Newton observations does not support the notion of long-term changes in the X-ray flux and broadband X-ray spectrum of the pulsar. Using an observing mode less affected by background noise than the previous XMM-Newton observations, we constrain the power-law (PL) spectral index as X 0.57 0.25 0.26 a = - - + (Fν ∝ ν α ) in the energy band 3–10 keV. From the NIR–optical data we obtain a PL slope αO = −0.24 ± 0.10 for the color index E(B − V ) = 0.03 mag. The slopes and fluxes of the NIR–optical and X-ray nonthermal spectra suggest that the NIR through X-ray emission can be described by the same PL and is generated by the same mechanism, unlike the pulsar’s γ-ray emission. The excess of the UV thermal component over the extension of the X-ray thermal component became smaller but did not disappear, indicating a nonuniformity of the bulk surface temperature. The NIR data also enable us to measure the proper motion accurately, with values μα = 47.5 ± 0.7 mas yr−1 and μδ = −8.7 ± 0.7 mas yr−1 .

B Posselt↗

Analog FM/FM versus digital color TV transmission aboard space station

Langley Research Center is developing an integrated fault tolerant network to support data, voice, and video communications aboard Space Station. The question of transmitting the video data via dedicated analog channels or converting it to the digital domain for consistancy with the test of the data is addressed. The recommendations in this paper are based on a comparison in the signal-to-noise ratio (SNR), the type of video processing required aboard Space Station, the applicability to Space Station, and how they integrate into the network.

Hart, M. M.↗