Results for “pixel” — Page 45

NASA NTRS2021

Unsteady Pressure-Sensitive-Paint Shot Noise Reduction

In the study of unsteady Pressure-Sensitive Paint (uPSP) image data sets, pixel intensity values collected by Phantom cameras from multiple perspectives are used to calculate the surface pressure of an experimental model. This paper focuses on mitigation of shot noise which is introduced into the image data set by the cameras. Shot noise impacts the quality of data collected, increasing the system error in its pressure value calculations. This paper characterises statistical methods to reduce shot noise within experimental data by taking an average or weighted average across an area of pixels of their respective counts. Each combined-pixel has a higher total effective intensity value and therefore exhibits reduced noise throughout its time history. This is demonstrated by calculating the standard deviations of the combined pixel values through time, which decrease as the combined pixel area increases. Finally, these methods are compared across experimental wind tunnel conditions to examine their effectiveness at different Mach numbers. Ultimately, the results are used to recommend a blur filter type and size which will be applied to the raw image data prior to processing, as well as a minimum camera resolution for future experiments. Downstream of the filter application, the software to convert the 2D image data sets into surface pressure readings on a 3D grid use a ratio of decimation that assigns multiple pixels to each 3D grid node. This decimation ratio will also be aligned with the size of the blur filter, resulting in a more manageable data set size and compromised spatial resolution. Combined with the effect of the blur filter, the resulting pixel intensity readings will exhibit significantly reduced shot noise, reducing the magnitude of uncertainty and error in the final calculated pressure. For future tests, the camera spatial resolution must be sufficient to capture small flow and model features even after the recommended blur filter is applied. The image data set is taken from a uPSP experiment of the Space Launch System Block 1 cargo vehicle model in September 2019.

Lucy Tang↗

NASA NTRS2021

Unsteady Pressure-Sensitive Paint (UPSP) Shot Noise Reduction

In the study of unsteady Pressure-Sensitive Paint (uPSP) image data sets, pixel intensity values collected by Phantom cameras from multiple perspectives are used to calculate the surface pressure of an experimental model. This paper focuses on mitigation of shot noise which is introduced into the image data set by the cameras. Shot noise impacts the quality of data collected, increasing the system error in its pressure value calculations. This paper characterises statistical methods to reduce shot noise within experimental data by taking an average or weighted average across an area of pixels of their respective counts. Each combined-pixel has a higher total effective intensity value and therefore exhibits reduced noise throughout its time history. This is demonstrated by calculating the standard deviations of the combined pixel values through time, which decrease as the combined pixel area increases. Finally, these methods are compared across experimental wind tunnel conditions to examine their effectiveness at different Mach numbers. Ultimately, the results are used to recommend a blur filter type and size which will be applied to the raw image data prior to processing, as well as a minimum camera resolution for future experiments. Downstream of the filter application, the software to convert the 2D image data sets into surface pressure readings on a 3D grid use a ratio of decimation that assigns multiple pixels to each 3D grid node. This decimation ratio will also be aligned with the size of the blur filter, resulting in a more manageable data set size and compromised spatial resolution. Combined with the effect of the blur filter, the resulting pixel intensity readings will exhibit significantly reduced shot noise, reducing the magnitude of uncertainty and error in the final calculated pressure. For future tests, the camera spatial resolution must be sufficient to capture small flow and model features even after the recommended blur filter is applied. The image data set is taken from a uPSP experiment of the Space Launch System Block 1 cargo vehicle model in September 2019.

Lucy Tang↗

NASA NTRSDate not supplied

Assessment of Sensor Footprint Size and Comparison of Commercial Smallsat Images

Science users of commercial satellite data build their studies on the properties of the satellite data they work with, pixel size being one of the determining factors. However, pixel size and nominal image footprint size can be different, impacting the scale of features discernable in the satellite images. Here, we assess geometric properties such as nominal image footprint size for Planet Labs' SuperDove series, MAXAR's WorldView series, and potentially BlackSky. Additionally, we assess temporal change in nominal footprint size for the SuperDove series. Nominal Image footprint size is assessed over the CalVal sites in Baotou, China; Shadnagar, India; and Big Spring, TX. Edge spread functions are constructed along the black/white transitions, from which the line spread functions are constructed and modulation transfer functions of the scene are estimated. Scene full width half maximum (FWHM), which represents sensor footprint size, is estimated from the line spread function. The average nominal footprint size is 3.3 pixels for SuperDove series, 1.5 pixels for WorldView-2, and 1.3 pixels for WorldView-3. The SuperDove series nominal footprint size improves with time in orbit, from an average of 3.4 pixels soon after launch to an average of 3.2 pixels one or more years after launch.

PlanetScope↗

DOE OSTI2019

Vehicle track detection in synthetic aperture radar imagery

The various technologies presented herein relate to detecting one or more vehicle tracks in radar imagery. A CCD image can be generated from a first SAR image and a second SAR image captured for a common scene, wherein the second SAR image may include a vehicle track that is not present in the first SAR image. A Radon transform (RT) process can be applied to each pixel in the CCD image, and further, a radial derivative (RDRT) can be determined for each pixel from RT values derived for each pixel. Each pixel can be labelled as being related to a track, or not, based upon a unary cost obtained from the RDRT value of that pixel, combined with a probability of the pixel label based upon labels applied to neighboring pixels. A labelled representation of the CCD image can be generated based upon the determination of “track” or “not track”.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2021

Unmanned aircraft system (UAS) detection and assessment via temporal intensity aliasing

A method and system for temporal frequency analysis for identification of unmanned aircraft systems. The method includes obtaining a sequence of video image frames and providing a pixel from an output frame of the video; generating a fluctuating pixel value vector; examining the fluctuating pixel value vector over a period of time; obtaining the frequency information present in the pixel fluctuations; summing the frequency coefficients for the vectorized pixel values from the fluctuating pixel value vector; obtaining an image representing a two dimensional space based on the summed center frequency coefficients; generating a series of still frames equal to a summation of the center frequency coefficients for pixel variations; and combining the temporal information into spatial locations in a matrix to provide a single image containing the spatial and temporal information present in the sequence of video image frame.

Woo, Bryana Lynn↗

DOE OSTI2022

Electronic device and method for compressing video data

A computer-implemented method for compressing video data comprises receiving a sequence of video data values, each video data value being a digital value from a successive one of a plurality of pixels that form a video sensor, the sequence of video data values resulting from successive frames of video captured by the video sensor; extracting the video data values for each pixel in turn to create a plurality of pixel data streams, each pixel data stream including the video data value for each frame of captured video for the pixel; and applying data compression to each pixel data stream to create compressed data for each pixel data stream.

Tohlen, Michael Aaron↗

DOE OSTI2023

Unmanned aircraft system (UAS) detection and assessment via temporal intensity aliasing

A method and system for temporal frequency analysis for identification of unmanned aircraft systems. The method includes obtaining a sequence of video image frames and providing a pixel from an output frame of the video; generating a fluctuating pixel value vector; examining the fluctuating pixel value vector over a period of time; obtaining the frequency information present in the pixel fluctuations; summing the frequency coefficients for the vectorized pixel values from the fluctuating pixel value vector; obtaining an image representing a two dimensional space based on the summed center frequency coefficients; generating a series of still frames equal to a summation of the center frequency coefficients for pixel variations; and combining the temporal information into spatial locations in a matrix to provide a single image containing the spatial and temporal information present in the sequence of video image frame.

Woo, Bryana Lynn↗

DOE OSTI2023

Electronic device and method for compressing video data

A computer-implemented method for compressing video data comprises receiving a sequence of video data values, each video data value being a digital value from a successive one of a plurality of pixels that form a video sensor, the sequence of video data values resulting from successive frames of video captured by the video sensor; extracting the video data values for each pixel in turn to create a plurality of pixel data streams, each pixel data stream including the video data value for each frame of captured video for the pixel; and applying data compression to each pixel data stream to create compressed data for each pixel data stream.

Tohlen, Michael Aaron↗

DOE OSTI2026

Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique

Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.

42 ENGINEERING↗

DOE OSTI2023

The brighter-fatter effect in the JWST MIRI Si:As IBC detectors: I. Observations, impact on science, and modeling

Context.The Mid-Infrared Instrument (MIRI) on board theJames WebbSpace Telescope (JWST) uses three Si:As impurity band conduction (IBC) detector arrays. The output voltage level of each MIRI detector pixel is digitally recorded by sampling up the ramp. For uniform or low-contrast illumination, the pixel ramps become nonlinear in a predictable way, but in areas of high contrast, the nonlinearity curve becomes much more complex. The origin of the effect is poorly understood and currently not calibrated out of the data. Aims.We provide observational evidence of the brighter-fatter effect (BFE) in MIRI conventional and high-contrast coronagraphic imaging, low-resolution spectroscopy, and medium-resolution spectroscopy data, and we investigate the physical mechanism that gives rise to the effect on the MIRI detector pixel raw voltage integration ramps. Methods.We used public data from the JWST/MIRI commissioning and Cycle 1 phase. We also developed a numerical electrostatic model of the MIRI detectors using a modified version of the publicPoisson_CCDcode. Results.We find that the physical mechanism behind the BFE manifesting in MIRI data is fundamentally different to that of charge-coupled devices and photodiode arrays such as the Hawaii-XRG near-infrared detectors used by the NIRISS, NIRCam, and NIRSpec instruments on board JWST. Observationally, the BFE makes the JWST MIRI data yield 10–25% larger point sources and spectral line profiles as a function of the relative level of de-biasing of neighboring detector pixels. This broadening impacts the MIRI absolute flux calibration, time-series observations of faint companions, and point spread function modeling and subtraction. We also find that the intra-pixel 2D profile of the shrinking Si:As IBC detector depletion region directly impacts the accuracy of the pixel ramp nonlinearity calibration model.

Astronomy & Astrophysics↗

DOE OSTI2015

Modeling the dark current histogram induced by gold contamination in complementary-metal-oxide-semiconductor image sensors

We propose a model for dark current induced by metallic contamination in a CMOS image sensor. Based on Shockley-Read-Hall kinetics, the expression of dark current proposed accounts for the electric field enhanced emission factor due to the Poole-Frenkel barrier lowering and phonon-assisted tunneling mechanisms. To that aim, we considered the distribution of the electric field magnitude and metal atoms in the depth of the pixel. Poisson statistics were used to estimate the random distribution of metal atoms in each pixel for a given contamination dose. Then, we performed a Monte-Carlo-based simulation for each pixel to set the number of metal atoms the pixel contained and the enhancement factor each atom underwent, and obtained a histogram of the number of pixels versus dark current for the full sensor. Excellent agreement with the dark current histogram measured on an ion-implanted gold-contaminated imager has been achieved, in particular, for the description of the distribution tails due to the pixel regions in which the contaminant atoms undergo a large electric field. The agreement remains very good when increasing the temperature by 15 °C. We demonstrated that the amplification of the dark current generated for the typical electric fields encountered in the CMOS image sensors, which depends on the nature of the metal contaminant, may become very large at high electric field. The electron and hole emissions and the resulting enhancement factor are described as a function of the trap characteristics, electric field, and temperature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Performance improvements of wavelength-shifting-fiber neutron detectors using high-resolution positioning algorithms

On the basis of FluoroBancroft linear-algebraic method [S.B. Andersson, Opt. Exp. 16, 18714 (2008)] three highly-resolved positioning methods were proposed for wavelength-shifting fiber (WLSF) neutron detectors. Using a Gaussian or exponential-decay light-response function (LRF), the non-linear relation of photon-number profiles vs. x-pixels was linearized and neutron positions were determined. The proposed algorithms give an average 0.03-0.08 pixel position error, much smaller than that (0.29 pixel) from a traditional maximum photon algorithm (MPA). The new algorithms result in better detector uniformity, less position misassignment (ghosting), better spatial resolution, and an equivalent or better instrument resolution in powder diffraction than the MPA. Moreover, these characters will facilitate broader applications of WLSF detectors at time-of-flight neutron powder diffraction beamlines, including single-crystal diffraction and texture analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Spatial resolution of a spherical x-ray crystal spectrometer at various magnifications

A high spatial resolution of a few μm is often required for probing small-scale high-energy-density plasmas using high resolution x-ray imaging spectroscopy. This resolution can be achieved by adjusting system magnification to overcome the inherent limitation of the detector pixel size. Laboratory experiments on investigating the relation between spatial resolution and system magnification for a spherical crystal spectrometer are presented. Tungsten Lβ{sub 2} rays from a tungsten-target micro-focus x-ray tube were diffracted by a Ge 440 crystal, which was spherically bent to a radius of 223 mm, and imaged onto an x-ray CCD with 13-μm pixel size. The source-to-crystal (p) and crystal-to-detector (q) distances were varied to produce spatial magnifications (M = q/p) ranging from 2 to 10. The inferred instrumental spatial width reduces with increasing system magnification M. However, the experimental measurement at each M is larger than the theoretical value of pixel size divided by M. Future work will focus on investigating possible broadening mechanisms that limit the spatial resolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Hammerhead, an ultrahigh resolution ePix camera for wavelength-dispersive spectrometers

Wavelength-dispersive spectrometers (WDS) are often used in synchrotron and FEL applications where high energy resolution (in the order of eV) is important. Increasing WDS energy resolution requires increasing spatial resolution of the detectors in the dispersion direction. The common approaches are not ideal: using strip detectors loses the 2D position sensitivity (important for, e.g., background estimation) and the high counting rate; using pixel detectors with a small pitch results in complex charge sharing behaviour and typically have a small size. Developing pixel detectors with high aspect ratio and a small pitch in the wavelength dispersive direction would be ideal, however, it would require a substantial ASIC development. We present a new approach, with a novel sensor design using rectangular pixels with a high aspect ratio (between strips and pixels, further called “strixels”), and strixel redistribution to match the square pixel arrays of typical ASICs. This results in a sensor area of 17.4 mm × 77 mm, with a fine pitch of 25 µm in the horizontal direction resulting in 3072 columns and 176 rows. The sensors use ePix100 readout ASICs, leveraging their low noise (43 e - , or 180 eV rms). We present results obtained with a Hammerhead ePix100 camera, showing that the small pitch (25 µm) in the dispersion direction maximizes performance for both high and low photon occupancies, resulting in optimal WDS energy resolution. The low noise level at high photon occupancy allows precise photon counting, while at low occupancy, both the energy and the subpixel position can be reconstructed for every photon, allowing an ultrahigh resolution (in the order of 1 µm) in the dispersion direction and rejection of scattered beam and harmonics. Using strixel sensors with redistribution and flip-chip bonding to standard ePix readout ASICs results in ultrahigh position resolution (~1 µm) and low noise in WDS applications, leveraging the advantages of hybrid pixel detectors (high production yield, good availability, relatively inexpensive) while minimizing development complexity through sharing the ASIC, hardware, software and DAQ development with other versions of ePix cameras.

47 OTHER INSTRUMENTATION↗

DOE OSTI2015

THE DIFFERENCE IMAGING PIPELINE FOR THE TRANSIENT SEARCH IN THE DARK ENERGY SURVEY

We describe the operation and performance of the difference imaging pipeline (DiffImg) used to detect transients in deep images from the Dark Energy Survey Supernova program (DES-SN) in its first observing season from 2013 August through 2014 February. DES-SN is a search for transients in which ten 3 deg{sup 2} fields are repeatedly observed in the g, r, i, z passbands with a cadence of about 1 week. The observing strategy has been optimized to measure high-quality light curves and redshifts for thousands of Type Ia supernovae (SNe Ia) with the goal of measuring dark energy parameters. The essential DiffImg functions are to align each search image to a deep reference image, do a pixel-by-pixel subtraction, and then examine the subtracted image for significant positive detections of point-source objects. The vast majority of detections are subtraction artifacts, but after selection requirements and image filtering with an automated scanning program, there are ∼130 detections per deg{sup 2} per observation in each band, of which only ∼25% are artifacts. Of the ∼7500 transients discovered by DES-SN in its first observing season, each requiring a detection on at least two separate nights, Monte Carlo (MC) simulations predict that 27% are expected to be SNe Ia or core-collapse SNe. Another ∼30% of the transients are artifacts in which a small number of observations satisfy the selection criteria for a single-epoch detection. Spectroscopic analysis shows that most of the remaining transients are AGNs and variable stars. Fake SNe Ia are overlaid onto the images to rigorously evaluate detection efficiencies and to understand the DiffImg performance. The DiffImg efficiency measured with fake SNe agrees well with expectations from a MC simulation that uses analytical calculations of the fluxes and their uncertainties. In our 8 “shallow” fields with single-epoch 50% completeness depth ∼23.5, the SN Ia efficiency falls to 1/2 at redshift z ≈ 0.7; in our 2 “deep” fields with mag-depth ∼24.5, the efficiency falls to 1/2 at z ≈ 1.1. A remaining performance issue is that the measured fluxes have additional scatter (beyond Poisson fluctuations) that increases with the host galaxy surface brightness at the transient location. This bright-galaxy issue has minimal impact on the SNe Ia program, but it may lower the efficiency for finding fainter transients on bright galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

A BLIND METHOD TO DETREND INSTRUMENTAL SYSTEMATICS IN EXOPLANETARY LIGHT CURVES

The study of the atmospheres of transiting exoplanets requires a photometric precision, and repeatability, of one part in ∼10{sup 4}. This is beyond the original calibration plans of current observatories, hence the necessity to disentangle the instrumental systematics from the astrophysical signals in raw data sets. Most methods used in the literature are based on an approximate instrument model. The choice of parameters of the model and their functional forms can sometimes be subjective, causing controversies in the literature. Recently, Morello et al. (2014, 2015) have developed a non-parametric detrending method that gave coherent and repeatable results when applied to Spitzer/IRAC data sets that were debated in the literature. Said method is based on independent component analysis (ICA) of individual pixel time-series, hereafter “pixel-ICA”. The main purpose of this paper is to investigate the limits and advantages of pixel-ICA on a series of simulated data sets with different instrument properties, and a range of jitter timescales and shapes, non-stationarity, sudden change points, etc. The performances of pixel-ICA are compared against the ones of other methods, in particular polynomial centroid division, and pixel-level decorrelation method. We find that in simulated cases pixel-ICA performs as well or better than other methods, and it also guarantees a higher degree of objectivity, because of its purely statistical foundation with no prior information on the instrument systematics. The results of this paper, together with previous analyses of Spitzer/IRAC data sets, suggest that photometric precision and repeatability of one part in 10{sup 4} can be achieved with current infrared space instruments.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Is flat fielding safe for precision CCD astronomy?

The ambitious goals of precision cosmology with wide-field optical surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST) demand precision CCD astronomy as their foundation. This in turn requires an understanding of previously uncharacterized sources of systematic error in CCD sensors, many of which manifest themselves as static effective variations in pixel area. Such variation renders a critical assumption behind the traditional procedure of flat fielding—that a sensor's pixels comprise a uniform grid—invalid. In this work, we present a method to infer a curl-free model of a sensor's underlying pixel grid from flat-field images, incorporating the superposition of all electrostatic sensor effects—both known and unknown—present in flat-field data. We use these pixel grid models to estimate the overall impact of sensor systematics on photometry, astrometry, and PSF shape measurements in a representative sensor from the Dark Energy Camera (DECam) and a prototype LSST sensor. Applying the method to DECam data recovers known significant sensor effects for which corrections are currently being developed within DES. For an LSST prototype CCD with pixel-response non-uniformity (PRNU) of 0.4%, we find the impact of "improper" flat fielding on these observables is negligible in nominal .7'' seeing conditions. Furthermore, these errors scale linearly with the PRNU, so for future LSST production sensors, which may have larger PRNU, our method provides a way to assess whether pixel-level calibration beyond flat fielding will be required.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Instrumental Response Model and Detrending for the Dark Energy Camera

We describe the model for mapping from sky brightness to the digital output of the Dark Energy Camera (DECam) and the algorithms adopted by the Dark Energy Survey (DES) for inverting this model to obtain photometric measures of celestial objects from the raw camera output. This calibration aims for fluxes that are uniform across the camera field of view and across the full angular and temporal span of the DES observations, approaching the accuracy limits set by shot noise for the full dynamic range of DES observations. The DES pipeline incorporates several substantive advances over standard detrending techniques, including principal-components-based sky and fringe subtraction; correction of the "brighter-fatter" nonlinearity; use of internal consistency in on-sky observations to disentangle the influences of quantum efficiency, pixel-size variations, and scattered light in the dome flats; and pixel-by-pixel characterization of instrument spectral response, through combination of internal-consistency constraints with auxiliary calibration data. This article provides conceptual derivations of the detrending/calibration steps, and the procedures for obtaining the necessary calibration data. Other publications will describe the implementation of these concepts for the DES operational pipeline, the detailed methods, and the validation that the techniques can bring DECam photometry and astrometry within $\approx 2$ mmag and $\approx 3$ mas, respectively, of fundamental atmospheric and statistical limits. In conclusion, the DES techniques should be broadly applicable to wide-field imagers.

79 ASTRONOMY AND ASTROPHYSICS↗