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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Programmable remapper with single flow architecture

The invention relates to image processing systems and methods and in particular to a machine which accepts a real time video image in the form of a matrix of picture elements (pixels) and remaps such image according to a selectable one of a plurality of mapping functions to create an output matrix of pixels. Such mapping functions, or transformations, may be any one of a number of different transformations depending on the objective of the user of the system. The system remaps input images from one coordinate system to another using a set of look-up tables for the data necessary for the transform. The transforms, which are operator selectable, are precomputed and loaded into massive look-up tables. Input pixels, via the look-up tables of any particular transform selected, are mapped into output pixels with the radiance information of the input pixels being appropriately weighted. An earlier embodiment of the system included two parallel processors: a collective processor which mapped multiple input pixels into a single output pixel and an interpolative processor. The interpolative processor performed an interpolation among pixels in the input image where a given input pixel may affect the value of many output pixels. Several advantages are provided over previous embodiments in that the two distinct processors are replaced by a single processor capable of performing both types of operations (collective and interpolative) with no more complexity. Previously, there has existed no image processor or 'remapper' that can operate with sufficient speed and flexibility to permit investigating different transformation patterns in real time.

Fisher, Timothy E.↗
NASA NTRS2008

On Certain New Methodology for Reducing Sensor and Readout Electronics Circuitry Noise in Digital Domain

NASA Hubble Space Telescope (HST) and upcoming cosmology science missions carry instruments with multiple focal planes populated with many large sensor detector arrays. These sensors are passively cooled to low temperatures for low-level light (L3) and near-infrared (NIR) signal detection, and the sensor readout electronics circuitry must perform at extremely low noise levels to enable new required science measurements. Because we are at the technological edge of enhanced performance for sensors and readout electronics circuitry, as determined by thermal noise level at given temperature in analog domain, we must find new ways of further compensating for the noise in the signal digital domain. To facilitate this new approach, state-of-the-art sensors are augmented at their array hardware boundaries by non-illuminated reference pixels, which can be used to reduce noise attributed to sensors. There are a few proposed methodologies of processing in the digital domain the information carried by reference pixels, as employed by the Hubble Space Telescope and the James Webb Space Telescope Projects. These methods involve using spatial and temporal statistical parameters derived from boundary reference pixel information to enhance the active (non-reference) pixel signals. To make a step beyond this heritage methodology, we apply the NASA-developed technology known as the Hilbert- Huang Transform Data Processing System (HHT-DPS) for reference pixel information processing and its utilization in reconfigurable hardware on-board a spaceflight instrument or post-processing on the ground. The methodology examines signal processing for a 2-D domain, in which high-variance components of the thermal noise are carried by both active and reference pixels, similar to that in processing of low-voltage differential signals and subtraction of a single analog reference pixel from all active pixels on the sensor. Heritage methods using the aforementioned statistical parameters in the digital domain (such as statistical averaging of the reference pixels themselves) zeroes out the high-variance components, and the counterpart components in the active pixels remain uncorrected. This paper describes how the new methodology was demonstrated through analysis of fast-varying noise components using the Hilbert-Huang Transform Data Processing System tool (HHT-DPS) developed at NASA and the high-level programming language MATLAB (Trademark of MathWorks Inc.), as well as alternative methods for correcting for the high-variance noise component, using an HgCdTe sensor data. The NASA Hubble Space Telescope data post-processing, as well as future deep-space cosmology projects on-board instrument data processing from all the sensor channels, would benefit from this effort.

Kizhner, Semion↗
NASA NTRS2008

Chromatic Modulator for a High-Resolution CCD or APS

A chromatic modulator has been proposed to enable the separate detection of the red, green, and blue (RGB) color components of the same scene by a single charge-coupled device (CCD), active-pixel sensor (APS), or similar electronic image detector. Traditionally, the RGB color-separation problem in an electronic camera has been solved by use of either (1) fixed color filters over three separate image detectors; (2) a filter wheel that repeatedly imposes a red, then a green, then a blue filter over a single image detector; or (3) different fixed color filters over adjacent pixels. The use of separate image detectors necessitates precise registration of the detectors and the use of complicated optics; filter wheels are expensive and add considerably to the bulk of the camera; and fixed pixelated color filters reduce spatial resolution and introduce color-aliasing effects. The proposed chromatic modulator would not exhibit any of these shortcomings. The proposed chromatic modulator would be an electromechanical device fabricated by micromachining. It would include a filter having a spatially periodic pattern of RGB strips at a pitch equal to that of the pixels of the image detector. The filter would be placed in front of the image detector, supported at its periphery by a spring suspension and electrostatic comb drive. The spring suspension would bias the filter toward a middle position in which each filter strip would be registered with a row of pixels of the image detector. Hard stops would limit the excursion of the spring suspension to precisely one pixel row above and one pixel row below the middle position. In operation, the electrostatic comb drive would be actuated to repeatedly snap the filter to the upper extreme, middle, and lower extreme positions. This action would repeatedly place a succession of the differently colored filter strips in front of each pixel of the image detector. To simplify the processing, it would be desirable to encode information on the color of the filter strip over each row (or at least over some representative rows) of pixels at a given instant of time in synchronism with the pixel output at that instant.

Hartley, Frank↗
NASA NTRS2008

Model of Image Artifacts from Dust Particles

A mathematical model of image artifacts produced by dust particles on lenses has been derived. Machine-vision systems often have to work with camera lenses that become dusty during use. Dust particles on the front surface of a lens produce image artifacts that can potentially affect the performance of a machine-vision algorithm. The present model satisfies a need for a means of synthesizing dust image artifacts for testing machine-vision algorithms for robustness (or the lack thereof) in the presence of dust on lenses. A dust particle can absorb light or scatter light out of some pixels, thereby giving rise to a dark dust artifact. It can also scatter light into other pixels, thereby giving rise to a bright dust artifact. For the sake of simplicity, this model deals only with dark dust artifacts. The model effectively represents dark dust artifacts as an attenuation image consisting of an array of diffuse darkened spots centered at image locations corresponding to the locations of dust particles. The dust artifacts are computationally incorporated into a given test image by simply multiplying the brightness value of each pixel by a transmission factor that incorporates the factor of attenuation, by dust particles, of the light incident on that pixel. With respect to computation of the attenuation and transmission factors, the model is based on a first-order geometric (ray)-optics treatment of the shadows cast by dust particles on the image detector. In this model, the light collected by a pixel is deemed to be confined to a pair of cones defined by the location of the pixel s image in object space, the entrance pupil of the lens, and the location of the pixel in the image plane (see Figure 1). For simplicity, it is assumed that the size of a dust particle is somewhat less than the diameter, at the front surface of the lens, of any collection cone containing all or part of that dust particle. Under this assumption, the shape of any individual dust particle artifact is the shape (typically, circular) of the aperture, and the contribution of the particle to the attenuation factor for a given pixel is the fraction of the cross-sectional area of the collection cone occupied by the particle. Assuming that dust particles do not overlap, the net transmission factor for a given pixel is calculated as one minus the sum of attenuation factors contributed by all dust particles affecting that pixel. In a test, the model was used to synthesize attenuation images for random distributions of dust particles on the front surface of a lens at various relative aperture (F-number) settings. As shown in Figure 2, the attenuation images resembled dust artifacts in real test images recorded while the lens was aimed at a white target.

Willson, Reg↗
DOE OSTI2018

Reflective photovoltaics

A photovoltaic module includes colorized reflective photovoltaic cells that act as pixels. The colorized reflective photovoltaic cells are arranged so that reflections from the photovoltaic cells or pixels visually combine into an image on the photovoltaic module. The colorized photovoltaic cell or pixel is composed of a set of 100 to 256 base color sub-pixel reflective segments or sub-pixels. The color of each pixel is determined by the combination of base color sub-pixels forming the pixel. As a result, each pixel can have a wide variety of colors using a set of base colors, which are created, from sub-pixel reflective segments having standard film thicknesses.

14 SOLAR ENERGY↗
DOE OSTI2015

Fabrication of large dual-polarized multichroic TES bolometer arrays for CMB measurements with the SPT-3G camera

This paper presents the procedures used by Argonne National Laboratory to fabricate large arrays of multichroic transition-edge sensor (TES) bolometers for cosmic microwave background (CMB) measurements. These detectors will be assembled into the focal plane for the SPT-3G camera, the third generation CMB camera to be installed in the South Pole Telescope. The complete SPT-3G camera will have approximately 2690 pixels, for a total of 16,140 TES bolometric detectors. Each pixel is comprised of a broad-band sinuous antenna coupled to a Nb microstrip line. In-line filters are used to define the different band-passes before the millimeter-wavelength signal is fed to the respective Ti/Au TES bolometers. There are six TES bolometer detectors per pixel, which allow for measurements of three band-passes (95 GHz, 150 GHz and 220 GHz) and two polarizations. The steps involved in the monolithic fabrication of these detector arrays are presented here in detail. Patterns are defined using a combination of stepper and contact lithography. The misalignment between layers is kept below 200 nm. The overall fabrication involves a total of 16 processes, including reactive and magnetron sputtering, reactive ion etching, inductively coupled plasma etching and chemical etching.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

SU-C-206-03: Metal Artifact Reduction in X-Ray Computed Tomography Based On Local Anatomical Similarity

Purpose: Metal implants such as orthopedic hardware and dental fillings cause severe bright and dark streaking in reconstructed CT images. These artifacts decrease image contrast and degrade HU accuracy, leading to inaccuracies in target delineation and dose calculation. Additionally, such artifacts negatively impact patient set-up in image guided radiation therapy (IGRT). In this work, we propose a novel method for metal artifact reduction which utilizes the anatomical similarity between neighboring CT slices. Methods: Neighboring CT slices show similar anatomy. Based on this anatomical similarity, the proposed method replaces corrupted CT pixels with pixels from adjacent, artifact-free slices. A gamma map, which is the weighted summation of relative HU error and distance error, is calculated for each pixel in the artifact-corrupted CT image. The minimum value in each pixel’s gamma map is used to identify a pixel from the adjacent CT slice to replace the corresponding artifact-corrupted pixel. This replacement only occurs if the minimum value in a particular pixel’s gamma map is larger than a threshold. The proposed method was evaluated with clinical images. Results: Highly attenuating dental fillings and hip implants cause severe streaking artifacts on CT images. The proposed method eliminates the dark and bright streaking and improves the implant delineation and visibility. In particular, the image non-uniformity in the central region of interest was reduced from 1.88 and 1.01 to 0.28 and 0.35, respectively. Further, the mean CT HU error was reduced from 328 HU and 460 HU to 60 HU and 36 HU, respectively. Conclusions: The proposed metal artifact reduction method replaces corrupted image pixels with pixels from neighboring slices that are free of metal artifacts. This method proved capable of suppressing streaking artifacts, improving HU accuracy and image detectability.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1995

Circuit for high resolution decoding of multi-anode microchannel array detectors

A circuit for high resolution decoding of multi-anode microchannel array detectors consisting of input registers accepting transient inputs from the anode array; anode encoding logic circuits connected to the input registers; midpoint pipeline registers connected to the anode encoding logic circuits; and pixel decoding logic circuits connected to the midpoint pipeline registers is described. A high resolution algorithm circuit operates in parallel with the pixel decoding logic circuit and computes a high resolution least significant bit to enhance the multianode microchannel array detector's spatial resolution by halving the pixel size and doubling the number of pixels in each axis of the anode array. A multiplexer is connected to the pixel decoding logic circuit and allows a user selectable pixel address output according to the actual multi-anode microchannel array detector anode array size. An output register concatenates the high resolution least significant bit onto the standard ten bit pixel address location to provide an eleven bit pixel address, and also stores the full eleven bit pixel address. A timing and control state machine is connected to the input registers, the anode encoding logic circuits, and the output register for managing the overall operation of the circuit.

Kasle, David B.↗
NASA NTRS1998

Does the UVI on Polar Detect Cosmic Snowballs?

Frank and Sigwarth [1997a] claim that the dark pixels observed in dayglow images obtained by the Earth sensor of the Visible Imaging System (VIS) are due to bombardment of Earth by 20 to 40 ton cosmic snowballs. We have independently studied the same one hour of VIS data Frank and Sigwarth used and have performed detailed statistical analysis of the dark pixels. The characteristics of the dark pixels from the VIS images have been compared to those obtained from the overlapping images from the Ultraviolet Imager (UVI). We find the occurrence distributions of the dark pixels, single and multiple, from VIS and UVI are nearly identical. This result cannot be explained by a -eophysical source since the two cameras have different pixel resolutions: A search for evidence of of spacecraft "wobble" motion, whose presence would indicate that the source is external to the camera, has found that pairs of dark pixel clusters are uniformly distributed in an-le and no preference is observed in the wobble direction. Instrument artifacts as the source of the dark pixels is the most likely explanation for these results. Probability estimates for the occurrence of dark pixel clusters lead us to expect coincident events of instrumental origin to occur frequently in the two cameras. The conclusion of this study is that neither VIS nor UVI provide any scientific evidence that the origin of dark pixels is geophysical.

Parks, G. K.↗
NASA NTRS2007

[Overview of the GSFC Effort to Build Microwave Detectors for CMB Polarization]

Filled arrays of bolometers are currently being employed for use in astronomy from the far-infrared through millimeter portion of the electromagnetic spectrum. Because of the large range of wavelengths for which such detectors are applicable, the size of a pixel (p) relative to the wavelength (lambda) will vary according to the specific application of a given available technology. As the pixel size becomes comparable to a wavelength of the absorbed radiation, correlations in the radiation field at the pixel can affect the imaging properties of the system independent of the correlations introduced by the front-end optics. We study the dependence of image fidelity and induced polarization on the size of the pixel by employing a formalism in which diffraction due to the pixel boundary is treated by propagating the second-order statistical correlations of the radiation field through a model optical system. We construct simulated polarized images of square pixels for various ratios of p lambda. For the limit in which few modes are supported by the pixel (p lambda lesssiml), we find that the diffraction due to the pixel edges is non-negligible and hence must be considered along with the telescope diffraction pattern in modeling the ultimate spatial resolution of an imaging system. For the case in which the pixel is over-moded (p lambda ggl), the geometric limit is approached as expected. This technique provides a quantitative approach to understand and optimize the imaging properties of planar detectors in the few-mode limit.

Chuss, David↗
NASA NTRS2010

A Framework for Propagation of Uncertainties in the Kepler Data Analysis Pipeline

The Kepler space telescope is designed to detect Earth-like planets around Sun-like stars using transit photometry by simultaneously observing 100,000 stellar targets nearly continuously over a three and a half year period. The 96-megapixel focal plane consists of 42 charge-coupled devices (CCD) each containing two 1024 x 1100 pixel arrays. Cross-correlations between calibrated pixels are introduced by common calibrations performed on each CCD requiring downstream data products access to the calibrated pixel covariance matrix in order to properly estimate uncertainties. The prohibitively large covariance matrices corresponding to the ~75,000 calibrated pixels per CCD preclude calculating and storing the covariance in standard lock-step fashion. We present a novel framework used to implement standard propagation of uncertainties (POU) in the Kepler Science Operations Center (SOC) data processing pipeline. The POU framework captures the variance of the raw pixel data and the kernel of each subsequent calibration transformation allowing the full covariance matrix of any subset of calibrated pixels to be recalled on-the-fly at any step in the calibration process. Singular value decomposition (SVD) is used to compress and low-pass filter the raw uncertainty data as well as any data dependent kernels. The combination of POU framework and SVD compression provide downstream consumers of the calibrated pixel data access to the full covariance matrix of any subset of the calibrated pixels traceable to pixel level measurement uncertainties without having to store, retrieve and operate on prohibitively large covariance matrices. We describe the POU Framework and SVD compression scheme and its implementation in the Kepler SOC pipeline.

Clarke, Bruce D.↗
NASA NTRS2011

Method and system for non-linear motion estimation

A method and system for extrapolating and interpolating a visual signal including determining a first motion vector between a first pixel position in a first image to a second pixel position in a second image, determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image, determining a third motion vector between one of the first pixel position in the first image and the second pixel position in the second image, and the second pixel position in the second image and the third pixel position in the third image using a non-linear model, determining a position of the fourth pixel in a fourth image based upon the third motion vector.

Lu, Ligang↗
NASA NTRS2011

Superpixel-Augmented Endmember Detection for Hyperspectral Images

Superpixels are homogeneous image regions comprised of several contiguous pixels. They are produced by shattering the image into contiguous, homogeneous regions that each cover between 20 and 100 image pixels. The segmentation aims for a many-to-one mapping from superpixels to image features; each image feature could contain several superpixels, but each superpixel occupies no more than one image feature. This conservative segmentation is relatively easy to automate in a robust fashion. Superpixel processing is related to the more general idea of improving hyperspectral analysis through spatial constraints, which can recognize subtle features at or below the level of noise by exploiting the fact that their spectral signatures are found in neighboring pixels. Recent work has explored spatial constraints for endmember extraction, showing significant advantages over techniques that ignore pixels relative positions. Methods such as AMEE (automated morphological endmember extraction) express spatial influence using fixed isometric relationships a local square window or Euclidean distance in pixel coordinates. In other words, two pixels covariances are based on their spatial proximity, but are independent of their absolute location in the scene. These isometric spatial constraints are most appropriate when spectral variation is smooth and constant over the image. Superpixels are simple to implement, efficient to compute, and are empirically effective. They can be used as a preprocessing step with any desired endmember extraction technique. Superpixels also have a solid theoretical basis in the hyperspectral linear mixing model, making them a principled approach for improving endmember extraction. Unlike existing approaches, superpixels can accommodate non-isometric covariance between image pixels (characteristic of discrete image features separated by step discontinuities). These kinds of image features are common in natural scenes. Analysts can substitute superpixels for image pixels during endmember analysis that leverages the spatial contiguity of scene features to enhance subtle spectral features. Superpixels define populations of image pixels that are independent samples from each image feature, permitting robust estimation of spectral properties, and reducing measurement noise in proportion to the area of the superpixel. This permits improved endmember extraction, and enables automated search for novel and constituent minerals in very noisy, hyperspatial images. This innovation begins with a graph-based segmentation based on the work of Felzenszwalb et al., but then expands their approach to the hyperspectral image domain with a Euclidean distance metric. Then, the mean spectrum of each segment is computed, and the resulting data cloud is used as input into sequential maximum angle convex cone (SMACC) endmember extraction.

Thompson, David R.↗
NASA NTRS2011

Development of Position-Sensitive Magnetic Calorimeters for X-Ray Astronomy

Metallic magnetic calorimeters (MMC) are one of the most promising devices to provide very high energy resolution needed for future astronomical x-ray spectroscopy. MMC detectors can be built to large detector arrays having thousands of pixels. Position-sensitive magnetic (PoSM) microcalorimeters consist of multiple absorbers thermally coupled to one magnetic micro calorimeter. Each absorber element has a different thermal coupling to the MMC, resulting in a distribution of different pulse shapes and enabling position discrimination between the absorber elements. PoSMs therefore achieve the large focal plane area with fewer number of readout channels without compromising spatial sampling. Excellent performance of PoSMs was achieved by optimizing the designs of key parameters such as the thermal conductance among the absorbers, magnetic sensor, and heat sink, as well as the absorber heat capacities. Micro fab ri - cation techniques were developed to construct four-absorber PoSMs, in which each absorber consists of a two-layer composite of bismuth and gold. The energy resolution (FWHM full width at half maximum) was measured to be better than 5 eV at 6 keV x-rays for all four absorbers. Position determination was demonstrated with pulse-shape discrimination, as well as with pulse rise time. X-ray microcalorimeters are usually designed to thermalize as quickly as possible to avoid degradation in energy resolution from position dependence to the pulse shapes. Each pixel consists of an absorber and a temperature sensor, both decoupled from the cold bath through a weak thermal link. Each pixel requires a separate readout channel; for instance, with a SQUID (superconducting quantum interference device). For future astronomy missions where thousands to millions of resolution elements are required, having an individual SQUID readout channel for each pixel becomes difficult. One route to attaining these goals is a position-sensitive detector in which a large continuous or pixilated array of x-ray absorbers shares fewer numbers of temperature sensors. A means of discriminating the signals from different absorber positions, however, needs to be built into the device for each sensor. The design concept for the device is such that the shape of the temperature pulse with time depends on the location of the absorber. This inherent position sensitivity of the signal is then analyzed to determine the location of the event precisely, effectively yielding one device with many sub-pixels. With such devices, the total number of electronic channels required to read out a given number of pixels is significantly reduced. PoSMs were developed that consist of four discrete absorbers connected to a single magnetic sensor. The design concept can be extended to more than four absorbers per sensor. The thermal conductance between the sensor and each absorber is different by design and consequently, the pulse shapes are different depending upon which absorber the xrays are received, allowing position discrimination. A magnetic sensor was used in which a paramagnetic Au:Er temperature-sensitive material is located in a weak magnetic field. Deposition of energy from an x-ray photon causes an increase in temperature, which leads to a change of magnetization of the paramagnetic sensor, which is subsequently read out using a low noise dc-SQUID. The PoSM microcalorimeters are fully microfabricated: the Au:Er sensor is located above the meander, with a thin insulation gap in between. For this position-sensitive device, four electroplated absorbers are thermally linked to the sensor via heat links of different thermal conductance. One pixel is identical to that of a single-pixel design, consisting of an overhanging absorber fabricated directly on top of the sensor. It is therefore very strongly thermally coupled to it. The three other absorbers are supported directly on a silicon-nitride membrane. These absorbers are thermally coupled to the sensor via Ti (5 nm)/Au250 nm) metal links. The strength of the links is parameterized by the number of gold squares making up the link. For detector performance, experimentally different pulse-shapes were demonstrated with 6 keV x-rays, which clearly show different rise times for different absorber positions. For energy resolution measurement, the PoSM was operated at 32 mK with an applied field that was generated using a persistent current of 50 mA. Over the four pixels, energy resolution ranges from 4.4 to 4.7 eV were demonstrated.

Bandler, SImon↗
DOE OSTI2018

A compressed sensing X-ray camera with a multilayer architecture

Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. In this work, we first illustrate the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Cryo-STEM Tomography with Inpainting

Traditionally, microscopists have worked with the Nyquist-Shannon theory of sampling, which states that to be able to reconstruct the image fully it needs to be sampled at a rate of at least twice the highest spatial frequency in the image. This sampling rate assumes that the image is sampled at regular intervals and that every pixel contains information that is crucial for the image (it even assumes that noise is important). Images in general, and especially low dose S/TEM images, contain significantly less information than can be encoded by a grid of pixels (which is why image compression works). Mathematically speaking, the image data has a low dimensional or sparse representation. Through the application of compressive sensing methods [1,2,3] this representation can be found using pre-designed measurements that are usually random for implementation simplicity. These measurements and the compressive sensing reconstruction algorithms have the added benefit of reducing noise. This reconstruction approach can be extended into higher dimensions, whereby the random sampling in each 2-D image can be extended into: a sequence of tomographic projections (i.e. tilt images); a sequence of video frames (i.e. incorporating temporal resolution and dynamics); spectral resolution (i.e. energy filtering an image to see the distribution of elements); and ptychography (i.e. sampling a full diffraction image at each location in a 2-D grid across the sample). This approach has been employed experimentally for materials science samples requiring low-dose imaging [2], and can be readily applied to biological samples. Figure 1 shows the resolution possible in a complex biological system, mouse pancreatic islet beta cells [4], when tomogram slices are reconstructed using subsampling. Reducing the number of pixels (1/6 pix and 1/3*1/3) shows minimal degradation compared to the reconstructions using all pixels (all data and 1/3 tilt). Although subsampling 1/6 of the tilts (1/6 of overall dose) degrades the reconstruction to the point that the cellular structures cannot be identified. Using 1/3 of both the pixels and the tilts provides a high quality image at 1/9 the overall dose even for this most basic and rapid demonstration of the CS methods. Figure 2 demonstrates the theoretical tomogram reconstruction quality (vertical axis) as undersampling (horizontal axis) is increased; we examined subsampling pixels and tilt-angles individually and a combined approach in which both pixels and tilts are sub-sampled. Note that subsampling pixels maintains high quality reconstructions (solid lines). Using the inpainting algorithm to obtain tomograms can automatically reduce the dose applied to the system by an order of magnitude. Perhaps the best way to understand the impact is to consider that by using inpainting (and with minimal hardware changes), a sample that can normally withstand a dose of ~10 e/Å2 can potentially be imaged with an “equivalent quality” to a dose level of 103 e/Å2. To put this in perspective, this is approaching the dose level used for the most advanced images, in terms of spatial resolution, for inorganic systems. While there are issues for biological specimens beyond dose (structural complexity being the most important one), this sampling approach allows the methods that are traditionally used for materials science to be applied to biological systems [5]. References: [1] A Stevens, H Yang, L Carin et al. Microscopy 63(1), (2014), pp. 41. [2] L Kovarik, A Stevens, A Liyu et al. Appl. Phys. Lett. 109, 164102 (2016) [3] A Stevens, L Kovarik, P Abellan et al. Adv. Structural and Chemical Imaging 1(10), (2015), pp. 1. [4] MD Guay, W Czaja, MA Aronova et al. Scientific Reports 6, 27614 (2016) [5] Supported by the Chemical Imaging, Signature Discovery, and Analytics in Motion Initiatives at PNNL. PNNL is operated by Battelle Memorial Inst. for the US DOE; contract DE-AC05-76RL01830.

Stevens, Andrew↗
DOE OSTI2024

Characterization and Optimization of Skipper CCDs for the SOAR Integral Field Spectrograph

We present results from the characterization and optimization of Skipper charge-coupled devices (CCDs) for use in a focal plane prototype for the Southern Astrophysical Research Integral Field Spectrograph (SIFS). We tested eight Skipper CCDs and selected six for SIFS based on performance results. The Skipper CCDs are 6k × 1k, 15 μm pixels, thick, fully depleted, p-channel devices that have been thinned to ~250 μm, backside processed, and treated with an anti-reflective coating. We demonstrate a single-sample readout noise of <4.3 e - rms pixel -1 in all amplifiers. We optimize the readout sequence timing to achieve a readout noise of 0.5 e - rms pixel -1 after 74 non-destructive measurements, which can be accomplished in a region covering 5% of the detector area in a readout time of <4 minutes. We demonstrate single-photon-counting in all 24 amplifiers (four amplifiers per detector) with a readnoise of σ N ~ 0.18 e - rms pixel -1 after N samp = 400 samples, and we constrain the degree of nonlinearity to be ≲1% at low signal levels (0 e - to 50 e - ). Clock-induced charge (CIC) remains an important issue when the Skipper CCD is configured to provide a large full-well capacity. We achieve a CIC rate of <1.45 × 10 -3 e - pixel -1 frame -1 for a full-well capacity of ~900 e - , which increases to a CIC rate of ~3 e - pixel -1 frame -1 for full-well capacities ~40,000-65,000 e - . We also perform conventional CCD characterization measurements such as charge transfer inefficiency (3.44 × 10 -7 on average), dark current (~2 × 10 -4 e - pixel -1 s -1 ), photon transfer curves, cosmetic defects (<0.45% “bad” pixels), and charge diffusion (point-spread function < 7.5 μm) to verify that these properties are consistent with expectations from conventional p-channel CCDs used for astronomy. Furthermore, we provide the first measurements of the brighter-fatter effect and absolute quantum efficiency (≳80% between 450 and 980 nm; ≳90% between 600 and 900 nm) using Skipper CCDs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1980

Development of a universal water signature for the LANDSAT-3 Multispectral Scanner, part 2 of 2

A generalized four-channel hyperplane to discriminate water from non-water was developed using LANDSAT-3 multispectral scanner (MSS) scences and matching same/next-day color infrared aerial photography. The MSS scenes over upstate New York, eastern Washington, Montana and Louisiana taken between May and October 1978 varied in Sun elevation angle from 40 to 58 degrees. The 28 matching air photo frames selected for analysis contained over 1400 water bodies larger than one surface acre. A preliminary water discriminant was used to screen the data and eliminate from further consideration all pixels distant from water in MSS spectral space. Approximately 1300 pixels, half of them non-edge water pixels and half non-water pixels spectrally close to water, were labelled. A linear discriminant was iteratively fitted to the labelled pixels, giving more weight to those pixels that were difficult to discriminate. This discriminant correctly classified 98.7 percent of the water pixels and 98.6 percent of the non-water pixels.

Schlosser, E. H.↗