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Image recovery at a resolution limited only by diffraction is now possible at large telescopes. The theory of speckle image reconstruction is explained and the current status of a video recording and digitization system for the reconstruction procedure is described. Potential applications of the process when used with very large telescopes are discussed. The constraints on telescope design imposed by these techniques are listed.
Spatial quality of an imaging sensor can be estimated by evaluating its modulation transfer function (MTF) from many different sources such as a sharp edge, a pulse target, or bar patterns with different spatial frequencies. These well-defined targets are frequently used for prelaunch laboratory tests, providing very reliable and accurate MTF measurements. A laboratory-quality edge input source was included in the spatial-mode operation of the Spectroradiometric Calibration Assembly (SRCA), which is one of the onboard calibrators of the Moderate Resolution Imaging Spectroradiometer (MODIS). Since not all imaging satellites have such an instrument, SRCA MTF estimations can be used as a reference for an on-orbit lunar MTF algorithm and results. In this paper, the prelaunch spatial quality characterization process from the Integrated Alignment Collimator and SRCA is briefly discussed. Based on prelaunch MTF calibration using the SRCA, a lunar MTF algorithm is developed and applied to the lifetime on-orbit Terra and Aqua MODIS lunar collections. In each lunar collection, multiple scan-directionMoon-to-background transition profiles are aligned by the subpixel edge locations from a parametric Fermi function fit. Corresponding accumulated edge profiles are filtered and interpolated to obtain the edge spread function (ESF). The MTF is calculated by applying a Fourier transformation on the line spread function through a simple differentiation of the ESF. The lifetime lunar MTF results are analyzed and filtered by a relationship with the Sun-Earth-MODIS angle. Finally, the filtered lunarMTF values are compared to the SRCA MTF results. This comparison provides the level of accuracy for on-orbit MTF estimations validated through prelaunch SRCA measurements. The lunar MTF values had larger uncertainty than the SRCA MTF results; however, the ratio mean of lunarMTF fit and SRCA MTF values is within 2% in the 250- and 500-m bands. Based on the MTF measurement uncertainty range, the suggested lunar MTF algorithm can be applied to any on-orbit imaging sensor with lunar calibration capability.
The Goldstone Deep Space Station ground-based synthetic aperture radar system has been used to obtain radar images of Venus with resolutions of close to 1.3 km. Observations were made at 12.5 cm wavelength using circular polarization. From 12 days of observations during the 1986 inferior conjunction, three images have been selected for initial processing. The images show remarkable surface features including craters, ridges, and regions of high Fresnel reflectivity in the plains region.
The automated detection of defects in high-angle annular dark-field Z-contrast (HAADF) scanning-transmission-electron microscopy (STEM) images has been a major challenge. Here, we report an approach for the automated detection and categorization of structural defects based on changes in the material’s local atomic geometry. The approach applies geometric graph theory to the already-found positions of atomic-column centers and is capable of detecting and categorizing any defect in thin diperiodic structures (i.e., “2D materials”) and a large subset of defects in thick diperiodic structures (i.e., 3D or bulk-like materials). Despite the somewhat limited applicability of the approach in detecting and categorizing defects in thicker bulk-like materials, it provides potentially informative insights into the presence of defects. The categorization of defects can be used to screen large quantities of data and to provide statistical data about the distribution of defects within a material. This methodology is applicable to atomic column locations extracted from any type of high-resolution image, but here we demonstrate it for HAADF STEM images.
High-resolution, calibrated images of the near-nucleus regions of Halley, Giacobini-Zinner (for ICE encounter) and additional comets displaying widely differing levels of activity were acquired with a CCD sensor at the Cassegrain focus of the 3.6 m Canada-France-Hawaii Telescope (CFHT). The International Halley Watch designated interference filters were used. Successful correlation of ICE magnetic field data with the optical images obtained with the CFHT on the night of encounter (11 Sept. 1985) primarily through the H2O(+) and neighboring continuum passbands and with 300 km spatial resolution provokes reinterpretation of the observed structure of cometary ion tails. The observations of Halley, limited by bad weather, were made at significant periods of the apparition: the first, in December 1984 with the comet at 5.3 AU during the period of the onset of activity; and the last, in November 1985 with the comet near opposition. The December observations show evidence of residual activity. The 18 November data show a highly-condensed inner coma with an extreme falloff in brightness from the region of the nucleus. These data provide the basis for characterizing the gas and dust environment in the immediate vicinity of the active nucleus.
Kelvin probe force microscopy (KPFM) was used to image and co-locate the presence of hydrogen in stainless steel (SS) with microstructure. Various SS samples were investigated, including forged, welded, LENS® fabricated, and pinch welded materials. KPFM images the local work function of a surface as a function of spatial position using atomic force microscopy. KPFM is capable of delivering high spatial (~10 nm) and potential (~5mV) resolution maps characterizing the microstrucure and the locally varying work function of surfaces. Hydrogen segregated at the surface of SS increases the local work function by either reducing tensile strain or by reducing the chemical potential of surface species. In a process known as hydrogen embrittlement, hydrogen segregates to and becomes trapped at extended defects (e.g. dislocations, boundaries, pores) which leads to the initiation of cracking and can result in structural failure. Hydrogen storage necessitates a proper understanding of the mechanisms of hydrogen embrittlement in SS. Developing advanced characterization techniques for hydrogen embrittlement is critical to identify long term solutions for materials exposed to hydrogen. Current techniques of observing hydrogen embrittlement involve mechanical testing, and optical microscopy with low resolution. Advance microstructural imaging techniques capable of resolving features down to the nanometer scale are needed. KPFM provides high resolution imaging for the characterization and development of SS components for hydrogen storage.
Abstract Atom segmentation and localization, noise reduction and deblurring of atomic-resolution scanning transmission electron microscopy (STEM) images with high precision and robustness is a challenging task. Although several conventional algorithms, such has thresholding, edge detection and clustering, can achieve reasonable performance in some predefined sceneries, they tend to fail when interferences from the background are strong and unpredictable. Particularly, for atomic-resolution STEM images, so far there is no well-established algorithm that is robust enough to segment or detect all atomic columns when there is large thickness variation in a recorded image. Herein, we report the development of a training library and a deep learning method that can perform robust and precise atom segmentation, localization, denoising, and super-resolution processing of experimental images. Despite using simulated images as training datasets, the deep-learning model can self-adapt to experimental STEM images and shows outstanding performance in atom detection and localization in challenging contrast conditions and the precision consistently outperforms the state-of-the-art two-dimensional Gaussian fit method. Taking a step further, we have deployed our deep-learning models to a desktop app with a graphical user interface and the app is free and open-source. We have also built a TEM ImageNet project website for easy browsing and downloading of the training data.
Solid-state, electronically scanned, linear detector arrays are now available which can be used in a pushbroom scan mode imaging system for high-resolution multispectral earth resource survey applications. These arrays provide high performance in the visible to near-IR region. Two performance criteria must be assessed in the choice of a detector array: signal-to-noise ratio and spectral response. Consideration of diffraction limitations shows that optics size cannot be significantly reduced by using very low-noise detectors. The required spectral response for a viable detector array should not have spectral ripples that cause a low-level, but significant, error in the detected effective reflectance of the target.
The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a high spatial resolution, multispectral imager with along-track stereo capabilities scheduled for launch on the first NASA spacecraft of the Earth Observing System (EOS AM-1) in mid-1999.
Plant cell signaling often relies on the cellular organization of receptor-like kinases (RLKs) within membrane nanodomains to enhance signaling specificity and efficiency. Thus, nanometer-scale quantitative analysis of spatial organizations of RLKs could provide new understanding of mechanisms underlying plant responses to environmental stress. Here, we used stochastic optical reconstruction fluorescence microscopy (STORM) to quantify the colocalization of the flagellin-sensitive-2 (FLS2) receptor and the nanodomain marker, remorin, within Arabidopsis thaliana root hair cells. We found that recovery of FLS2 and remorin in the plasma membrane, following ligand-induced internalization by bacterial-flagellin-peptide (flg22), reached ~85% of their original membrane density after ~90 min. The pairs colocalized at the membrane at greater frequencies, compared with simulated randomly distributed pairs, except for directly after recovery, suggesting initial uncoordinated recovery followed by remorin and FLS2 pairing in the membrane. The purinergic receptor, P2K1, colocalized with remorin at similar frequencies as FLS2, while FLS2 and P2K1 colocalization occurred at significantly lower frequencies, suggesting that these RLKs mostly occupy distinct nanodomains. The chitin elicitor receptor, CERK1, colocalized with FLS2 and remorin at much lower frequencies, suggesting little coordination between CERK1 and FLS2. These findings emphasize STORM’s capacity to observe distinct nanodomains and degrees of coordination between plant cell receptors, and their respective immune pathways.
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Optical imaging of QSO 2305 + 187 with resolution ranging from 0.1 to 1.0 arcsec in continuum and line emission is presented. The data are from FOCAM and the HR Cam of the Canada-France-Hawaii Telescope, and the Wide Field Camera of the Hubble Space Telescope. These are compared with previously published optical and radio images. The QSO host galaxy has the basic properties of an elliptical, but has significant irregularities, and tidal tails which indicate an ongoing gravitational interaction with a close companion.
Abstract Confocal imaging has shown that CELLULOSE SYNTHASE (CESA) particles move through the plasma membrane as they synthesize cellulose. However, the resolution limit of confocal microscopy circumscribes what can be discovered about these tiny biosynthetic machines. Here, we applied Structured Illumination Microscopy (SIM), which improves resolution two-fold over confocal or widefield imaging, to explore the dynamic behaviors of CESA particles in living plant cells. SIM imaging reveals that Arabidopsis thaliana CESA particles are more than twice as dense in the plasma membrane as previously estimated, helping explain the dense arrangement of cellulose observed in new wall layers. CESA particles tracked by SIM display minimal variation in velocity, suggesting coordinated control of CESA catalytic activity within single complexes and that CESA complexes might move steadily in tandem to generate larger cellulose fibrils or bundles. SIM data also reveal that CESA particles vary in their overlaps with microtubule tracks and can complete U-turns without changing speed. CESA track patterns can vary widely between neighboring cells of similar shape, implying that cellulose patterning is not the sole determinant of cellular growth anisotropy. Together, these findings highlight SIM as a powerful tool to advance CESA imaging beyond the resolution limit of conventional light microscopy.
Plans are underway at NASA Goddard to develop a moderate-resolution (0.5-1.0-km) imaging spectrometer with 104 spectral bands in the range from 0.4 to 14.2 microns for use as a NASA facility aboard the Space Station Earth Observation System. Science requirements call for the system to image the earth's surface every 2 d for a period of 10 yr, using two electrooptic sensors. MODIS-T (tilt) has 64 10-nm-wide channels in the 400-1000-nm range. The system has 5-cm-diameter optics, scans + or - 45 deg, and can be pointed + or - 60 deg along track. Calculated S/N is in excess of 800:1 near 400 nm. MODIS-N (nadir) scans + or - 45 deg about nadir with 12 500-m- and 28 1000-m-resolution channels, including two polarization channels and 14 thermal-IR channels. With 20-cm-diameter optics the calculated S/N of the majority of the reflected solar bands is over 1000:1. NETD values for the thermal bands are on the order of 0.1-0.2 K at 300 K. Combined MODIS-T and MODIS-N data rates are 8.3 Mb/s in daylight and 1.5 Mb/s at night, resulting in a total of 360 Gb/d.
Data acquisition, initial site characterization, image and geographic information methods available, and brief evaluations of first-year for NASA's Thematic Mapper (TM) working group are presented. The TM and other spectral data are examined in order to relate local, intensive ecosystem research findings to estimates of carbon cycling rates over wide geographic regions. The effort is to span environments ranging from dry to moist climates and from good to poor site quality using the TM capability, with and without the inclusion of geographic information system (GIS) data, and thus to interpret the local spatial pattern of factors conditioning biomass or productivity. Twenty-eight TM data sets were acquired, archived, and evaluated. The ERDAS image processing and GIS system were installed on the microcomputer (PC-AT) and its capabilities are being investigated. The TM coverage of seven study areas were exported via ELAS software on the Prime to the ERDAS system. Statistical analysis procedures to be used on the spectral data are being identified.
Externally segmented germanium detectors promise a breakthrough in gamma-ray imaging capabilities while retaining the superb energy resolution of germanium spectrometers. An angular resolution of 0.2 deg becomes practical by combining position-sensitive germanium detectors having a segment thickness of a few millimeters with a one-dimensional coded aperture located about a meter from the detectors. Correspondingly higher angular resolutions are possible with larger separations between the detectors and the coded aperture. Two-dimensional images can be obtained by rotating the instrument. Although the basic concept is similar to optical or X-ray coded-aperture imaging techniques, several complicating effects arise because of the penetrating nature of gamma rays. The complications include partial transmission through the coded aperture elements, Compton scattering in the germanium detectors, and high background count rates. Extensive electron-photon Monte Carlo modeling of a realistic detector/coded-aperture/collimator system has been performed. Results show that these complicating effects can be characterized and accounted for with no significant loss in instrument sensitivity.
MLExchange is a machine learning (ML) operations platform providing web user-interfaces (UIs) for data visualization and analysis pipelines at synchrotron facilities. Among these UIs is the segmentation app which helps synchrotron users utilize ML algorithms to automatically segment high-resolution scientific images with minimal manual annotation effort. In this work, we share code optimizations that significantly speed up the segmentation inference workflow of large data in short time. By optimizing the sequence of CPU-GPU data transfers and introducing CPU parallelization to key operations, we improve the per-device, per-image frame computational efficiency and observe close to 3×$$\times$$ speedup over the original segmentation inference workflow run time when utilizing a single GPU. Further adaptations enabling multi-GPU inference yield more than 40×$$\times$$ speedup with 100 GPUs compared to the optimized single GPU inference workflow. This acceleration of the segmentation inference workflow will provide MLExchange users with easy access to segmentation results with little wait time.
Various approaches are considered to the solution of the electron-optical problem of designing an image tube configuration. Emphasis is placed on the method of computer design, and an illustration is given in which the technique is used in the design of an 80-mm image tube with a zoom capability of 3:1. The solutions are discussed to such problems as image distortion, magnification, and electron bundles striking the zoom electrode. Three types of an electron-optical configuration are examined for the electron-optic limitations to resolution: (1) the proximity image tube, (2) the magnetic-type image tube having uniform electric and magnetic fields, and (3) the electrostatic-type image tube such as the 80-mm zoom tube.