Results for “PSF estimation”

DOE OSTI2021

PSF Estimation in Crowded Astronomical Imagery as a Convolutional Dictionary Learning Problem

In this paper, we present a new algorithm for estimating the Point Spread Function (PSF) in wide-field astronomical images with extreme source crowding. Robust and accurate PSF estimation in crowded astronomical images dramatically improves the fidelity of astrometric and photometric measurements extracted from wide-field sky monitoring imagery. Our radically new approach utilizes convolutional sparse representations to model the continuous functions involved in the image formation. This approach avoids the need to detect and precisely localize individual point sources that is shared by existing methods. In experiments involving simulated astronomical imagery, it significantly outperforms the recent alternative method with which it is compared.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Dark Energy Survey Year 6 Results: Point-Spread Function Modeling

We present the point-spread function (PSF) modeling for weak lensing shear measurement using the full six years of the Dark Energy Survey (DES Y6) data. We review the PSF estimation procedure using the PIFF (PSFs In the Full FOV) software package and describe the key improvements made to PIFF and modeling diagnostics since the DES year three (Y3) analysis: (i) use of external Gaia and infrared photometry catalogs to ensure higher purity of the stellar sample used for model fitting, (ii) addition of color-dependent PSF modeling, the first for any weak lensing analysis, and (iii) inclusion of model diagnostics inspecting fourth-order moments, which can bias weak lensing measurements to a similar degree as second-order modeling errors. Through a comprehensive set of diagnostic tests, we demonstrate the improved accuracy of the Y6 models evident in significantly smaller systematic errors than those of the Y3 analysis, in which all g band data were excluded due to insufficiently accurate PSF models. For the Y6 weak lensing analysis, we include g band photometry data in addition to the riz bands, providing a fourth band for photometric redshift estimation. Looking forward to the next generation of wide-field surveys, we describe several ongoing improvements to PIFF, which will be the default PSF modeling software for weak lensing analyses for the Vera C. Rubin Observatory’s Legacy Survey of Space and Time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2005

Quickbird Satellite in-orbit Modulation Transfer Function (MTF) Measurement Using Edge, Pulse and Impulse Methods for Summer 2003

The spatial characteristics of an imaging system cannot be expressed by a single number or simple statement. However, the Modulation Transfer Function (MTF) is one approach to measure the spatial quality of an imaging system. Basically, MTF is the normalized spatial frequency response of an imaging system. The frequency response of the system can be evaluated by applying an impulse input. The resulting impulse response is termed the Point Spread function (PSF). This function is a measure of the amount of blurring present in the imaging system and is itself a useful measure of spatial quality. An underlying assumption is that the imaging system is linear and shift-independent. The Fourier transform of the PSF is called the Optical Transfer Function (OTF) and the normalized magnitude of the OTF is the MTF. In addition to using an impulse input, a knife-edge in technique has also been used in this project. The sharp edge exercises an imaging system at all spatial frequencies. The profile of an edge response from an imaging system is called an Edge Spread Function (ESF). Differentiation of the ESF results in a one-dimensional version of the Point Spread Function (PSF). Finally, MTF can be calculated through use of Fourier transform of the PSF as stated previously. Every image includes noise in some degree which makes MTF of PSF estimation more difficult. To avoid the noise effects, many MTF estimation approaches use smooth numerical models. Historically, Gaussian models and Fermi functions were applied to reduce the random noise in the output profiles. The pulse-input method was used to measure the MTF of the Landsat Thematic Mapper (TM) using 8th order even functions over the San Mateo Bridge in San Francisco, California. Because the bridge width was smaller than the 30-meter ground sample distance (GSD) of the TM, the Nyquist frequency was located before the first zero-crossing point of the sinc function from the Fourier transformation of the bridge pulse. To avoid the zero-crossing points in the frequency domain from a pulse, the pulse width should be less than the width of two pixels (or 2 GSD's), but the short extent of the pulse results in a poor signal-to-noise ratio. Similarly, for a high-resolution satellite imaging system such as Quickbird, the input pulse width was critical because of the zero crossing points and noise present in the background area. It is important, therefore, that the width of the input pulse be appropriately sized. Finally, the MTF was calculated by taking ratio between Fourier transform of output and Fourier transform of input. Regardless of whether the edge, pulse and impulse target method is used, the orientation of the targets is critical in order to obtain uniformly spaced sub-pixel data points. When the orientation is incorrect, sample data points tend to be located in clusters that result in poor reconstruction of the edge or pulse profiles. Thus, a compromise orientation must be selected so that all spectral bands can be accommodated. This report continues by outlining the objectives in Section 2, procedures followed in Section 3, descriptions of the field campaigns in Section 4, results in Section 5, and a brief summary in Section 6.

Helder, Dennis↗

DOE OSTI2022

Uncertainty Quantification for Point Spread Functions in X-Ray Radiography

X-ray radiographers have tools for estimating the point spread function (PSF) which determines the extent of the blur in images. Knowledge of uncertainties in their estimations can be extremely valuable, and existing methods do not provide this information. We have developed a new technique using a Bayesian framework that will provide useful uncertainties to the estimated PSF.

point spread function↗

NASA NTRS1988

Comparative point-spread function calculations for the MOMS-1, Thematic Mapper and SPOT-HRV instruments

Point-spread functions (PSF) comparisons were made between the Modular Optoelectronic Multispectral Scanner (MOMS-01), the LANDSAT Thematic Mapper (TM) and the SPOT-HRV instruments, principally near Lake Nakuru, Kenya. The results, expressed in terms of the width of the point spread functions at the 50 percent power points as determined from the in-scene analysis show that the TM has a PSF equal to or narrower than the MOMS-01 instrument (50 to 55 for the TM versus 50 to 68 for the MOMS). The SPOT estimates of the PSF range from 36 to 40. When the MOMS results are adjusted for differences in edge scanning as compared to the TM and SPOT, they are nearer 40 in the 575 to 625 nm band.

Salomonson, V. V.↗

NASA NTRS1983

Spatial resolution estimation of LANDSAT-4 TM and MSS data

In order to verify that the LANDSAT-4 sensors are operating within specifications, it is useful to estimate the system parameters by analysis of the measured data. One parameter of particular interest is the sensor point-spread function (PSF) which determines the resolution of the system. A method of estimating the PSF is described that utilizes data obtained during scanning of ground elements having identifiable geometric and radiometric structure. These data are then processed in such a manner as to recover either the PSF itself or to estimate the parameters of an assumed functional representation of the PSF.

Mcgillem, C. D.↗

NASA NTRS1986

Astronomical imaging by filtered weighted-shift-and-add technique

The weighted-shift-and-add speckle imaging technique is analyzed using simple assumptions. The end product is shown to be a convolution of the object with a typical point-spread function (psf) that is similar in shape to the telescope psf and depends marginally on the speckle psf. A filter can be applied to each data frame before locating the maxima, either to identify the speckle locations (matched filter) or to estimate the instantaneous atmospheric psf (Wiener filter). Preliminary results show the power of the technique when applied to photon-limited data and to extended objects.

Ribak, Erez↗

NASA NTRS1993

X-ray evidence for particulate contamination on the AXAF VETA-1 mirrors

X-ray testing of the AXAF outer mirror pairs, in the VETA-1 configuration, reveals a point spread function (PSF) with unexpectedly large wings at low energies. Although the angular dependence in the wings of the PSF is close to that expected for diffractive scattering from surface roughness, the energy dependence differs substantially. Analyses of the observed X-ray PSF, images near ring focus, and single-quadrant images at conjugate focus suggest that the excess scattering observed at low X-ray energies results from diffractive scattering by relatively small grains (as small as a few tenths micrometer in radius). We develop a simple model for the contribution of scattering by particulates to the PSF. Merging this model with that for scattering by surface roughness, we fit the combined model to the observed energy-dependent PSF, in order to estimate parameters and associated uncertainties characterizing the grain-size distribution and the surface-roughness power spectral density. In particular, we find that the fractional coverage of the mirrors by particulates is approximately 1 x 10 exp -4 (for grain radii between 0.1 and 10 microns), and that the rms surface-roughness is approximately 0.7 nm (for spatial frequencies between 1/mm and 1000/mm).

O'Dell, S. L.↗

NASA NTRS1985

Spatial Resolution Estimation of LANDSAT-4 Thematic Mapper Data

The problem of estimating the overall point-spread function (PSF) of multispectral scanner systems was studied using real scene data and known geometric structures in the scene. A direct solution to an approximate form of the PSF was made along with a method using the derivative of an estimated edge response. Both results agreed closely. The TM scanner system specifications are given in line-spread function width and these values are listed with the experimental results in terms of meters. The estimated values are very reasonable, considering the number of factors which could be influencing the result. The atmosphere will have a blurring effect on the overall PSF as well as on cubic convolution resampling effects and possible electronic effects not accounted for in the specification. Also, the specific definition of the LSF specification is not known nor is the actual altitude at the instant the data were acquired. Thus the nominal overall PSF half-amplitude width of 39 m is reasonable; however, a greater sample of scene objects should be evaluated to furthur verify this result.

Mcgillem, C. D.↗

DOE OSTI2025

Chromatic effects on the PSF and shear measurement for the Roman Space Telescope High-Latitude Wide Area Survey

Weak gravitational lensing (WL) is a key cosmological probe that requires precise measurement of galaxy images to infer shape distortions, or shear, and constrain cosmology. Accurate estimation of the point spread function (PSF) is crucial for shear measurement, but the wavelength dependence of the PSF introduces chromatic biases that can systematically impact shear inference. We focus on biases arising from spectral energy distribution (SED) differences between stars, used for PSF modelling, and galaxies, used for shear measurement. We investigate these effects in Roman’s four design reference mission WL bands (Y106, J129, H158, F184) and wide filter (W146). Using Roman-like image simulations, we quantify the induced shear biases and compare them to requirements on those biases. Multiplicative biases over all galaxies hover around ~0.2 per cent in the WL bands and 2 per cent in the wide filter, exceeding the mission requirement of |m| < 0.032 per cent and relaxed requirement of |m| < 0.1 per cent⁠. In individual redshift bins, biases can reach 0.4–0.9 per cent for the WL bands and 3–6 per cent for the wide filter. Additive biases remain acceptable in the WL bands but exceed systematic limits in the wide filter. We develop and test PSF-level corrections, showing that a first-order correction reduces biases within survey requirements for the WL bands; however, higher-order terms are necessary for the wide filter. Our results highlight the necessity of chromatic corrections for precision WL with Roman and provide a framework for mitigating these biases. Finally, we compare analytical colour-based corrections to self-organizing maps and find that both methods effectively reduce biases.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1983

Estimation of a remote sensing system point-spread function from measured imagery

A general approach to identifying the point spread function (PSF) of a remotely sensed scene is demonstrated in terms of a step function for an abrupt change in the gray level along the row or column of the image data. The estimate of the PSF is made in terms of a finite sum of basis functions, employing a sequence of rectangular pulses covering the spatial extent of the PSF. The approximation, if narrow impulses are employed, provides accurate fidelity to the PSF. The method becomes practical when the geometrical structure of the scene elements producing the measured response is known. The field boundary is obtained through consideration of the differing intensities on each side of the boundary, which is a step discontinuity. The mathematical procedure for the technique is provided, together with a sample problem from Landsat-4 Thematic Mapper data. Atmospheric blurring and electronic effects on the overall PSF and the cubic convolution resampling effects are noted.

Mcgillem, C. D.↗

DOE OSTI2021

Impact of point spread function higher moments error on weak gravitational lensing

ABSTRACT Weak gravitational lensing is one of the most powerful tools for cosmology, while subject to challenges in quantifying subtle systematic biases. The point spread function (PSF) can cause biases in weak lensing shear inference when the PSF model does not match the true PSF that is convolved with the galaxy light profile. Although the effect of PSF size and shape errors – i.e. errors in second moments – is well studied, weak lensing systematics associated with errors in higher moments of the PSF model require further investigation. The goal of our study is to estimate their potential impact for LSST weak lensing analysis. We go beyond second moments of the PSF by using image simulations to relate multiplicative bias in shear to errors in the higher moments of the PSF model. We find that the current level of errors in higher moments of the PSF model in data from the Hyper Suprime-Cam survey can induce a ∼0.05 per cent shear bias, making this effect unimportant for ongoing surveys but relevant at the precision of upcoming surveys such as LSST.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Legacy Survey of Space and Time Data Preview 2

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Legacy Survey of Space and Time Data Preview 2: deep_coadd dataset type

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release This dataset is a subset of the full data release consisting of the deep_coadd dataset type. These are the combination of multiple processed, calibrated, and background- subtracted images, for a patch of sky, for each of the six filters. This release contains 925,460 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Legacy Survey of Space and Time Data Preview 2: survey property dataset type

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release This dataset is a subset of the full data release consisting of the survey property dataset type. These are healSparse property maps for the survey. This release contains 84 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Legacy Survey of Space and Time Data Preview 2: dia_source dataset type

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release This dataset is a subset of the full data release consisting of the dia_source dataset type. These are measurements for detected sources in difference images. This release contains 2,112 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Legacy Survey of Space and Time Data Preview 2: DiaSource searchable catalog

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release This dataset is a subset of the full data release consisting of a searchable catalog named DiaSource. This catalog contains measurements for detected sources in difference images. This catalog contains 1,000,825,975 rows with 90 columns.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Legacy Survey of Space and Time Data Preview 2: dia_object dataset type

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release This dataset is a subset of the full data release consisting of the dia_object dataset type. These are derived properties for transient and variable objects. This release contains 2,112 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗