scholarly journals Accurate Photometry of Saturated Stars Using the Point-spread-function Wing Technique with Spitzer

2022 ◽  
Vol 163 (2) ◽  
pp. 46
Author(s):  
Kate Y. L. Su ◽  
G. H. Rieke ◽  
M. Marengo ◽  
Everett Schlawin
Keyword(s):  
Point Spread Function ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Large Radius ◽  
Point Spread ◽  
Primary Sample ◽  
Spread Function ◽  
Optical Stability ◽  
Flux Calibration ◽  
Better Than

Abstract We report Spitzer 3.6 and 4.5 μm photometry of 11 bright stars relative to Sirius, exploiting the unique optical stability of the Spitzer Space Telescope point-spread function (PSF). Spitzer's extremely stable beryllium optics in its isothermal environment enables precise comparisons in the wings of the PSF from heavily saturated stars. These bright stars stand as the primary sample to improve stellar models, and to transfer the absolute flux calibration of bright standard stars to a sample of fainter standards useful for missions like JWST and for large ground-based telescopes. We demonstrate that better than 1% relative photometry can be achieved using the PSF wing technique in the radial range of 20″–100″ for stars that are fainter than Sirius by 8 mag (from outside the saturated core to a large radius where a high signal-to-noise ratio profile can still be obtained). We test our results by (1) comparing the [3.6]−[4.5] color with that expected between the WISE W1 and W2 bands, (2) comparing with stars where there is accurate K S photometry, and (3) also comparing with relative fluxes obtained with the DIRBE instrument on COBE. These tests confirm that relative photometry is achieved to better than 1%.

An Approach to Measuring the Point Spread Function of the Confocal Raman Microscope

2020 ◽  
Vol 74 (10) ◽  
pp. 1230-1237
Author(s):  
Xiang Ding ◽  
Yanzhe Fu ◽  
Jiyan Zhang ◽  
Yao Hu ◽  
Shihang Fu
Keyword(s):  
Image Quality ◽  
Size Effect ◽  
Point Spread Function ◽  
Performance Indicator ◽  
Signal To Noise Ratio ◽  
Polystyrene Microspheres ◽  
Point Spread ◽  
Spread Function ◽  
Confocal Raman

The confocal Raman microscope (CRM) is a powerful tool in analytical science. Image quality is the most important performance indicator of CRM systems. The point spread function (PSF) is one of the most useful tools to evaluate the image quality of microscopic systems. A method based on a point-like object is proposed to measure the PSF of CRM, and the size effect of spherical objects is discussed. A series of phantoms are fabricated by embedding different sizes of polystyrene microspheres into polydimethylsiloxane matrix. The diameters of microspheres are from 0.2 µm to 5 µm. The phantoms are tested by measuring the PSF of a commercial CRM whose nominal lateral resolution is about 1 µm. Results of the PSF are obtained and the accuracy of resolution is used to evaluate the size effect of the microspheres. Experimental results are well consistent with theoretical analysis. The error of the PSF can be decreased by reducing the diameter of the microsphere but meanwhile the signal-to-noise ratio (S/N) will be lowered as well. The proper diameter of microspheres is proposed in consideration of the trade-off between the S/N and the measurement error of the PSF. Results indicate that the method provides a useful approach to measurement of the PSF and the resolution of the CRM.

scholarly journals Point-spread Function Deconvolution of the IFU Data and Restoration of Galaxy Stellar Kinematics

2021 ◽  
Vol 257 (2) ◽  
pp. 66
Author(s):  
Haeun Chung ◽  
Changbom Park ◽  
Yong-Sun Park
Keyword(s):  
Point Spread Function ◽  
Performance Test ◽  
Spatial Information ◽  
Signal To Noise Ratio ◽  
Line Of Sight ◽  
Stellar Kinematics ◽  
Point Spread ◽  
Deconvolution Algorithm ◽  
Spread Function ◽  
Field Unit

Abstract We present a performance test of the point-spread function (PSF) deconvolution algorithm applied to astronomical integral field unit (IFU) spectroscopy data for restoration of galaxy kinematics. We deconvolve the IFU data by applying the Lucy–Richardson algorithm to the 2D image slice at each wavelength. We demonstrate that the algorithm can effectively recover the true stellar kinematics of the galaxy, by using mock IFU data with a diverse combination of surface brightness profile, signal-to-noise ratio, line-of-sight geometry, and line-of-sight velocity distribution (LOSVD). In addition, we show that the proxy of the spin parameter λ R e can be accurately measured from the deconvolved IFU data. We apply the deconvolution algorithm to the actual SDSS-IV MaNGA IFU survey data. The 2D LOSVD, geometry, and λ R e measured from the deconvolved MaNGA IFU data exhibit noticeable differences compared to the ones measured from the original IFU data. The method can be applied to any other regular-grid IFU data to extract the PSF-deconvolved spatial information.

scholarly journals Reconstructed spatial resolution and contrast recovery with Bayesian penalized likelihood reconstruction (Q.Clear) for FDG-PET compared to time-of-flight (TOF) with point spread function (PSF)

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Julian M. Rogasch ◽  
Said Suleiman ◽  
Frank Hofheinz ◽  
Stephanie Bluemel ◽  
Mathias Lukas ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Point Spread Function ◽  
Activity Concentration ◽  
Signal To Noise Ratio ◽  
Time Of Flight ◽  
Penalized Likelihood ◽  
Systematic Evaluation ◽  
Point Spread ◽  
Spread Function ◽  
Relative Differences

Abstract Background Bayesian penalized likelihood reconstruction for PET (e.g., GE Q.Clear) aims at improving convergence of lesion activity while ensuring sufficient signal-to-noise ratio (SNR). This study evaluated reconstructed spatial resolution, maximum/peak contrast recovery (CRmax/CRpeak) and SNR of Q.Clear compared to time-of-flight (TOF) OSEM with and without point spread function (PSF) modeling. Methods The NEMA IEC Body phantom was scanned five times (3 min scan duration, 30 min between scans, background, 1.5–3.9 kBq/ml F18) with a GE Discovery MI PET/CT (3-ring detector) with spheres filled with 8-, 4-, or 2-fold the background activity concentration (SBR 8:1, 4:1, 2:1). Reconstruction included Q.Clear (beta, 150/300/450), “PSF+TOF4/16” (iterations, 4; subsets, 16; in-plane filter, 2.0 mm), “OSEM+TOF4/16” (identical parameters), “PSF+TOF2/17” (2 it, 17 ss, 2.0 mm filter), “OSEM+TOF2/17” (identical), “PSF+TOF4/8” (4 it, 8 ss, 6.4 mm), and “OSEM+TOF2/8” (2 it, 8 ss, 6.4 mm). Spatial resolution was derived from 3D sphere activity profiles. RC as (sphere activity concentration [AC]/true AC). SNR as (background mean AC/background AC standard deviation). Results Spatial resolution of Q.Clear150 was significantly better than all conventional algorithms at SBR 8:1 and 4:1 (Wilcoxon, each p < 0.05). At SBR 4:1 and 2:1, the spatial resolution of Q.Clear300/450 was similar or inferior to PSF+TOF4/16 and OSEM+TOF4/16. Small sphere CRpeak generally underestimated true AC, and it was similar for Q.Clear150/300/450 as with PSF+TOF4/16 or PSF+TOF2/17 (i.e., relative differences < 10%). Q.Clear provided similar or higher CRpeak as OSEM+TOF4/16 and OSEM+TOF2/17 resulting in a consistently better tradeoff between CRpeak and SNR with Q.Clear. Compared to PSF+TOF4/8/OSEM+TOF2/8, Q.Clear150/300/450 showed lower SNR but higher CRpeak. Conclusions Q.Clear consistently improved reconstructed spatial resolution at high and medium SBR compared to PSF+TOF and OSEM+TOF, but only with beta = 150. However, this is at the cost of inferior SNR with Q.Clear150 compared to Q.Clear300/450 and PSF+TOF4/16/PSF+TOF2/17 while CRpeak for the small spheres did not improve considerably. This suggests that Q.Clear300/450 may be advantageous for the 3-ring detector configuration because the tradeoff between CR and SNR with Q.Clear300/450 was superior to PSF+TOF4/16, OSEM+TOF4/16, and OSEM+TOF2/17. However, it requires validation by systematic evaluation in patients at different activity and acquisition protocols.

Off-axis electron holography in an aberration-corrected transmission electron microscope

2009 ◽  
Vol 367 (1903) ◽  
pp. 3773-3793 ◽  
Author(s):  
Hannes Lichte ◽  
Dorin Geiger ◽  
Martin Linck
Keyword(s):  
Electron Microscope ◽  
Transmission Electron Microscope ◽  
Point Spread Function ◽  
Signal To Noise Ratio ◽  
Electron Holography ◽  
Signal To Noise ◽  
Point Spread ◽  
Transmission Electron ◽  
Spread Function ◽  
Noise Ratio

Electron holography allows the reconstruction of the complete electron wave, and hence offers the possibility of correcting aberrations. In fact, this was shown by means of the uncorrected CM30 Special Tübingen transmission electron microscope (TEM), revealing, after numerical aberration correction, a resolution of approximately 0.1 nm, both in amplitude and phase. However, it turned out that the results suffer from a comparably poor signal-to-noise ratio. The reason is that the limited coherent electron current, given by gun brightness, has to illuminate a width of at least four times the point-spread function given by the aberrations. As, using the hardware corrector, the point-spread function shrinks considerably, the current density increases and the signal-to-noise ratio improves correspondingly. Furthermore, the phase shift at the atomic dimensions found in the image plane also increases because the collection efficiency of the optics increases with resolution. In total, the signals of atomically fine structures are better defined for quantitative evaluation. In fact, the results achieved by electron holography in a Tecnai F20 Cs-corr TEM confirm this.

scholarly journals Mitigating the effects of undersampling in weak lensing shear estimation with metacalibration

2021 ◽  
Vol 502 (3) ◽  
pp. 4048-4063
Author(s):  
Arun Kannawadi ◽  
Erik Rosenberg ◽  
Henk Hoekstra
Keyword(s):  
Point Spread Function ◽  
Gravitational Lensing ◽  
State Of The Art ◽  
Weak Lensing ◽  
Weight Functions ◽  
High Signal ◽  
Signal To Noise ◽  
Space Telescope ◽  
Point Spread ◽  
Spread Function

ABSTRACT metacalibration is a state-of-the-art technique for measuring weak gravitational lensing shear from well-sampled galaxy images. We investigate the accuracy of shear measured with metacalibration from fitting elliptical Gaussians to undersampled galaxy images. In this case, metacalibration introduces aliasing effects leading to an ensemble multiplicative shear bias about 0.01 for Euclid  and even larger for the Roman Space Telescope, well exceeding the missions’ requirements. We find that this aliasing bias can be mitigated by computing shapes from weighted moments with wider Gaussians as weight functions, thereby trading bias for a slight increase in variance of the measurements. We show that this approach is robust to the point-spread function in consideration and meets the stringent requirements of Euclid for galaxies with moderate to high signal-to-noise ratios. We therefore advocate metacalibration as a viable shear measurement option for weak lensing from upcoming space missions.

Dose Limited Resolution

1998 ◽  
Vol 4 (S2) ◽  
pp. 802-803
Author(s):  
D. Van Dyck ◽  
A.J. den Dekker ◽  
J. Sijbers ◽  
E. Bettens
Keyword(s):  
Point Spread Function ◽  
Communication Channel ◽  
Unit Area ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Imaging Device ◽  
Point Spread ◽  
Spread Function ◽  
Minimal Contrast ◽  
Definition Of

1. IntroductionThe definition of resolution as introduced by Lord Rayleigh [1] is related to the width of the point spread function of the imaging device. In this definition, noise has not been taken into account. Another definition of resolution has been introduced by Rose [2] in the field of radar and TV. Here the resolution is defined in terms of the dose (D) (i.e. number of imaging particles per unit area) and the signal to noise ratio SNR (i.e. the minimal contrast) A third definition of resolution is based on the idea that the microscope is a communication channel between the object and the observer. The resolution can then be rephrased as the amount of information that is transmitted by the channel in the sense as defined by Shannon [3] as a number of bits per unit area. This definition however does not describe how this information can be deduced and what its precision is.

Wiener Filter Based on the Image to Blur

2012 ◽  
Vol 591-593 ◽  
pp. 1567-1570
Author(s):  
Chao Da Chen ◽  
Si Qing Zhang ◽  
Chui Xin Chen
Keyword(s):  
Image Quality ◽  
Image Restoration ◽  
Point Spread Function ◽  
Signal To Noise Ratio ◽  
Wiener Filter ◽  
Point Spread ◽  
Spread Function ◽  
Degraded Image ◽  
Ill Posed ◽  
Fuzzy Image

Image restoration, refers to the removal or loss in the process of getting digital image degradation of the image quality, image restoration technology is the key to meet the requirements of the point spread function, degradation model is an ill-posed integral equations, in the frequency domain, when H ( U, V ) less or equal to zero, the noise will be amplified, the degraded image and interference in H ( U, V ) value of the spectrum will be small to restore the image influence. In view of the point spread function put forward Wiener filtering algorithm, the noise lead to ill-posed integral with specified signal-to-noise ratio to reduce image restoration effects, through the IPT toolbox for fuzzy image restoration, image quality to achieve the anticipated effect.

scholarly journals A Contribution to Sonograph Image Quality Estimation Using Point Spread Function

2004 ◽  
Vol 47 (4) ◽  
pp. 293-295
Author(s):  
Ladislav Doležal ◽  
Jan Hálek
Keyword(s):  
Image Quality ◽  
Point Spread Function ◽  
Signal To Noise Ratio ◽  
Region Of Interest ◽  
Measuring System ◽  
Point Spread ◽  
Scanning Area ◽  
Spread Function ◽  
Gain Compensation

In medical sonography, sonograph image quality is an essential aspect for the safety of both patient and doctor. Its evaluation therefore requires an accurate and objective method for measurement. In this regard, a number of methods are in current use. Most of these are based on tissue mimicking phantom imaging. In contrast, we have used another principle based on Point Spread Function (PSF) analysis which is a product of the measuring system we have developed. In this case, the measured sonograph scans a small metallic ball target that moves in a water bath on a specified trajectory. The Region Of Interest (ROI) of the sonogram containing the ball target picture is digitised and the amplitude of the pixels analysed. The result is the PSF from which we calculate the lateral resolution (LR). For this purpose, we use our own original software. Using this method, we have to date been able to plot LR characteristics over the scanning plane. The method allows us to differentiate separate scanning lines and even multiple focal areas for dynamic focussing systems. It can detect malfunctions in dynamic focussing, size of aperture, time gain compensation function and/or transducer element failure. The procedure itself is not as easy or as fast to use as tissue mimicking phantoms or 3D signal to noise ratio evaluation, but it provides accurate and objective numeric parameters corresponding to the quality of image at any specified point over the whole scanning area. It is also a very powerful tool when used in combination with the other methods mentioned above.

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