scholarly journals Simulation and Analysis of Spectral Response Function and Bandwidth of Spectrometer

2016 ◽  
Vol 2016 ◽  
pp. 1-8
Author(s):  
Zhenyu Gao ◽  
Ruidong Jia ◽  
Hao Zhang ◽  
Zhiwei Xia ◽  
Wei Fang
Keyword(s):  
Response Function ◽  
Spectral Response ◽  
Simulation Method ◽  
Design Phase ◽  
Optical Aberrations ◽  
Simulation Procedure ◽  
Point Spread ◽  
Spread Function ◽  
Prism Monochromator ◽  
Tracing Method

A simulation method for acquiring spectrometer’s Spectral Response Function (SRF) based on Huygens Point Spread Function (PSF) is suggested. Taking into account the effects of optical aberrations and diffraction, the method can obtain the fine SRF curve and corresponding spectral bandwidth at any nominal wavelength as early as in the design phase. A prism monochromator is proposed for illustrating the simulation procedure. For comparison, a geometrical ray-tracing method is also provided, with bandwidth deviations varying from 5% at 250 nm to 25% at 2400 nm. Further comparison with reported experiments shows that the areas of the SRF profiles agree to about 1%. However, the weak scattered background light on the level of 10−4 to 10−5 observed by experiment could not be covered by this simulation. This simulation method is a useful tool for forecasting the performance of an underdesigned spectrometer.

scholarly journals Blind Fusion of Hyperspectral Multispectral Images Based on Matrix Factorization

2021 ◽  
Vol 13 (21) ◽  
pp. 4219
Author(s):  
Jian Long ◽  
Yuanxi Peng
Keyword(s):  
Response Function ◽  
Spatial Resolution ◽  
Point Spread Function ◽  
Spectral Response ◽  
Estimation Method ◽  
Hyperspectral Images ◽  
Fusion Method ◽  
Multispectral Images ◽  
Point Spread ◽  
Spread Function

The fusion of low spatial resolution hyperspectral images and high spatial resolution multispectral images in the same scenario is important for the super-resolution of hyperspectral images. The spectral response function (SRF) and the point spread function (PSF) are two crucial prior pieces of information in fusion, and most of the current algorithms need to provide these two preliminary pieces of information in advance, even for semi-blind fusion algorithms at least the SRF. This causes limitations in the application of fusion algorithms. This paper aims to solve the dependence of the fusion method on the point spread function and proposes a method to estimate the spectral response function from the images involved in the fusion to achieve blind fusion. We conducted experiments on simulated datasets Pavia University, CAVE, and the remote sensing images acquired by two spectral cameras, Sentinel 2 and Hyperion. The experimental results show that our proposed SRF estimation method can improve the PSNR value by 5 dB on average compared with other state-of-the-art SRF estimation results. The proposed blind fusion method can improve the PSNR value of fusion results by 3–15 dB compared with other blind fusion methods.

Simulation of Spectral Response Function based on Huygens Point Spread Function

2015 ◽  
Vol 44 (10) ◽  
pp. 1030002
Author(s):  
高震宇 GAO Zhen-yu ◽  
方伟 FANG Wei ◽  
宋宝奇 SONG Bao-qi ◽  
姜明 JIANG Ming ◽  
王玉鹏 WANG Yu-peng
Keyword(s):  
Response Function ◽  
Point Spread Function ◽  
Spectral Response ◽  
Point Spread ◽  
Spread Function

scholarly journals Photon count estimation in single-molecule localization microscopy

2018 ◽  
Author(s):  
Rasmus Ø. Thorsen ◽  
Christiaan N. Hulleman ◽  
Mathias Hammer ◽  
David Grünwald ◽  
Sjoerd Stallinga ◽  
...  
Keyword(s):  
Single Molecule ◽  
Axial Position ◽  
Optical Aberrations ◽  
Intensity Estimation ◽  
Localization Microscopy ◽  
Photon Count ◽  
Point Spread ◽  
Spread Function ◽  
Gaussian Point ◽  
Single Molecule Localization Microscopy

Recently, Franke, Sauer and van de Linde1 introduced a way to estimate the axial position of single-molecules (TRABI). To this end, they compared the detected photon count from a temporal radial-aperture-based intensity estimation to the estimated count from Gaussian point-spread function (PSF) fitting to the data. Empirically they found this photometric ratio to be around 0.7-0.8 close to focus and decreasing away from it. Here, we explain this reported but unexplained discrepancy and furthermore show that the photometric ratio as indicator for axial position is susceptible even to typical optical aberrations.

scholarly journals The Point Spread Function Variations inside Wide-field Astonomical Images

10.14311/1696 ◽  
2013 ◽  
Vol 53 (1) ◽  
Author(s):  
Elena Anisimova ◽  
Jan Bednář ◽  
Petr Páta
Keyword(s):  
Point Spread Function ◽  
Imaging System ◽  
Wide Field ◽  
Optical Aberrations ◽  
Atmospheric Scattering ◽  
Function Fitting ◽  
Astronomical Imaging ◽  
Point Spread ◽  
Spread Function ◽  
Field Imaging

The Point Spread Function (PSF) of the astronomical imaging system is usually approximated by a Gaussian or Moffat function. For simplification, the astronomical imaging system is considered to be time and space invariant. This means that invariable PSF within an exposed image is assumed. If real wide-field imaging systems are considered, this presumption is not fulfilled. In real systems, stronger optical aberrations are expected (especially coma) at greater distances from the center of the captured image. This impacts the efficiency of stellar astrometry and photometry algorithms, so it is necessary to know the PSF variation. In this paper, we perform the first step toward assigning PSF changes: we study the dependence of the Moffat function fitting parameters (FWHM and the atmospheric scattering coefficient ) on the position of a stellar object.

scholarly journals LAUE LENSES FOR HARD X–/SOFT γ–RAYS: NEW PROTOTYPE RESULTS

2013 ◽  
Vol 23 ◽  
pp. 11-15
Author(s):  
V. LICCARDO ◽  
E. VIRGILLI ◽  
F. FRONTERA ◽  
V. VALSAN ◽  
V. CARASSITI ◽  
...  
Keyword(s):  
Point Spread Function ◽  
San Diego ◽  
Spectral Response ◽  
Laue Lens ◽  
Point Spread ◽  
Spread Function ◽  
Γ Rays ◽  
Physics Department

The results obtained with the new Laue lens prototype built in the LARIX facility in the Physics Department of University of Ferrara will be present. Thanks to the methods adopted for improving the first prototype (SPIE conference in San Diego, Ferrari et al. 2009) here we present the results of the new prototype with improved performances in terms of point spread function (PSF) and spectral response.

Imaging through Scattering Media with a Learning Based Prior

2020 ◽  
Vol 2020 (14) ◽  
pp. 306-1-306-6
Author(s):  
Florian Schiffers ◽  
Lionel Fiske ◽  
Pablo Ruiz ◽  
Aggelos K. Katsaggelos ◽  
Oliver Cossairt
Keyword(s):  
Optimization Problem ◽  
Autonomous Driving ◽  
Scattering Media ◽  
Photon Scattering ◽  
Point Spread ◽  
Spread Function ◽  
Radiative Transport Equation ◽  
Spatio Temporal ◽  
Transient Imaging

Imaging through scattering media finds applications in diverse fields from biomedicine to autonomous driving. However, interpreting the resulting images is difficult due to blur caused by the scattering of photons within the medium. Transient information, captured with fast temporal sensors, can be used to significantly improve the quality of images acquired in scattering conditions. Photon scattering, within a highly scattering media, is well modeled by the diffusion approximation of the Radiative Transport Equation (RTE). Its solution is easily derived which can be interpreted as a Spatio-Temporal Point Spread Function (STPSF). In this paper, we first discuss the properties of the ST-PSF and subsequently use this knowledge to simulate transient imaging through highly scattering media. We then propose a framework to invert the forward model, which assumes Poisson noise, to recover a noise-free, unblurred image by solving an optimization problem.

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