A Robust Star Acquisition Algorithm Based on Facet Model

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.532-533.1747 ◽

2012 ◽

Vol 532-533 ◽

pp. 1747-1751

Author(s):

Guang Rui Li

Keyword(s):

Cluster Formation ◽

Minimum Threshold ◽

Vector Method ◽

Point Spread ◽

Spread Function ◽

Great Progress ◽

Speed Up ◽

Intense Noise ◽

Performance Evaluation Index ◽

Facet Model

An efficient and robust star acquisition algorithm based on facet fitting is presented to improve the performance of star sensors. The location of star central pixels can be determined by searching extremum intensity pixels among the point spread function (PSF) of stars, which is well fitted by the cubic facet model. According to extremum theory, the second derivative operators are pre-calculated and the searching process can be completed using convolution operations thrice. Simultaneously, cluster formation is also a time consuming routine, which is accomplished using specific maximum and minimum threshold to speed up it. A variety of experiments are carried out to validate the performance of proposed algorithm, moreover, the performance evaluation index M is presented. The results clearly show that the proposed algorithm makes a great progress than the vector method in time expense and accuracy under intense noise conditions.

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Fast signal analysis in Rotating-Polarization CARS microscopy

Optical Data Processing and Storage ◽

10.2478/odps-2014-0001 ◽

2014 ◽

Vol 1 (1) ◽

Cited By ~ 2

Author(s):

Giuseppe de Vito ◽

Vincenzo Piazza

Keyword(s):

Raman Spectroscopy ◽

Point Spread Function ◽

Signal Analysis ◽

Point Spread ◽

Novel Approach ◽

Spread Function ◽

Cars Microscopy ◽

Speed Up ◽

Orientation Anisotropy ◽

Anti Stokes

AbstractRotating Polarization Coherent Anti-Stokes Raman Spectroscopy (RP-CARS) is a novel approach to CARS microscopy that takes advantage of polarizationdependent selection rules in order to gain information about molecule orientation anisotropy and direction within the optical point spread function. However, in the original implementation of this technique, the lockin amplifier-based acquisition was quite time demanding. Here we present a new software-based approach that permits a great speed-up in the RP-CARS images acquisition process.

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Computing light pollution indicators for environmental assessment

10.22541/au.161772596.62032718/v1 ◽

2021 ◽

Author(s):

Fabio Falchi ◽

Salvador Bará

Keyword(s):

Light Pollution ◽

Light Sources ◽

Point Spread ◽

Main Indicator ◽

Rotationally Symmetric ◽

Spread Function ◽

Speed Up ◽

Sky Brightness ◽

Sky Radiance ◽

Spatially Variant

Light pollution modelling and monitoring has traditionally used zenith sky brightness as its main indicator. Several other indicators (e.g. average sky radiance, horizontal irradiance, average sky radiance at given interval of zenith distances) may be more useful, both for general and for specific purposes of ecology studies, night sky and environmental monitoring. These indicators can be calculated after the whole sky radiance is known with sufficient angular detail. This means, for each site, to integrate the contribution in each direction of the sky of each light source in the radius of hundreds of km. This approach is extremely high time consuming if the mapping is desired for a large territory. Here we present a way to obtain maps of large territories for a large subset of useful indicators, bypassing the need to calculate first the radiance map of the whole sky in each site to obtain from it the desired indicator in that site. For each indicator, a point spread function (PSF) is calculated from the whole sky radiance maps generated by a single source at sufficiently dense number of distances from the observing site. If the PSF is transversally shift-invariant, i.e. if it depends only on the relative position of source and observer, then we can further speed up the map calculation via the use of fast Fourier-transform (FFT). We present here examples of maps for different indicators. Precise results can be calculated for any single site, taking into account the site and light sources altitudes, by means of specific inhomogeneous (spatially-variant) and anisotropic (non rotationally symmetric) PSFs.

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J1 The point-spread function

To Measure the Sky ◽

10.1017/cbo9781316424117.022 ◽

2016 ◽

pp. 447-447 ◽

Cited By ~ 1

Keyword(s):

Point Spread Function ◽

Point Spread ◽

Spread Function

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Automatisiertes Verfahren zur Prüfung von Qualitätsseigenschaften von Ultraschalldiagnostikgeräten vor Ort in Kliniken und Praxen mit einem 3D Phantom und Point-Spread-Function (PSF) Messung

Ultraschall in der Medizin - European Journal of Ultrasound ◽

10.1055/s-2004-834017 ◽

2004 ◽

Vol 25 (S 1) ◽

Author(s):

HJ Schultz ◽

J Satrapa ◽

G Doblhoff

Keyword(s):

Point Spread Function ◽

Point Spread ◽

Spread Function

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Imaging through Scattering Media with a Learning Based Prior

Electronic Imaging ◽

10.2352/issn.2470-1173.2020.14.coimg-306 ◽

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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