scholarly journals A Sub-pixel Centroid Algorithm for Star Image Based on Gaussian Distribution

2011 ◽  
Vol 53 (182) ◽  
pp. 307-310
Author(s):  
Jing SUN ◽  
Guangrui LI ◽  
Desheng WEN ◽  
Bin XUE ◽  
Shaodong YANG
Keyword(s):  
Gaussian Distribution ◽  
Star Image ◽  
Centroid Algorithm

A Recovery Algorithm of Star Energy Distribution for Star Sensor under High Dynamic Condition

2013 ◽  
Vol 815 ◽  
pp. 187-192
Author(s):  
Cun Lian Wang ◽  
Bao Hua Li ◽  
Chang Hong Wang ◽  
Yun Chen
Keyword(s):  
Energy Distribution ◽  
Gaussian Distribution ◽  
Dynamic Condition ◽  
Star Sensor ◽  
Image Distribution ◽  
Recovery Algorithm ◽  
Star Image ◽  
High Dynamic ◽  
Centroiding Algorithm ◽  
The Ideal

Under the condition of high dynamic, there is a pixel shift phenomenon which is called smear in the star image sampled by star sensor. The recovery algorithm of star energy distributing for star sensor is presented in the paper. The quaternion of next frame is calculated with the previous continuous quaternion. All the ideal star coordinates of star image in the FOV is calculated with the quaternion of next frame. Then the angle between the two previous continuous axis directions is calculated with the previous continuous axis directions calculated with the previous continuous quaternion. The radius of threshold scan window of star image is calculated according to the angle. Finally, within the star image radius of the threshold scan window, shift the original star image to make the shifted star energy distribution continuous. So the star image distribution subjects to 2-D Gaussian distribution, and the star coordinates is obtain with centroiding algorithm. A star sensor featuring a recovery algorithm of star energy distributing for star sensors proposed in this paper was for demonstration at night sky experiment.

High-Accuracy Star Sensor Centroid Algorithm Based on Star Image Resampling

2019 ◽  
Vol 39 (7) ◽  
pp. 0712003
Author(s):  
曹阳 Yang Cao ◽  
李保权 Baoquan Li ◽  
李海涛 Haitao Li ◽  
桑鹏 Peng Sang
Keyword(s):  
High Accuracy ◽  
Star Sensor ◽  
Star Image ◽  
Centroid Algorithm

Structure images of Si, Ge and Mos2 crystals and some application to radiation damage studies

1978 ◽  
Vol 36 (1) ◽  
pp. 292-293 ◽  
Author(s):  
K. Izui ◽  
T. Nishida ◽  
S. Furuno ◽  
H. Otsu ◽  
S. Kuwabara
Keyword(s):  
Radiation Damage ◽  
Exposure Time ◽  
Gaussian Distribution ◽  
Intensity Distribution ◽  
Chromatic Aberration ◽  
Magnetic Lens

Recently we have observed the structure images of silicon in the (110), (111) and (100) projection respectively, and then examined the optimum defocus and thickness ranges for the formation of such images on the basis of calculations of image contrasts using the n-slice theory. The present paper reports the effects of a chromatic aberration and a slight misorientation on the images, and also presents some applications of structure images of Si, Ge and MoS2 to the radiation damage studies.(1) Effect of a chromatic aberration and slight misorientation: There is an inevitable fluctuation in the amount of defocus due to a chromatic aberration originating from the fluctuations both in the energies of electrons and in the magnetic lens current. The actual image is a results of superposition of those fluctuated images during the exposure time. Assuming the Gaussian distribution for defocus, Δf around the optimum defocus value Δf0, the intensity distribution, I(x,y) in the image formed by this fluctuation is given by

Limit tolerances for sums of measurement errors

2018 ◽  
Vol 934 (4) ◽  
pp. 59-62
Author(s):  
V.I. Salnikov
Keyword(s):  
Normal Distribution ◽  
Mean Square Error ◽  
Gaussian Distribution ◽  
Measurement Errors ◽  
Theory And Practice ◽  
Mean Square ◽  
The Mean ◽  
Limiting Values ◽  
Limiting Value

The question of calculating the limiting values of residuals in geodesic constructions is considered in the case when the limiting value for measurement errors is assumed equal to 3m, ie ∆рred = 3m, where m is the mean square error of the measurement. Larger errors are rejected. At present, the limiting value for the residual is calculated by the formula 3m√n, where n is the number of measurements. The article draws attention to two contradictions between theory and practice arising from the use of this formula. First, the formula is derived from the classical law of the normal Gaussian distribution, and it is applied to the truncated law of the normal distribution. And, secondly, as shown in [1], when ∆рred = 2m, the sums of errors naturally take the value equal to ?pred, after which the number of errors in the sum starts anew. This article establishes its validity for ∆рred = 3m. A table of comparative values of the tolerances valid and recommended for more stringent ones is given. The article gives a graph of applied and recommended tolerances for ∆рred = 3m.

Fringe order identification in optical fibre white-light interferometry using centroid algorithm method

1992 ◽  
Vol 28 (6) ◽  
pp. 553 ◽  
Author(s):  
S. Chen ◽  
A.W. Palmer ◽  
K.T.V. Grattan ◽  
B.T. Meggitt
Keyword(s):  
Optical Fibre ◽  
White Light ◽  
White Light Interferometry ◽  
Fringe Order ◽  
Centroid Algorithm

scholarly journals Separate Universe calibration of the dependence of halo bias on cosmic web anisotropy

2020 ◽  
Vol 499 (3) ◽  
pp. 4418-4431 ◽  
Author(s):  
Sujatha Ramakrishnan ◽  
Aseem Paranjape
Keyword(s):  
Dark Matter ◽  
High Precision ◽  
Gaussian Distribution ◽  
Initial Perturbation ◽  
Analytical Framework ◽  
Web Environment ◽  
Wide Range ◽  
Galaxy Assembly ◽  
Very High ◽  
Good Agreement

ABSTRACT We use the Separate Universe technique to calibrate the dependence of linear and quadratic halo bias b1 and b2 on the local cosmic web environment of dark matter haloes. We do this by measuring the response of halo abundances at fixed mass and cosmic web tidal anisotropy α to an infinite wavelength initial perturbation. We augment our measurements with an analytical framework developed in earlier work that exploits the near-lognormal shape of the distribution of α and results in very high precision calibrations. We present convenient fitting functions for the dependence of b1 and b2 on α over a wide range of halo mass for redshifts 0 ≤ z ≤ 1. Our calibration of b2(α) is the first demonstration to date of the dependence of non-linear bias on the local web environment. Motivated by previous results that showed that α is the primary indicator of halo assembly bias for a number of halo properties beyond halo mass, we then extend our analytical framework to accommodate the dependence of b1 and b2 on any such secondary property that has, or can be monotonically transformed to have, a Gaussian distribution. We demonstrate this technique for the specific case of halo concentration, finding good agreement with previous results. Our calibrations will be useful for a variety of halo model analyses focusing on galaxy assembly bias, as well as analytical forecasts of the potential for using α as a segregating variable in multitracer analyses.

Sign in / Sign up

Export Citation Format

Share Document