Image motion as a measure of seeing quality

1987 ◽  
Vol 99 ◽  
pp. 1360 ◽  
Author(s):  
H. M. Martin
Keyword(s):  
Image Motion

Image Sequence Enhancements Based on the Normal Component of Image Motion

1982 ◽  
Author(s):  
Larry S. Davis ◽  
Hu-chen Xie ◽  
Azriel Rosenfeld
Keyword(s):  
Normal Component ◽  
Image Sequence ◽  
Image Motion

Efficient onboard image motion compensation for orbital inclination and eccentricity of geostationary weather satellites

2020 ◽  
Vol 234 (7) ◽  
pp. 1311-1325
Author(s):  
MP Ramachandran ◽  
MK Agarwal ◽  
DA Daniel
Keyword(s):  
Motion Compensation ◽  
Satellite Images ◽  
Software Tool ◽  
Image Motion ◽  
Wind Vector ◽  
Orbital Inclination ◽  
Scanning Mirror ◽  
The Earth ◽  
Detail Image ◽  
Geographical Locations

Image registration is important in geostationary weather satellites. Achieving consistent registration of the images with respect to the geographical locations on the Earth is here of interest. The consistency in the registration between the images is affected whenever the orbital inclination and eccentricity are not zero. The imaging payload has a two-axis scanning mirror to capture the Earth image. The above orbital effects together with scan mirror pointing direction are the factors that cause the misregistration. This paper presents an onboard algorithm that provides the scan compensation angles due to the above factors and achieves consistent registration. The compensation varies every second, which is the time taken for each scan. Hence it is preferred to have computations onboard than to have ground based bulk uplinks for the scan compensation. The paper presents an algorithm that is useful, say, when (i) the onboard computing capabilities are limited, (ii) the navigation accuracies are coarse and (iii) the image resampling is not preferred on the ground and the payload data are directly used for weather applications. The paper also discusses the tests that were carried on the onboard software in order to validate its performance in achieving the consistent registration before launch. This is done by using another independent software tool which is also described in detail. Image motion algorithm was invoked for a couple of days in INSAT 3DR. The atmospheric wind vector deduced directly from the satellite images is given at the end.

Interferential seeing monitor, a seeing monitor for atmospheric turbulence studies: calibration with the differential image motion monitor

2020 ◽  
Vol 500 (2) ◽  
pp. 1884-1888
Author(s):  
Mohammed Sabil ◽  
A Habib ◽  
Z Benkhaldoun
Keyword(s):  
Structure Function ◽  
Atmospheric Turbulence ◽  
Wave Structure ◽  
Image Motion ◽  
Phase Fluctuations ◽  
Amplitude Fluctuations ◽  
Focus Plane ◽  
Cross Calibration ◽  
Double Slit ◽  
Good Agreement

ABSTRACT In this work, we aim to calibrate an interferential seeing monitor (ISM), which is a testing instument used at astronomical sites. Its method is based on the study of the diffraction pattern produced by a Young’s double-slit at the focus plane of a telescope. This method allows us to obtain the wave structure function by taking into account both phase and amplitude fluctuations of the light wavefront. A phase seeing εϕ was assigned to phase fluctuations and an amplitude seeing εχ was assigned to amplitude fluctuations (scintillation phenomenon), which allows us to obtain both phase and amplitude fluctuations. The feasibility of the ISM method was demonstrated by numerical simulations presented in a previous work. In this work, we have conducted a cross-calibration campaign of the ISM with a differential image motion monitor (DIMM) over 16 nights at the Oukaimeden and Atlas Golf Marrakech Observatories. The goal of this campaign was to study the reliability of this new method. In this paper, we present the calibration measurements and a comparison between the seeing measured by the ISM (εϕ, εχ) and that obtained by the DIMM (εdimm). These results show good agreement between the phase- eeing εϕ and εdimm.

Diffraction Images of Edge Objects in the Presence of Linear Image Motion

1974 ◽  
Vol 3 (1-4) ◽  
pp. 46-49
Author(s):  
R. Rattan ◽  
K. Singh
Keyword(s):  
Image Motion

Driving saccade to pursuit using image motion

1995 ◽  
Vol 16 (3) ◽  
pp. 205-228 ◽  
Author(s):  
David W. Murray ◽  
Kevin J. Bradshaw ◽  
Philip F. McLauchlan ◽  
Ian D. Reid ◽  
Paul M. Sharkey
Keyword(s):  
Image Motion

Image Motion and Resolution For Air-To-Air Photography

1965 ◽  
Vol 3 (2) ◽  
Author(s):  
Irving J. Spiro
Keyword(s):  
Image Motion

Compensation of focal plane image motion perturbations with optical correlator in feedback loop

2004 ◽  
Author(s):  
Klaus Janschek ◽  
Valerij Tchernykh ◽  
Serguei Dyblenko ◽  
Gregory Flandin ◽  
Bernd Harnisch
Keyword(s):  
Focal Plane ◽  
Feedback Loop ◽  
Image Motion ◽  
Optical Correlator ◽  
Plane Image
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