Summary Of Se D Da Ra
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Matsuda Kazuki 2009/9/5
Transcript of Summary Of Se D Da Ra
Matsuda Kazuki
2009/9/5
Written by Yoshifumi Sudo, Naoshi Baba, Noriaki Miura, Satoru Ueno,
and Reizaburo Kitai
Shift and Add Operation is very useful to get high-resolution image from atmospherically degraded data.
The self-deconvolving data reconstruction algorithm (SeDDaRA) is to augment high-speed-frequency components in solar speckle images.
Self-deconvolving image -> SAA -> get High-resolution image.
Adaptive Optics mitigate atmospheric turbulence in real time.
On the other hand, there are various a posteriori methods.Stellar speckle imaging – SAA is simplest in
this category.Can applied to solar image.
Key point of SAA method is shifting image on point position of the instantaneous PSF.But it is difficult to apply to extended
object.
Some alternative method is required to find shifting width.Co-relation. On Granulation. From reference
frame. But, in this way, quality of SAA result is
determined by selection of reference frame.
It is desirable that human’s selection independent results (& method).
1st – self-deconvolving. 2nd – SAA with reference frame.
Reference frame is determined from RMSC.
The i-th specle image gi(x,y) is writen
The Fourier Transform is
Deconvolution by using a“pseudo Wiener filter Di(u,v)”
H is low frequency of G-N
SAA Reference frame is determined by RMSC
A Frame which had Highest RMSC is reference frame.
Fix reference frame and SAA method. One more SAA method under the
condition that reference frame is 1st result.
Finish.
