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Journal Club Bozeman 6 November 2001

Journal Club Bozeman 6 November 2001. Population: 636 800 Ladies: 337 200 Gents: 299 600. SXT image formation process. BLUR. i true brightness distribution. p point spread function. c convolution of i and p.

larissa-carpenter
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Journal Club Bozeman 6 November 2001

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  1. Journal Club Bozeman 6 November 2001

  2. Population: 636 800 Ladies: 337 200 Gents: 299 600

  3. SXT image formation process BLUR i true brightness distribution p point spread function c convolution of i and p

  4. SXT image formation process (continued) NOISE c convolution of i and p d blurred & noisy data d = c + noise

  5. SXT image formation process (continued) cross sections i d What we know is d. For i, p, c we can only look for approximations.

  6. Deconvolution To find i from d and p or To find p from d and i i – approximation of image (true brightness distribution) p – approximation of point spread function d – data (blurred & noisy)

  7. Find new estimate of i from d and p Find new estimate of I from D and P Find new estimate of p from d and i Find new estimate of P from D and I Blind Deconvolution i – image (true brightness distribution) p – point spread function d – data (blurred & noisy) I, P, D – Fourier transforms of i, d, p D = product of P and I + noise in fouries space d = convolution of p and i + noise

  8. PURPOSE To determine the approximation of the core part of the SXT PSF from flare observations collected in-flight, in thick aluminum filter. STEPS TO ACHIVE • Select appropriate SXT data set • Find first approximation of the PSF by Steepest Descent Method • Improve it by Blind Deconvolution

  9. SXT Point Spread Function Model Two regions spiky core extended wings

  10. Wing part of SXT PSF Large flare image taken on 27 Feb 1992 at 09:51. Half resolution SXT data.

  11. Core part of SXT PSF Ground calibration images in Al-K line (White Sands 1991)

  12. Elliptical distortion of SXT PSF (strong in CCD corners) Contours at 0.1, 0.2, 0.4 and 0.8 of maximum value.

  13. Where SXT Data have been taken during the year 2000 To the left,a coverage map of the CCD detector surface by full resolution SXT frames. Gray intensity says how many times a given pixel was captured within a full resolution frame during year 2000. To the right a shaded surface for the coverage map (Log10 scale).

  14. Selection of SXT data • Compact • CCD Temperature below –20o C • DC below 50 DN • Taken outside SAA • Global maximum present • at least 7 pixels away from image boundaries • Not saturated but maximum value above 1000 DN Compact source images selected in thick aluminium filter data (small dots) and WSMR calibration beam positions on CCD surface (crosses).

  15. Steepest Descent Method PSF is the sharpest object of photon origins that can be formed on SXT CCD Find sequence of images placed nearly at the same location on CCD

  16. Steepest Descent Method (continued) image sequence sub-array sequence normalized Normalize image signal in certain sub-arrays centered at the peak. (here 15x15 square sub-arrays)

  17. Steepest Descent Method (continued) sub-array sequence normalized Construct PSF approximation by taking at each pixel minimal signal value possible to find in the whole normalized sequence at respective pixel position.

  18. Steepest Descent Method – comparison with WSMR calibration data Steepest descents Calibration x cross-section y cross-section

  19. Initial data preparation for Blind Deconvolution Select the most compact flare image found in the neighborhood of a given CCD pixel Construct initial guess for PSF by steepest descent method and put it into an image size array

  20. Fourier transforms PSF Im Re SXT flare mage Re Im

  21. ALGORITHM Fourier transform of Initial approximation for PSF Find new estimate of I2 from D and P2 I2 P2 Inverse Fourier Transform Fourier Transform i2 p2 • Impose image constraints • positivity • conservation of total counts • Impose PSF constraints • positivity • normalization p1 i1 Inverse Fourier Transform Fourier Transform P1 I1 Find new estimate of P1 from D and I1 Fourier domain constraint average I1 and I2

  22. RESULTS Input PSF steepest descents Restored PSF blind deconvolution

  23. RESULTS Input SXT data Restored SXT data

  24. RESULTS Input SXT data Restored SXT data

  25. Conclusions • Blind Deconvolution of the selected SXT flare data can give us: • Sharper PSF core profile • than can be directly obtained from data by steepest descent method • Peak sharpening in SXT data • Peak separation in data • Works fast

  26. What we have done • Working IDL code • Good SXT Flare data selected • First deconvolutions of SXT data performed

  27. Will do next • Improve the code • Fit deconvolved PSFs by Moffat functions • Prepare web site about the project (partly done) • to make the code accessible for other users. • Add the code to Solar Soft package

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