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Solar Feature Catalogues in EGSO

Solar Feature Catalogues in EGSO. V V Zharkova, J. Aboudarham, S Zharkov , S S Ipson, A K Benkhalil and N.Fuller. Work Package 5 http://www.cyber.brad.ac.uk/egso/. I. The Image standardisation techniques II. The feature recognition techniques for

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Solar Feature Catalogues in EGSO

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  1. Solar Feature Catalogues in EGSO V V Zharkova, J. Aboudarham, S Zharkov, S S Ipson, A K Benkhalil and N.Fuller

  2. Work Package 5 http://www.cyber.brad.ac.uk/egso/ • I. The Image standardisation techniques • II. The feature recognition techniques for sunspots, ARs, filaments and MNL • III. Verification of the features • IV. Feature Catalogue design • V. Use cases – papers @ COSPAR etc KES 2004, 20-24 September 2004, Wellington, NZ

  3. I. Why the pre-processing techniques? Difficulties with images: • Artefacts and defects in data (strips, lines, intensity) • Errors in FITS header information • Image shape (ellipse), disk centre • Weather transparency (clouds) and different thickness of atmosphere • Centre-to-limb darkening The techniques developed: Zharkova et al.,Sol. Phys, 214 (2003)) • Fitting ellipse to solar limb • Standardising image shape and size • Removing radial limb darkening • Non-radial intensity corrections (under investigation) KES 2004, 20-24 September 2004, Wellington, NZ

  4. III. Feature Recognition Techniques • Sunspot detection (Edge detection, Morphological operators, thresholding) • Filament detection(fast morphological methods, ANN and region growing) • Active region detection(local quarter thresholding (LQT), region growing (RG), Histogram Equalisation (HE), morphological operations (MO)) • Magnetic neutral lines (dual distance transform) • Generation of synoptic maps for every feature KES 2004, 20-24 September 2004, Wellington, NZ

  5. 2002-07-24T09:35:30.257Z KES 2004, 20-24 September 2004, Wellington, NZ

  6. Sunspot Detection detected edges & low int regions => <= original image <ROI result > KES 2004, 20-24 September 2004, Wellington, NZ

  7. Sunspot detection on SOHO/MDI WL images the original imageDetected edges  c)The found regions (dilated) d) The final detection results superimposed e) The extract from d) KES 2004, 20-24 September 2004, Wellington, NZ

  8. KES 2004, 20-24 September 2004, Wellington, NZ

  9. 22(7 false) 12 (3 false) 9 15 11 (3 false) 08/04/02 8 (1 false) 8 21/04/02 11 (3 false) 20 (5 false) 17 (2 false) 15(1 false) 14 11 13 (1 false) 19(6 false) 16 12 19 (3 false ) 18 16 16 16 15/04/02 10 12 (2 false) 14 (3 false) 14 (3 false) 01/04/02 16 16 16 17/04/02 11 12 (1 false) 16/04/02 15 13 (1 false) 12 (1 false) 13 17(1 false) 14 10 (1 false) 15 (1 false) 20 (6 false) 14 17 19(2 false) 15 12 (1 false) 11 21 18 14 24 (9 false) 11 (1 false) 34 14 (1 false) 13(3 false) 11 15 (5 false) 15 (3 false) 12 11 #Sunspots Ideally 12 21 19 15 21 (3 false) 02/04/02 14/04/02 10 Date Visible # Detected 20 15(1 false) 19 19 03/04/02 14 07/04/02 15(1 false) 15(1 false) 19 10/04/02 13 (1 false) 20 (2 false) 04/04/02 13(3 false) 13 (3 false) 9 11 15 (3 false) 12 12 12 13 11/04/02 9 9 12/04/02 18 20 13 10 16(2 false) 14 14 20/04/02 18/04/02 9 10 15(1 false) 22/04/02 12 13 (1 false) 11 10 22 (1 false) 26 (5 false) 27 (6 false) 13 19/04/02 10 11 16 18(1 false) 19(2 false) 19(2 false) 06/04/02 10 05/04/02 10 11 21 (3 false) 12 9 14 20 10 18(4 false) #Detected mr=0 (All candidates) #Detected mr=3 deviation >15, x<2.1 #Detected mr=1 Dev > 5, x < 3.5 12 18 (6 false) 17 17 17 09/04/02 13(1 false) 12 12 16 13 (1 false) 18/04/02 17 17 Sunspot Detection in Ca k1 line Meudon images compared with the Meudon manual detection results KES 2004, 20-24 September 2004, Wellington, NZ

  10. S/s area magnetic flux (abs&excess) versus areas: year 2001 KES 2004, 20-24 September 2004, Wellington, NZ

  11. b c a b c a d e d e AR Detection Technique H-alpha image (Meudon Observatory) SOHO/EIT image ( Fe XII 195 A) KES 2004, 20-24 September 2004, Wellington, NZ

  12. Comparison with BBSO Observatory (01/04/02) Hα KES 2004, 20-24 September 2004, Wellington, NZ

  13. FAR – False Acceptance Rate FRR – False Rejection Rate An average FAR of 1.8per day in April and only 1 in July. The FRR was very low at about 0.2 in both months April and July, with only 5 days in each month when we failed to detect a region detected by NOAA

  14. Fe XII, 195 Å Corona 10, 000 Km Ca II K3 Middle Chromosphere 750-1800 Km Hα Low Chromosphere 250-750 Km Fe XII 195Å Hα Ca IIK3 Active Region 3D KES 2004, 20-24 September 2004, Wellington, NZ

  15. Filament detection The method used to detect filaments is based on region growing. First the contrast is enhanced and the intensity variations over the image are reduced. Then a first threshold is computed to find the seed points. Finally the pixels are merged to the filament region depending on the following criteria: I(p) ≤ I() - .()  {filaments}, (Collin et al.) where I(p) is the pixel intensity,  a region defined around p, I() and s() the mean and standard deviation of . • Left: original image Right : resulting regions KES 2004, 20-24 September 2004, Wellington, NZ

  16. Comparison with database Left: Pattern recognition results. Right: Meudon “manual” database. KES 2004, 20-24 September 2004, Wellington, NZ

  17. Magnetic inversion lines • To grow isotropically regions and to mark the points where the positive and negative regions make contact. • The specific steps used to construct the inversions lines in this illustration are as follows. • The magnetogram data are first re-binned from a dynamic range of 3000 to a dynamic range of 256 with a zero gauss corresponding to 127.5. • A 3 by 3 median filter is applied to smooth the image by reducing noise fluctuations. The resulting image is then segmented into three types of magnetic regions negative, neutral and positive • The boundaries between the resulting grown regions is then marked using a Sobel edge detection operation. KES 2004, 20-24 September 2004, Wellington, NZ

  18. IV. Solar Feature Catalogue design • Purpose • Provide comprehensive information about: (a) detected features on a date; (b) provide a cropped image library; • Create an option to search data by any feature characteristics • Feature automated detection (1996-2003) • Meudon daily Ca II K3 and H-alpha images • SOHO/MDI white light images and magnetograms • Architecture • [ RDBMS ⇮ web services ⇮ web server ] under Linux • Data accessibility • EGSO broker: via web services [ASCII ⇮ XML VOTable ] • Human user: via a web GUI [http://www.cyber.brad.ac.uk/egso/SFC/SFCtest.html] • Special test features via web GUI • Preset searches for every feature by time, location, size, etc • Use cases for possible searches KES 2004, 20-24 September 2004, Wellington, NZ

  19. Observing table: Observation Observatory Instrument Wavelength Pre-processing table: Ellipse fitting Limb darkening Altered parameters Feature tables: Name Location Size Shape – Chain code, raster scan Mean, min, max intensities/Qs Other characteristics Feature tables structure SFC Database Structure (FP v1.8) KES 2004, 20-24 September 2004, Wellington, NZ

  20. Feature Locations • There are several options available to store pixel locations • Chain Code • File Masks • Raster Scans • The choice of the method depends on an individual feature • Raster Scans (bounding rectangle mask): • reconstructed: pixel values equal to 0 corresponding to quiet sun, 1 to penumbra, 2 to umbra KES 2004, 20-24 September 2004, Wellington, NZ

  21. Input Image Detected AR Chain Code Chain Code start pixel Chain Code constriction example Chain Code Directions

  22. Filament detection • The method used to detect filaments is based on region growing. First the contrast is enhanced and the intensity variations over the image are reduced. • Then a first threshold is computed to find the seed points. • Finally the pixels are merged to the filament region depending on the following criteria: • I(p) ≤ I() - .()  {filaments}, (Collin et al.) where I(p) is the pixel intensity,  a region defined around p, I() and s() the mean and standard deviation of . KES 2004, 20-24 September 2004, Wellington, NZ

  23. Filament shapes Computing parameters like length, centroid, orientation is not straight forward. E.g., calculating the barycentre can give points outside the filament themselves. To get reliable parameters, the concept of a ‘pruned skeleton’ has been used. KES 2004, 20-24 September 2004, Wellington, NZ

  24. The pruned skeleton • The thinning morphological operator is used to get the skeleton of the binary blob (1). The result is the skeleton of the object (2 with dashed line for the boundary). It contains many short branches produced by small irregularities on the boundary of the object. An algorithm, calculating the distances between nodes and branches pixels, has been developed to remove the branches, keeping the full length skeleton (3). The following descriptive parameters can be deduced from the skeleton: • - The length • - The filament centre as the middle of the skeleton, in heliographic coordinates or in pixels • - A curvature index • The chain code of the skeleton can also be computed to get a linear representation of the filament. KES 2004, 20-24 September 2004, Wellington, NZ

  25. Catalogue Overview • Observational Parameters: • Date of observation, resolution, Observatory, Wavelength etc; • Processing Parameters • Pre-Processing Setup & Output: • Ellipse fitting results, new resolution, determined quiet sun intensity etc; • Individual Feature Parameters: • Gravity center (proj & Carrington), area, bounding rectangle, intensity statistics • Sunspots: • diameter, umbral size, number of umbras detected, magnetic information etc • Filaments: • Skeleton length, Skeleton Chain Code, filament orientation, curvature etc • Raster Scans & Chain Codes (bounding rectangle mask): • Sunspot Catalogue (from 1996-05-19 19:08:35 to 2003-12-25 19:51:32) • Filaments & AR (from 1998-01-01 11:35:00 to 2002-12-26 10:25:13) • Filaments:1407 observations processed, 70676 features stored • AR: 1303 observations, 10664 features • Sunspots: 8936 observations, 342307 features • SSW software: • Catalogue Search -> VOTable(XML) -> IDL SSW -> features reconstructed, over plotted KES 2004, 20-24 September 2004, Wellington, NZ

  26. Sunspot Parameters (Observation) KES 2004, 20-24 September 2004, Wellington, NZ

  27. Sunspot Parameters (Feature) KES 2004, 20-24 September 2004, Wellington, NZ

  28. Search page sample KES 2004, 20-24 September 2004, Wellington, NZ

  29. Search results – html, ASCII, XML KES 2004, 20-24 September 2004, Wellington, NZ

  30. V. Current status and Use cases • Currently, we have SFCs for sunspots, active regions and filaments (daily cadence) for 1996-2003. • Will have all the SOHO era coverage (96-05) by March ‘05 • Since October we will offer a limited IDL processing on site (our server) to restore the features of interest • Build an entry into the Unified Observing Catalogues (UOC) of EGSO • Use cases (talks @ COSPAR 2004 Paris): • Suggestions are published in the Use Case document on web • Sunspot magnetic fields in 96-2003, N-S asymmetry – oral E2.2 • Active region 484 magnetic flied tracking – P0339 • Magnetic field in filaments – P0186 • Filament detection with ANN – P0172 (from Thursday) KES 2004, 20-24 September 2004, Wellington, NZ

  31. You all are very welcome to try our product at http://www.cyber.brad.ac.uk/egso/SFC/ Thank You! KES 2004, 20-24 September 2004, Wellington, NZ

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