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eSDO 1121: Loop Recognition

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Deliverable eSDO-1121: Loop Recognition
M. Smith, E.Auden, L. van Driel-Gesztelyi
28 June 2005

Description

Coronal loops observed by SDO will be identified in AIA images over multiple wavelengths. Three avenues of development will be explored: the primary investigation will concentrate on the use of Rangupathy's [3] 'Improved Curve Tracing' method (based on the work of Steger [2]), which will be independent of magnetic field information. If this method proves unreliable, then the secondary approach will extend automated loop recognition work developed by Lee and Gary[1]. Using an iterative approach, coronal loops identified by the oriented connectivity method will be matched with magnetic field line extrapolations. If this method, too, proves unsatisfactory, then curvelet analysis will be used to identify coronal loops.

Inputs

  • Multi-wavelength flatfield AIA filtergrams
  • HMI vector magnetograms (if OCM with magnetic field line extrapolation approach is used)

Outputs

  • Coronal Loops FITS file
    • Image extension - AIA flatfield image superimposed with recognized loops. Loops will be shown in different colours for specific temperatures.
    • Tabular extension - footprints for each terminus of recognized loops. A footprint will be described in terms of solar coordinates, radius, and temperature.

Test Data

  • TRACE images

Tool Interface

  • commandline: input of AIA images, output of FITS files containing images and statistical data.
    1. AstroGrid CEA web service: this algorithm will be deployed as a CEA service hosted in the UK that users can call the web service to process datasets on the grid.
    2. SolarSoft routine: the C module will be wrapped in IDL and distributed through the MSSL SolarSoft gateway. Users will access to a SolarSoft installation can call the routine from the commandline or GUI to process locally held data.
    3. JSOC module: the C module will be installed in the JSOC pipeline. Users can access the routine through pipeline execution to operate on data local to the JSOC data centre.

Science Use Case

The user wants to identify coronal loops in multiple wavelengths over a given time period. In addition to viewing recognized loops superimposed on a filtergram image, the user also wants a description of each loop's footprint that includes solar coordinates, radius, and temperature.

  1. The user identifies flatfield images from one or more of the 10 AIA channels taken during the specified time period.
  2. The user inputs the flatfield AIA images to the automated loop recognition algorithm. (Currently there are no user-specified variables to describe for the loop recognition algorithm to be distributed through SolarSoft or deployed as an AstroGrid CEA service.)
  3. The algorithm runs and returns a FITS file to the user.
  4. The user can view an image within the FITS file displaying recognized loops superimposed in colour over the original AIA flatfield image. Loops are colour-coded by temperature.
  5. The user can also view a table of footprints for each terminus of a recognized loop. The footprints are described in terms of solar coordinates, radius, and temperature.

Technical Use Case

Steger and Raghupathy's 'Improved Curve Tracing' algorithm (first choice)

  1. The automated loop recognition algorithm receives an AIA flatfield image as input.
  2. Iteratively apply Steger's curve tracing algorithm to identify loops, limiting large changes of angle to improve curve following at junctions.
  3. Calculate inner products based on average curve orientation to detect fading curves.
  4. Apply lookahead to fading curves to detect possible re-emergence of the curve.
  5. Identify loop terminating pixels. Use ancillary SDO pointing files to establish corresponding solar coordinates.
  6. Superimpose loops onto original AIA flatfield image. Write to a FITS file with an image extension for the loop recognition image and a tabular extension containing footprint information, including solar coordinates, radius of footprint, and temperature.
  7. Return FITS file.

OCM with dependence on magnetic extrapolation (second choice)

  1. The automated loop recognition algorithm receives an AIA flatfield image as input.
  2. Clean image with median filtering, unsharp masking, and linear filtering
  3. Apply Strous algorithm to identify loop pixels
  4. Now find HMI magnetogram corresponding to time coverage of AIA image; call magnetic field extrapolation algorithm. Return azimuths to loop recognition algorithm
  5. Create a weighted pixel matrix using magnetic field azimuths, pixel intensity, angular information and proximity to previously identified loops. Apply matrix iteratively over all pixels to enhance loop connectivity (oriented connectivity method).
  6. Smooth loop curves with a B-spline filter.
  7. Link disconnected loop subsections using an edge-linking algorithm such as the Hough Transform.
  8. Smooth the edge-linked loops with a second B-spline filter.
  9. Identify loop terminating pixels. Use ancillary SDO pointing files to establish corresponding solar coordinates.
  10. Superimpose loops onto original AIA flatfield image. Write to a FITS file with an image extension for the loop recognition image and a tabular extension containing footprint information, including solar coordinates, radius of footprint, and temperature.
  11. Return FITS file.

Curvelet analysis (third choice)

  1. The automated loop recognition algorithm receives an AIA flatfield image as input.
  2. Clean image with median filtering, unsharp masking, and linear filtering
  3. Iteratively apply curvelet transform to identify loops.
  4. Smooth loop curves with a B-spline filter.
  5. Link disconnected loop subsections using an edge-linking algorithm such as the Hough Transform.
  6. Smooth the edge-linked loops with a second B-spline filter.
  7. Identify loop terminating pixels. Use ancillary SDO pointing files to establish corresponding solar coordinates.
  8. Superimpose loops onto original AIA flatfield image. Write to a FITS file with an image extension for the loop recognition image and a tabular extension containing footprint information, including solar coordinates, radius of footprint, and temperature.
  9. Return FITS file.

Quicklook Products

  • FITS file containing two extensions:
    • AIA image with superimposed recognized loops
    • Table suggesting footprint coordinates, intensity and other statistical data in multiple wavelengths observed using different AIA channels.

Support Information

  1. Lee, J.K., Gary, G.A., Newman, T.S. American Astronomy Society, SPD meeting #34. 02/2003. 2003SPD....34.0305L
  2. C. Steger - 'An Unbiased Detector of Curvilinear Structures'.
  3. K. Raghupathy, Thomas W. Parks - 'Improved Curve Tracing in Images'.

-- MikeSmith - 03 Aug 2005 -- ElizabethAuden - 29 Jun 2005

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Topic revision: r7 - 2005-09-30 - ElizabethAuden
 
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