Object-Based Methods for Analyzing Solar Images

D. M. Zarro (SM&A/GSFC)




CONTENTS


1. INTRODUCTION

1.1 Creating a Map Object
1.2 Plotting a Map Object
1.3 Plotting Map Objects on Different Color Scales

2. OPERATIONS WITH MAP OBJECTS
2.1 Rotating a Map Object
2.2 Stretching and Resizing a Map Object
2.3 Extracting a Sub-region From a Map Object
2.4 Differencing Map Objects

3. APPLYING MAP OBJECTS TO SOLAR IMAGES
3.1 Creating a SOHO/EIT Map Object
3.2 Creating a SOHO/CDS Map Object
3.3 Creating a Yohkoh/SXT Map Object
3.4 Converting a FITS File to a Map Object
3.5 Correcting for Solar Differential Rotation

4. OVERLAYING MAP OBJECTS


1. INTRODUCTION

In its simplest form, an IDL map object is a structure that contains two-dimensional (2-d) image data with accompanying pixel coordinate and spatial scale information. The latter parameters are defined as properties of the map and are unique for each image source. Defined in this manner, an arbitrary image can be manipulated or transformed in a manner that is independent of the image source.

With the advent of version 5, IDL has been enhanced to support object-oriented programming (OOP). What this means in practical terms is that structures that once could only contain data variables as tags, can also have additional fields that are actually functions (or procedures) that operate on the data themselves. These structure functions are called methods. In the context of OOP, image maps with such methods are known as objects.

This software note describes how to create and use map objects for processing solar images. We will use sample images obtained from instruments onboard SOHO and Yohkoh missions. Typical processing tasks include: roll-correction, stretching, translation, solar rotation-compensation, and image coalignment. Although we discuss solar examples, the techniques described below are applicable to any two-dimensional dataset. IDL mapping software is incorporated into the SolarSoft system - a set of integrated software libraries, databases, and system utilities which provide a "common" programming and data analysis environment for Solar Physics.

1.1 Creating a Map Object

The low-level function for creating a map object is make_map. In this example, a 256x256 array is created with findgen and converted to a map variable: 

IDL> image=findgen(256,256) 
IDL> map=make_map(image)
IDL> help,/st,map

** Structure <4031f908>, 8 tags, length=40056, refs=1:
   DATA            FLOAT     Array[100, 100]
   XC              FLOAT           0.00000
   YC              FLOAT           0.00000
   DX              FLOAT           1.00000
   DY              FLOAT           1.00000
   TIME            STRING    '11-Mar-1998 11:40:44.000'
The resulting map is an anonymous structure with the following tag definitions:

The above tag definitions are defined also as keywords in make_map. For example, a map with a pixel spacing of 2 units in the x-direction and 3 units in the y-direction is created by: 

IDL> image=findgen(256,256) 
IDL> map=make_map(image,dx=2,dy=3)
IDL> help,/st,map
** Structure <403cd0e8>, 9 tags, length=40072, refs=1:
   DATA            FLOAT     Array[100, 100]
   XC              FLOAT           0.00000
   YC              FLOAT           0.00000
   DX              FLOAT           2.00000
   DY              FLOAT           3.00000
   TIME            STRING    '18-Mar-1998 15:23:16.000'


Note that the basic map structure definition is kept intentionally simple, with data and coordinate parameters being the main defining properties. The units of the coordinate system are also arbitrary. Additional properties are added two ways:

  1. At the definition stage. For example, to include a property UNITS that specifies coordinate units: 

    IDL> nmap=make_map(map,units='arcsecs')
IDL> help,nmap,/st
** Structure <403cd0e8>, 9 tags, length=40072, refs=1:
   DATA            FLOAT     Array[100, 100]
   XC              FLOAT           0.00000
   YC              FLOAT           0.00000
   DX              FLOAT           2.00000
   DY              FLOAT           3.00000
   TIME            STRING    '18-Mar-1998 15:23:16.000'
   UNITS           STRING    'arcsecs'
  2. After the definition stage. Following the same example, but using the function add_prop : 

    
IDL> add_prop,map,units='arcsecs'

    produces the same result. Multiple properties are added as multiple keywords, with the restriction that each property name is unique.

1.2 Plotting a Map Object

Map objects are plotted using the procedure plot_map . Thus, using the 2-d image created earlier, 

IDL> plot_map,map



Fig. 1 - Image Map

The procedure plot_map inherits all the major IDL plot keywords such as xstyle, ystyle, font, charsize, charthick, etc. It supports the following additional keywords:

The use of more advanced keywords will be demonstrated later in this tutorial.

1.3 Plotting Map Objects on Different Color Scales

The following steps demonstrate how to simultaneously plot map objects using different color tables. 


IDL> image=findgen(256,256) 
IDL> map=make_map(image)                ;-- make a simple map
IDL> nc=100                             ;-- # of colors per image
IDL> loadct,3,ncolors=nc                ;-- load red table from  0:nc-1
IDL> plot_map,map,ncolors=nc            ;-- plot map using red table
IDL> loadct,1,bottom=nc,ncolors=nc      ;-- load blue table from nc:2*nc-1
IDL> plot_map,map,bottom=nc,ncolors=nc  ;-- plot using blue table

The key to plotting with separate color tables is to divide evenly the total number of available device colors. The latter is given by the system variable !d.table_size. In the above example, the total available colors is 200. Hence, the color table is split into two equal halves of nc=100 colors each. The routine loadct loads a red color table (#3) into the first 0 to nc-1 color range, and blue color table (#1) into the second nc to 2*nc-1 range. The resulting plots appear as:

Fig. 2a - Red Table Fig. 2b - Blue Table

2. OPERATIONS WITH MAP OBJECTS

The following examples demonstrate various image processing that can be applied to map objects.

2.1 Rotating a Map Object

Map objects are rotated using the function rot_map . An interesting example is provided by rotating (i.e, rolling) a SOHO EIT full Sun image. The routines for creating an EIT map object will be described in section 3.1 . For now, assume a 512x512 EIT map, eit_map with the following properties: 


   DATA            INT       Array[512, 512]
   XC              FLOAT           14.2450
   YC              FLOAT          -13.0278
   DX              FLOAT           5.18000
   DY              FLOAT           5.18000
   TIME            STRING    '15-Mar-1998 00:00:49.985'
   DUR             FLOAT           12.1000
   ID              STRING    'EIT: 304'
   SOHO            INT              1
   UNITS           STRING    'arcsecs'

This map object contains an EIT 304 Angstrom image that has been double-binned from it's original 1024x1024 size. Note the additional properties ID specifying the image wavelength, DUR specifying the image duration, and SOHO specifying image source. To rotate this map through, say, 60 degrees clockwise about its center, and display the results: 


IDL> rmap=rot_map(eit_map,60.)
IDL> plot_map,eit_map,/log
IDL> plot_map,rmap,/log,/new

IDL> help,/st,rmap

   DATA            INT       Array[512, 512]
   XC              FLOAT           14.2450
   YC              FLOAT          -13.0278
   DX              FLOAT           5.18000
   DY              FLOAT           5.18000
   TIME            STRING    '15-Mar-1998 00:00:49.985'
   DUR             FLOAT           12.1000
   ROLL            FLOAT           60.0000
   ROLL_CENTER     FLOAT     Array[2]
   ID              STRING    'EIT: 304'
   SOHO            INT              1
   UNITS           STRING    'arcsecs'

Fig. 3a - Before roll Fig. 3b - After roll

The keyword /new forces the creation of a new plot window in which to plot the rotated image. The rotation is performed by rotating the coordinates of each image pixel, computing a new grid of rotated coordinates, and interpolating the new grid back to the original image. Generally, the dimensions of the rotated grid will be larger than the original image. By default, rot_map will preserve the original image dimensions by clipping image pixels that fall outside the original dimensions. The keyword /full_size inhibits clipping.

The roll angle and roll center are added as property fields name ROLL and ROLL_CENTER to the rotated map. The roll angle in units of degrees measured clockwise from North and the roll center coordinates are in data units (i.e., arcsecs). Note that if the input map is already rolled, then the new roll angle will be added to the existing roll value. By default, the map is rotated about it's center. The keyword center can be used to rotate about an arbitrary center, e.g., center=[20,30] .

The keyword roll has the same functionality and can be used to roll a map to any given roll angle, regardless of it's current roll angle. For example, to rotate a map to a 100 degree roll: 


IDL> rmap=rot_map(eit_map,roll=100.)

2.2 Stretching and Resizing a Map Object

The function grid_map changes the dimensions and pixel spacing of a map object. For example, the following command will rebin the 512x512 EIT map displayed in figure 3a, to a 128x128 size map: 


IDL> gmap=grid_map(map,128,128)

The (x,y) pixel spacings of the output map are computed automatically. To change the spacing between pixels, use the keywords dx, dy . For example, to rebin to a pixel spacing of 2 units in x- and 5 in y-directions: 


IDL> gmap=grid_map(map,dx=2,dy=5)

The (x,y) dimensions of the output map are computed automatically. Spacing and output dimension parameters can be combined to produce different stretching and resizing effects. For large images, regridding can be a slow process since each pixel has to be interpolated onto a new spatial scale.

2.3 Extracting a Sub-Region From a Map Object

The procedure sub_map extracts a sub-region from a map object. It can be used in two ways, graphically or manually. 


IDL> sub_map,map,smap,/plot,[xrange=xrange,yrange=yrange,ref_map=ref_map]

A sub-region of map is selected graphically by using the keyword /plot, in which case plot_map is called and a "rubber-band" cursor is used to select a sub-region. The sub-region map is returned in smap. The data coordinate limits of the sub-region are returned as two-element vectors in the keywords xrange and yrange. Alternatively, the data coordinate limits can be input via the keywords xrange=[xmin,xmax], yrange=[ymin,ymax], or via the keyword ref_map. In the latter case, the extracted sub-region will be extracted according to the xrange/yrange values of ref_map.

2.4 Differencing Map Objects

The procedure diff_map subtracts two map objects to produce a difference map. 


IDL> dmap=diff_map(map1,map2,[/rotate])

The output map object dmap contains a difference image of the two images contained in the map1 and map2 input maps -- the second image is subtracted from the first. The optional keyword /rotate solar rotates the second image to the time of the first image prior to subtraction. Solar rotation is described in section 3.5 .

3. APPLYING MAP OBJECTS TO SOLAR IMAGES

This section describes the steps involved in creating map objects for various solar datasets. The routine index2map is a generally useful program for creating map objects from any dataset that is in a Yohkoh index/data format.

3.1 Creating a SOHO/EIT Map Object

The following lines read and process EIT images into maps: 


IDL> files=eit_files('19-mar-98','20-mar-98',wave=304,/full)
IDL> read_eit,files,index,data,[outsize=outsize]
IDL> eit_prep,index,data=data,outindex,outdata 
IDL> index2map,outindex,outdata,emap

Each step is summarized as follows:

  1. eit_files returns EIT filenames for a range of times/dates and wavelength filter. This example returns filenames (string array) for 304 Angstom full-disk images.
  2. read_eit reads the filenames array and returns an index structure representation of the FITS file header and a 2-d data array of image values. The latter is a 3-d array when more than one image is read. The optional keyword outsize specifies the dimensions of the output image. For example, setting outsize=512 produces a 512x512 image.
  3. eit_prep applies degridding, dark current, and flatfield corrections to the image data.
  4. index2map converts the corrected outindex and outdata variables into a map object. The latter is an array when multiple images are copied.

In the case of full-disk images, the 1024x1024 array size can lead to IDL out-of-memory problems on some systems. To avoid this problem, there is an optional outsize keyword to rebin images to a smaller dimension (with accompanying loss of spatial resolution). The following example creates a 512x512 map object. 


IDL>index2map,outindex,outdata,emap,outsize=512

The outsize keyword can also be used when reading the image with read_eit. More detailed documentation on manipulating EIT data is located in the EIT Users Guide .

3.2 Creating a SOHO/CDS Map Object

The function mk_cds_map creates CDS map objects. The CDS instrument produces images by rastering in pre-determined spectral lines. Images can be derived by using the peak count rate intensity of these lines, or by integrating the count rates over the observed spectral wavelength band. The following steps illustrate reading and processing CDS images into maps: 


IDL> files=cds_files('19-mar-98','20-mar-98',study=study,info=info)
IDL> read_cds,files,ql
IDL> cds_map=mk_cds_map(ql,window,/calib,/clean)

Each step is summarized as follows:

  1. cds_files returns CDS filenames for a range of times/dates. This procedure requires that the environment variable CDS_FITS_DATA point to the directory containing the CDS FITS files. An optional input keyword study can be used to search for specific files. This keyword is an acronym for the CDS study, e.g. study='SYNOP' . An optional output keyword info returns a string array of observation start times and study names for the files. Currently, the mapping software requires that only maps with similar dimensions can be combined. Since CDS studies can have arbitrary raster sizes, one must be careful not to mix different studies into an array of maps.
  2. read_cds reads each file name and returns an array of "quicklook" data structures QL. Each QL structure contains a single raster experiment in several simultaneous wavelengths.
  3. mk_cds_map creates map objects for selected selected spectral windows. The window argument is a scalar or vector of window numbers. Each window corresponds to a particular wavelength range. If this argument is not included, then the function will prompt for window numbers. The following keywords are also supported:

3.3 Creating a Yohkoh/SXT Map Object

The following example, reads and creates an SXT map object from an SXT full-frame data file: 

IDL> rd_xda,'sfr970407.1229',-1,index,data
IDL> sxt_prep,index,data,outindex,outdata,/register,/norm,/roll
IDL> index2map,outindex,outdata,sxt_map

Details on the use of rd_xda for reading SXT files can be found in the Yohkoh Analysis Guide. The procedure sxt_prep applies instrumental corrections to the SXT raw image that include (among other things) adjustment for spacecraft jitter, roll, dark current subtraction, and exposure normalization. Multiple images can be combined with the restriction that they have the same dimensions. Figure 4 shows a map object created from an SXT full-frame AlMg filter image with the following properties: 


IDL> help,/st,sxt_map
** Structure <40a74fe8>, 9 tags, length=1048648, refs=2:
   DATA            FLOAT     Array[512, 512]
   XC              FLOAT          -73.8006
   YC              FLOAT          -154.193
   DX              FLOAT           4.91000
   DY              FLOAT           4.91000
   TIME            STRING    ' 6-Jun-1996 19:30:37.000'
   DUR             FLOAT           1.00000
   ID              STRING    'AlMg '
   UNITS           STRING    'arcsecs' 

IDL> plot_map,sxt_map,/log,grid=20



Fig. 4 - SXT map

The above image is plotted using the keyword grid=20. This keyword enables overlaying of a latitude and longitude grid with a grid spacing equal to the keyword value in units of degrees. Setting grid to a negative value will disable gridding, but will enable plotting of the optical solar limb. The same effect is achieved using the keyword /limb.

3.4 Converting a FITS File to a Map Object

FITS files can be converted to map objects by using the procedures mreadfits and index2map. The following example reads and converts a SOHO/MDI full-disk magnetogram FITS file into a map object, and plots the result: 


IDL> mreadfits,'smdi_maglc_fd_19980331_1117.fts',index,data,header=header
IDL> index2map,index,data,map
IDL> loadct,0
IDL> plot_map,map

The keyword header optionally returns the string header of the FITS file. Multiple FITS files can also be read by mreadfits.



Fig. 5 - MDI map

A second example is provided by TRACE data: 


IDL> read_trace,files,dset,index,data
IDL> index2map,index,data,trace_map
IDL> plot_map,trace_map

where the procedure read_trace is a special purpose reader for TRACE files.

3.5 Correcting for Solar Differential Rotation

The function drot_map rotates a map object using the solar differential rotation formula of Howard, Harvey, and Forgach, Solar Physics, 130, 295, 1990. Since the formula is derived from statistical studies of small-scale magnetic features, it is most accurately applied to photospheric images and is less accurate when applied to transition region and coronal images observed by EIT and SXT, respectively. The following example demonstrates the differential rotation of the above full-disk SXT image over 4 days. 


IDL> gmap=grid_map(sxt_map,256,256)
IDL> dmap=drot_map(gmap,4,/days)
IDL> plot_map,sxt_map,/log
IDL> plot_map,dmap,/log,/new,/limb



Fig. 6 - Rotated SXT map

Because solar rotation involves interpolating each pixel to a new location, processing large 512x512 or 1024x1024 images can be very time-consuming and memory-intensive on some systems. In the above example, the SXT map object is rebinned to a more manageable 256x256 size prior to rotation. The function drot_map accepts map object and duration (in hours) as input arguments. It also supports the following keywords:

The function drot_map combines regridding, roll-correction, and translation through the following additional keywords:

4. OVERLAYING MAP OBJECTS

Map objects are graphically overlayed using the keyword /over in plot_map . In the following example, an SXT map is contoured over an EIT map. 


IDL>plot_map,eit_map,fov=sxt_map,/log  ;-- first plot EIT 
IDL>plot_map,sxt_map,/log,/over,/rotate  ;-- then contour over SXT

The fov keyword is a map structure from which plot_map infers xrange and yrange values. In the above example, only the sub-region of eit_map that overlaps with that of sxt_map field-of-view is displayed. This keyword is optional. Different sub-regions can be displayed also via the xrange and yrange keywords.

The /rotate keyword corrects for solar rotation of the overlayed image relative to the first. This correction is important if the time difference between images is more than several hours. The overlayed image can be rotated to a specified time via the keyword time.

Fig. 7a - EIT Fig. 7b - SXT



Fig. 7c - SXT/EIT Overlay



The following example shows an overlay of MDI magnetogram contours on an SXT observation of flare loops. The example illustrates the use of additional keyword options in plot_map.



Fig. 8 - MDI/SXT Overlay 


IDL>set_line_color               
IDL>levels=100+findgen(11)*100.  
IDL>plot_map,sxt_map,/log        
IDL>plot_map,mdi_map,/over,/rotate,/positive,lcolor=5,levels=levels
IDL>plot_map,mdi_map,/over,/rotate,/negative,lcolor=2,levels=-levels

Each step is explained below:

  1. set_line_color defines a simple color table in which color=2 corresponds to yellow, and color=5 corresponds to blue.
  2. findgen is used to define an array of contour levels: 100,200...1000.
  3. the SXT map specified in sxt_map is plotted.
  4. positive MDI magnetogram values in the map mdi_map are overplotted as blue contours.
  5. negative MDI magnetogram values are overplotted as yellow contours.




The final example shows an overlay of a CDS Ne VI map on an EIT 171 map, for a limb active region. 


IDL>plot_map,eit_map,/log        
IDL>plot_map,cds_map,/over,cthick=2

The keyword cthick=2 specifies a double thickness contour for the overlay image.

Fig. 9a - EIT 171 Fig. 9b - CDS Ne VI



Fig. 9c - CDS/EIT Overlay

Last Revised: Wed Mar 1 19:55:20 2000