Manipulating Images

 

Processing a single-image FITS file

This is the most basic operation. To check if the fits file is not a multiple fits file, try

IDL> print, eit_fxpar(hdr, 'NAXIS3')

If NAXIS3 greater than 1, go to Dealing with Multi-image fits file. Anyhow, if you've got a single-image fits file, and if you want to obtain the image data, you could do:

IDL> img = readfits(file, hdr)

which will read the data directly from the fits file and return the EIT header information. However, this method is not recommended. It is better to always make use of the eit_prep.pro program.

The eit_prep.pro program

Attention EIT software users

The calling syntax of eit_prep has just changed and the new version is NOT backwards compatible. Please modify your programs according to the update instructions.

If you'd like to have the data properly calibrated (i.e. flat-fielded, degridded, exposure time normalized to DN [data numbers] per second, filter normalized, and response normalized), there is a program called eit_prep.pro. This program should be used whenever possible since its source code is regularly updated to include the latest developpements of the calibration. (For descriptions of exposure time and filters, see header information). To read in a single-image EIT FITS file, use eit_prep like so:

IDL> eit_prep, file, header, image

which reads the specified FITS file, analyzes the content of the header and applies all the relevant calibrations. These include

A few other corrections (vignetting, stray-light) will be added soon. For more details, see the calibration section of this guide.

If you wish you can various keywords to your call to eit_prep in order to control the level of calibration applied to the data:

IDL> eit_prep, file, header, image, /no_calibrate

this will return a raw image with no calibration applied at all. It is equivalent to the simple use of read_fits described above.

Dealing with Multi-image FITS files

If the file you are dealing with is a multiple-image file, you can process a single image, a vector, or all the images:

Single image: IDL> eit_prep, file, hdrs, datacube, image_no=3, /save_zero
Vector: IDL> eit_prep, file, hdrs, datacube, image_no=[0,5,22], /save_zero
All the images: IDL> eit_prep, file, hdrs, datacube, image_no='all', /save_zero

If all of the data is missing in a single image, the keyword /save_zero forces eit_prep to return a blank image (normally it would just return a zero, which won't fit into your data cube). You now have a processed data cube - the images may be of different wavelengths, you can check:

IDL> print, eit_fxpar(hdr, 'WAVELNTH', image_no=5)

which returns the wavelength of the fifth image in the data cube. You can also return an array of all of the wavelengths:

IDL> waves = eit_fxpar(hdr, 'WAVELNTH', image_no='all')

Dealing with many FITS files

There are various methods for dealing with multiple FITS files. If the files contain only single images then the call to eit_prep as described in reading a single FITS file section works for a vector file list. An alternative method for reading many FITS files (single image or multiple images) is:

IDL> read_eit, filelist, inhdr, imgs
IDL> eit_prep, inhdr, outhdr, imgs, data=temporary(imgs)

Often one might wish to process a number of FITS files without saving all the data in memory but rather writing the processed data to new FITS files. This is accomplished via:

IDL> mk_eit_l1, list = filelist

You may wish to examine the other options for this routine.

Displaying images

Once you've got your image, you can pull up an IDL window and display it. We recommend logarithmic scaling:

IDL> tvscl, alog10(img>0.5)

where img is two-dimensional. If you've got several images in a data cube, you can do

IDL> tvscl, alog10(img[*,*,5]>0.5)

which will display the 6th image of the cube. Since there may be pixels with zero counts in the image, the image is floored with a value of 0.5 before taking its logarithm. Setting a lower bound avoids errors generated when trying to compute the non-defined value of the logarithm of zero. Experiment by varying the lower and upper limits until the image looks best. Note: images with the same wavelength should be displayed with the same upper and lower limits if they are to be compared.

EIT color tables

In the software tree, in the directory specified by the environment variable SSW_SETUP_DATA, lurks a file called 'color_table.eit'. You should also ensure that you have an environment variable 'coloreit' defined as this file. There is one EIT color table dedicated to each of the four wavelengths. These color tables are optimized to ensure a good rendition of the details present in the data. Hence the EIT user's rule: No EIT image is to be displayed with the wrong color table. Some are tempted to always use "Red Temperature" or another color table, and many have suffered for their folly. To choose the correct color table entry, do:

IDL> wave = eit_fxpar(hdr, 'WAVELNTH')

or

IDL> wave = eit_fxpar(hdr, 'WAVELNTH', image_no=5)
IDL> eit_colors, wave

You could also do:

IDL> xloadct, file = getenv('coloreit')

to get the color table widget.

For example, the image on the left is an EIT 284 displayed with the Red Temperature table (bad!) without playing with the lower and upper limits:

IDL> tvscl, alog10(img>0.5)

While the image in the middle is displayed with better limits but in the wrong color table:

IDL> tvscl, alog10(img>0.02<50)

while the final image (which shows much better quiet sun detail because the color table is optimized for an EIT image in that particular wavelength) is both scaled properly and has the correct color table:

 

 

EIT Pointing

Note: This section is important only for older versions of the data. Current versions of data have the corrected EIT pointings in the headers.

This section is not meant to be an exhaustive study of EIT pointing questions, but rather to introduce the User to the main parameters and PITFALLS, especially with regards to co-alignment with other instruments. It is assumed the user is familiar with the standard FITS keywords, CRPIX, CRVAL, etc. NOTE, FITS standard starts with pixel (1,1) while IDL uses pixel (0,0). you may need to correct for this.

WHERE ARE WE POINTED? Not an easy question. Until recently, EIT had used automated limb-fitter to determine the Solar pointing. As is well known, this method can fail given the presence of above-limb material. The level zero data has been re-processed with a more accurate determination of the pointing. For older data, you can obtain the pointing of EIT, by ignoring the FITS headers and using the function eit_point, e.g.

IDL> xy = eit_point(date, wavelength)

An additional complication is subfield images taken prior to the re-processing date. These images contain no values of CRPIX, CRVAL, but instead have the "raw" pixel coordinates, (P1_X:P2_X,P1_Y:P2_Y). To convert these to Solar coordinates one must get the xy pointing as above and then to obtain the lower left corner of the image:

IDL> CRPIX1 = (eit_fxpar(hdr,'p1_x')-xy(0)-1) * eit_pixsize()
IDL> CRPIX2 = (eit_fxpar(hdr,'p1_y')-xy(1)-20) * eit_pixsize()


EIT Timing

It is necessary to devote a short description of the times given in the EIT image headers. In particular, one needs to be cognizant of two times, the exposure time and the time of observation.

EXPOSURE TIME: The time given in the header reflects the commanded exposure time plus a SHUTTER DWELL TIME which is approximately 2.1 seconds. Due to on-board software problems, this shutter time is not properly reflected in the images prior to July 17, 1996 and has been fixed at 2.1 seconds.

OBSERVATION TIME: Here again, there is an ambiguity due to the on-board software. The time reflected in the DATE_OBS field is the "nominal" start time of the exposure. HOWEVER, we realized that this time was off from the "true" start time, by varying amounts up to 5 minutes. Starting from September 1997, a better approximation to the "true" start time is given in the CORRECTED DATE_OBS field (mapped to CORR_OBS in structures)l this time should be within ~ 15 s of the actual UTC of the start of the exposure. This may be important when performing detailed time comparisons, e.g. high cadence EIT images versus MDI hi-res magnetograms.

 


Web curator: Frédéric Auchère
Responsible NASA official: Joseph B. Gurman, Facility Scientist, Solar Data Analysis Center
joseph.b.gurman@gsfc.nasa.gov
+1 301 286-4767
NASA Goddard Space Flight Center
Solar Physics Branch / Code 682

Last revised: 2006 June 17 - J.B. Gurman