ISOCAM Interactive Analysis User's Manual Version 5.0 - ISO - ESA

262 CHAPTER 20. ADVANCED DATA CALIBRATION
• Project the images contained in the FITS files and place the results in the file result.fits:
CIA> spawn, !cia_exec+’/projection -i2,input -o result.fits’
• Take a look at the result:
CIA> result = readfits(’result.fits’, hdr)
CIA> tviso, result[*, *, 0]
20.15.4 Back projection
The projection routines also allow the possibility to back project a raster MOSAIC to a set
of EXPOSUREs. A real source will, due to the many effects present in the ISOCAM data,
have a somewhat different signal in each EXPOSURE. The purpose of the data calibration is to
minimize or eliminate this difference. Knowledge of how the signal varies from EXPOSURE to
EXPOSURE is not contained in the raster MOSAIC, so the back-projected EXPOSUREs will
each contain an averaged source signal. Figures 20.7 and 20.8 illustrate this point. Note that
this averaged source signal is really an idealized signal, i.e. it assumes that the same source has
the same signal in each EXPOSURE. This assumption can be useful for testing the quality of
the data analysis. The less the signal in the original EXPOSUREs deviates from the idealized
signal in the back-projected EXPOSUREs the better the quality of the data calibration.
The back projection is performed with the routine back project. You should of course only
perform back projection on a fully calibrated PDS after creation of the raster MOSAIC:
CIA> raster_scan, raster_pds
CIA> help, raster_pds.image
FLOAT = Array[32, 32, 8]
CIA> back_project, raster_pds, images
CIA> help, images
IMAGES FLOAT = Array[32, 32, 8]
You can use stat to check the quality of your calibration. The lower the RMS the less the
averaged or idealized signal deviates from the real calibrated and corrected signal:
CIA> stat, images - raster_pds.image
-------------------------------------------
Image dimensions: 32 32
Number of frames: 8
Total number of pixels: 8192
-------------------------------------------
Minimum Maximum Mean Median RMS
-10.7506 14.4660 0.144570 0.00626230 0.902133