Class Hierarchy: Base -> Component -> CalibImages

The CalibImages class is a container for bias/dark/flat/fringing/non-linearity images. An introduction bias and flat calibration is available here.

This class can be used to generate calibration images and to apply them in a single step to science images. This class is using functions available in the imProc.dark and imProc.flat packages.

• Bias [class: AstroImage]

• Dark [class: AstroImage]

• Flat [class: AstroImage]

• Fringe [class: AstroImage]

• Linearity

• DarkGroupsKey - cell array of keys

• DarkGroupsVal - Cell (size Nimages) of cells (size Nkeys)

• SubtractOverScan - A logical (default is true)

Additional private properties are updated automatically from the image header:

• FlatFilter
• DarkExpTime
• DarkTemp
• FringeFilter
• FringeExpTime

The following static method can be use to read FITS calibration images into a CalibImages object:

CI = CalibImages.read('Bias','LAST.2.1.2_20200821.060000_clear___1_0_dark_proc_Image_1.fits','BiasMask','LAST.2.1.2_20200821.060000_clear___1_0_dark_proc_Mask_1.fits','Flat','LAST.2.1.2_20200821.060000_clear___1_0_flat_proc_Image_1.fits','FlatMask','LAST.2.1.2_20200821.060000_clear___1_0_flat_proc_Mask_1.fits');

Alternatively, if the images file names follows the LAST/ULTRASAT file name convention implemented in the FileNames object) you can read the latest calibration files stored in a specific directory:

CI = CalibImages.loadFromDir
% see help for more information

Several tools for creating bias and flat images exist. These tools are using the functions in the imProc.dark and imProc.flat packages.

Some simple examples:

CI = CalibImages('Bias',Bias, 'Flat',Flat);  % load bias/flat images
% create bias/flat and process:
CI.createBias(Images);
CI.createFlatFilter(Images, 'R');  % create a flat image for a single filter
CI.createFlat(Images);  % create a flat images for all filters

The CalibImages class contains functions for specific steps (e.g., debias, overscan, deflatOneFilt, deflat). To apply all the calibration steps (e.g., bias subtraction, flat correction,,,) in a single call:

These steps includs:

• Create a mask image
• Flag staturated pixels in mask
• Subtract bias image
• Propagate bias mask to science mask.
• Subtract and remove overscan from image
• Nonlinearity correction
• Divide image by flat
• Propagate flat mask to science mask.
• Correct for fringing
• Multiple image by gain

CI.processImages(Images); % subtract bias and divided by flat

• isemptyProp - Check if some properties (e.g., 'Bias') images are empty.
• crop - Crop all images in a CalibImages object.
• populateLinearity - read Linearity file from the config file and populate the CalibImages.
• exist - Check if Bias/Dark/Flat/... image is populated in a CalibImages object.

% check if bias and flat images exist in CalibImages object
% R1 corresponds to Bias, while R2 corresponds to Flat
[R1, R2] = isemptyProp(Obj, {'Bias','Flat'}, 'Image')

% crop the Calibration images in the CalibImages object:
CI.crop([1 100 1 100])

% Check if Dark calibration image exist:
CI.exist('Dark')