Want a task that will generate meta data for variation with groups of exposures
Intra-Camera vignetting maps
mask all sources within the images to produce sky gradient + vignetting map for each image
median combine these and then use it to produce residual maps for each camera
residual images can be fitted with a simple plane and the gradient, orientation, min and max are recorded as meta data for the exposure
NB: hard to decouple the vignetting pattern and the sky background... differently camera orientations may help to filter out he sky gradient component but with only 10 cameras this may not work that well
Fit 2D polynomial maps of vector field of PSF parameters
Extract sources and psf parameters in each exposure (psf size, eccentricity, orientation etc) and fit a 2D polynomial to sampled vector field
Can then repeat a similar process to previous metric, looking for variability between the psf parameter maps
This would allow us to see if all psf elongation is orientated in the same direction (indicating dome vignetting) or randomly (indicated a detector tilt issue or something else within the instrument)
Could use bright time as an opportunity to produce vignetting and psf elongation maps, as the brighter sky background will produce brighter residual gradients than ones produced in dark time
Want a task that will generate meta data for variation with groups of exposures
Intra-Camera vignetting maps
Fit 2D polynomial maps of vector field of PSF parameters
Could use bright time as an opportunity to produce vignetting and psf elongation maps, as the brighter sky background will produce brighter residual gradients than ones produced in dark time