
20090606 : design notes on the multi-image photometry analysis

  assumptions:
  
  * each input image represents the same sky pixels : they are warped to a common frame.

  * each image has been previously processed, with the background subtracted and the psf model determined

  basic outline:

  * load images, masks, variance : for now, we should load all images.  in the future, we might be able to split this into segments.  

  * option: model and subtract background for each image (should not be needed)

  * option: smooth each image with a psf or fraction (not needed if stack smooths too much?)

  * generate the significance (chisq) image: X_i = sum(f_i^2 / var_i)

  * perform the peak detection on X_i

  * for each of the input images:

    * generate the significance image S_i = f_i^2 / var_i 
    
    * perform the peak detection on S_i

  * merge the list of peaks

  * generate the footprints

  * linear fit to the peaks with the set of images (psf for each image)


  design issues:
  
  * pmSource represents the analysis for an object on a single image
  * extended pmSourceSet to group connected pmSources on multiple images?
