DIAGNOSTIC AND QUALITY-ASSURANCE TOOLS FOR LOW-CONTRAST IMAGES OBTAINED FROM ARRAY DETECTORS

We investigate methods of estimating a background image frame for subt raction from a data frame for use when a more suitable measured backgr ound frame is not available. We define background as any signal compon ent that is not attributable to the phenomenon currently under investi gation. We describe a technique that is based on pixel-by-pixel least- squares regression of images for computing a background frame from ava ilable data. We argue that the same technique can be a useful quality- assurance tool for evaluating instrument performance. For example, it can help to separate image structure resulting from the reading proces s from structure resulting from the characteristics of the detector it self. We demonstrate that background estimation can be nontrivial by c omparing the results of different background estimation procedures by using data obtained from a CCD array detector. We investigate the temp erature-dependent contributions of the detector and readout electronic s to the total signal as a demonstration of the diagnostic capabilitie s of least-squares image regression.