Gain calibrating nonuniform image-array data using only the image data

Abstract

An algorithm is developed for calibrating the spatial nonuniformity of image-array (CCD-type) detectors. Like other techniques this approach uses multiple, spatially displaced images. In circumstances where high-precision flat fields are not available by other means (i.e., sky flats) this technique is advantageous as it uses the data frames for gain calibration even when the array images extended, nonuniform, sources. Numerical experiments and direct observations with intrinsically uniform and quite nonuniform detectors show that this algorithm is useful when data frames are crowded with sources - circumstance where 'median filtering' flatfielding techniques often fail. The algorithm described is robust and efficiently uses information from multiple data frames to determine pixel gain variations, using visible and IR array observations of extended sources.