Filtered gain calibration and its effect on DQE and image quality in digital imaging systems

Abstract

Digital imaging systems require offset and gain calibration to normalize the behavior of individual pixels. This normalization corrects for imperfections in the system and also external variables that have effects on uniformity. Imaging metrics like Detective Quantum Efficiency (DQE) and Modulation Transfer Function (MTF) define how sensitivity and resolution are transferred through the system. Gain calibration can result in a loss of DQE due to the noise associated with its application. The typical technique to minimize this noise is to average several gain calibration procedures so that the introduced noise is minimized. This paper discuses the effects of gain calibration on DQE. It measures DQE as a function of the number of gain calibration procedures averaged and contrasts it with a novel technique that uses a single filtered gain calibration. It demonstrates that noise filter techniques, applied to a single gain calibration, regains the loss in DQE without any degradation in resolution. This paper also compares imaging performance of a system using a filtered gain map against a system that has many gain calibrations averaged. The technique is demonstrated using a Thin-Film-Transistor (TFT)-based large area medical imaging system.