Infrared imaging suffer from an undesired fixed-pattern noise mainly due to the response disparity of the individual detectors in a focal-plane array. Even though this nonuniformity noise can be removed after a blackbody calibration procedure, it tends to reappear due to the intrinsic nature of infrared sensing. Online nonuniformity correction techniques have been employed for denoising and tracking the drift, also avoiding to halt normal camera operations. In this paper, a new reference-free infrared imaging quality metric is presented. The main purpose of the proposed metric is to evaluate the quality of the denoised infrared images in real-time, exchanging the typical need of calibration sources by the knowledge of the fixed-pattern noise statistics. We compare the performance of the proposed metric against standard reference-based and reference-free metrics, using a variety of real-time nonuniformity correction techniques. Results show that the new metric is able to track the nonuniformity correction performance, constantly evaluating the quality of the denoised infrared image sequences.