Fixed pattern noise (FPN) in infrared images seriously degrades the imaging quality and visual effect of infrared focal plane arrays (FPAs). Although many scene-based non-uniformity correction (NUC) algorithms have been developed recent years, the convergence speed of the bias and gain correction parameters still need to be further improved. In this paper, we present a novel NUC approach for IR FPAs which minimizes the total variation of the estimated IR irradiance guided by a noise model image, and we name it guided total variation (GTV) NUC method. A temporal detection factor is introduced to NUC procedure to prevent NU parameters updating when scene movement stops. In the proposed scheme, the correction parameters of the FPN are estimated via an iterative optimization strategy, frame by frame. The experimental results of synthetic and real IR videos demonstrate that the proposed algorithm have better NUC performance in terms of fewer ghosting artifacts and faster convergence than the state-of-the-art methods.
The radiation gain of UV image intensifier is an important index to measure response capability of ultraviolet detector, thus its accurate measurement is necessary. This paper establishes radiation gain measurement method and device of ultraviolet image intensifier, The process of measuring the magnitude and Influencing factors for the measurement of ultraviolet radiation gain by the equipment were analyzed. And the error analysis of the measurement uncertainty of the device, The radiation gain measurement has an extended uncertainty of 9.59%, It can meet the requirements of high precision measurement of radiation gain of UV image intensifier. The research achievement can support the research and development of domestic ultraviolet detectors, thus providing an effective and accurate detection method for improving and promoting the technical performance of ultraviolet detectors.