Cao Yanpeng, Tisse Christel-Loic
Appl Opt. 2013 Sep 1;52(25):6266-71. doi: 10.1364/AO.52.006266.
In uncooled long-wave infrared (LWIR) microbolometer imaging systems, temperature fluctuations of the focal plane array (FPA) result in thermal drift and spatial nonuniformity. In this paper, we present a novel approach based on single-image processing to simultaneously estimate temperature variances of FPAs and compensate the resulting temperature-dependent nonuniformity. Through well-controlled thermal calibrations, empirical behavioral models are derived to characterize the relationship between the responses of microbolometer and FPA temperature variations. Then, under the assumption that strong dependency exists between spatially adjacent pixels, we estimate the optimal FPA temperature so as to minimize the global intensity variance across the entire thermal infrared image. We make use of the estimated FPA temperature to infer an appropriate nonuniformity correction (NUC) profile. The performance and robustness of the proposed temperature-adaptive NUC method are evaluated on realistic IR images obtained by a 640 × 512 pixels uncooled LWIR microbolometer imaging system operating in a significantly changed temperature environment.
在非制冷长波红外(LWIR)微测辐射热计成像系统中,焦平面阵列(FPA)的温度波动会导致热漂移和空间不均匀性。在本文中,我们提出了一种基于单图像的新颖方法,用于同时估计FPA的温度方差,并补偿由此产生的与温度相关的不均匀性。通过精心控制的热校准,推导了经验行为模型,以表征微测辐射热计的响应与FPA温度变化之间的关系。然后,在空间相邻像素之间存在强相关性的假设下,我们估计最佳FPA温度,以使整个热红外图像的全局强度方差最小化。我们利用估计的FPA温度来推断适当的非均匀性校正(NUC)曲线。在由一个640×512像素的非制冷LWIR微测辐射热计成像系统在显著变化的温度环境中获得的实际红外图像上,评估了所提出的温度自适应NUC方法的性能和鲁棒性。