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Nonuniformity Correction Algorithm for TEC-less Uncooled Infrared Imaging System

机译:少TEC非制冷红外成像系统的非均匀性校正算法

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The TEC-less uncooled infrared focal plane array (UIRFPA) imaging system faces the problem of nonuniformity caused by substrate temperature drift. Based on the establishment of an ambient temperature effect function, an improved nonuniformity correction (NUC) algorithm with temperature drift compensation is proposed. The first stage is offline calibration: a templates lookup table is established experimentally, and then the fitting regression coefficients are obtained using Least Squares. The second stage is real-time correction: the original readout image is preprocessed by the fitting template to compensate for nonuniformity drift, and the total variation (TV) NUC algorithm with an adaptive iterative step size is designed to correct the residual high-frequency noise. Real infrared video test shows that the algorithm effectively compensates for the nonuniformity drift while avoiding degradation and ghosting artifacts. The corrected image quality is better than that of the traditional TV-NUC method, and the roughness is reduced by nearly 40% compared to the original image.
机译:无需TEC的未冷却红外焦平面阵列(UIRFPA)成像系统面临由基板温度漂移引起的不均匀性问题。在建立环境温度影响函数的基础上,提出了一种具有温度漂移补偿的改进的非均匀校正算法。第一个阶段是离线校准:通过实验建立模板查找表,然后使用最小二乘法获得拟合回归系数。第二阶段是实时校正:通过拟合模板对原始读出的图像进行预处理,以补偿不均匀性漂移;设计具有自适应迭代步长的总变化(TV)NUC算法,以校正残留的高频噪声。 。真实的红外视频测试表明,该算法有效地补偿了非均匀性漂移,同时避免了退化和重影伪影。校正后的图像质量优于传统的TV-NUC方法,并且与原始图像相比,粗糙度降低了近40%。

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