【摘要】 由于焦平面自身的非均匀性、微偏振片阵列的工艺缺陷以及集成匹配误差等因素影响，导致偏振集成探测器存在更为严重的盲元和非均匀性问题。国标盲元检测和传统非均匀性校正方法的局限性导致偏振盲元漏检和非均匀性校正失真等问题。为了解决上述问题，建立了偏振探测器的线性响应模型，在响应校正的基础上，定标了微偏振片参数，实现了入射辐射的偏振校正。提出了一种基于非线性最小二乘拟合马吕斯曲线的盲元检测方法，标定了各个通道的标准曲线，利用曲线偏差和拟合参数，实现了响应盲元和偏振盲元的同时检测。利用自研的中波红外偏振集成探测器实验验证，校正结果显示，偏振校正后非均匀性相比原始数据和响应校正分别降低了98.14%和40.46%；检测出响应盲元有563个，偏振盲元有86个。成像结果表明，文中方法盲元识别准确，而国标法存在盲元漏检问题，校正后的偏振信息能够凸显成像场景的目标轮廓。有效解决了探测器原始数据存在的问题，为偏振集成探测器的数据处理和偏振成像质量提升提供了参考。更多还原

【Abstract】 Objective Due to the process defects of the micro-polarizer array and the matching error between the polarizer array and the focal plane array, the polarization modulation of the incident light with the same intensity and the same polarization direction is different, resulting in more blind pixels and more serious non-uniformity problems in the polarization integrated imaging system. Due to the influence of blind pixels and non-uniformity, infrared images will introduce noise, information loss and error increase. Therefore, the data preprocessing of polarization i ntegrated detection system is particularly important.Methods In this paper, the linear response model of the polarization detector is established. On the basis of the response correction, the parameters of the micro-polarizer are calibrated, and the polarization correction of the incident radiation is realized. A blind pixel detection method based on nonlinear least squares fitting Marius curve is proposed. The standard curves of each channel are calibrated. Using the curve deviation and fitting parameters,t he simultaneous detection of response blind pixel and polarization blind pixel is achieved.Results and Discussions The self-developed mid-wave infrared polarization integrated detector is used for experimental verification. The correction results show that the non-uniformity after polarization correction is reduced by 98.14% and 40.46% respectively compared with the original data and response correction data. 563response blind pixels and 86 polarization blind pixels are detected. The imaging results show that the blind pixel recognition of this method is accurate, while the national standard method has the problem of blind pixel missed detection. The corrected polarization information can highlight the target contour of the imaging scene. The problem of the original data of the detector is effectively solved, which provides a reference for the data processing and polarization imaging quality improvement of the polarization integrated detector.Conclusions This paper first analyzes the classification and causes of blind pixels. Due to the limitations of traditional detection methods and the influence of focal plane inhomogeneity, it is impossible to accurately determine the response blind pixels and polarization blind pixels. On the basis of non-uniformity correction, a nonlinear least squares fitting Marius response curve is proposed, and blind pixel detection is realized by means of curve deviation and fitting parameters. The experimental verification was carried out based on the polarization integrated detector developed by our research group. There are 563 response blind pixels detected by curve deviation and 86 polarization blind pixels detected by fitting parameters. The results show that the method in this paper can detect blind pixels more accurately than the national standard method, and reduce missed detection to a certain extent. Finally, the blind pixel compensation and imaging work are carried out. The imaging results show that the polarization imaging can better highlight the edge contour contrast of the target. The data preprocessing method of polarization integrated infrared detector in this paper can provide reference for subsequent high-quality polarization imaging detection.更多还原