基于梯度场景的非均匀校正方法

发布时间：2018-06-16 22:53

  本文选题：遥感 + 非均匀性校正　； 参考：《光学学报》2017年05期

【摘要】：长波红外探测器经常被用于机载红外预警系统中,常受严重的非均匀性噪声干扰。为了校正探测器的非均匀性,补偿辐射响应非线性,提出了一种基于梯度场景的非均匀性校正方法。给出了探测器辐射响应非均匀性的观测模型;以标准黑体和梯度场景作为参考源,在理论上推导出校正系数表达式;利用原理样机进行了外场实验,并探测民航客机目标。实验结果表明:与基于黑体的两点校正方法相比,利用本文方法进行非均匀性校正后的图像,局部标准差峰值由8.57降低到2.39;对于相距50.64km的空中客车A319型客机,目标的信杂比由4.87提高到11.22。本文算法可以有效降低图像局部标准差,适用于机载红外预警系统。
[Abstract]:Long-wave infrared detectors are often used in airborne infrared early warning systems and are often disturbed by serious non-uniform noise. In order to correct the nonuniformity of detector and compensate the nonlinearity of radiation response, a gradient scene based nonuniformity correction method is proposed. The observation model of the nonuniformity of the detector's radiation response is given, the calibration coefficient expression is derived theoretically using the standard blackbody and gradient scene as the reference source, and the external field experiment is carried out using the principle prototype, and the target of the civil aviation airliner is detected. The experimental results show that the peak value of local standard deviation is reduced from 8.57 to 2.39 when compared with the blackbody based two-point correction method, and the peak value of local standard deviation is reduced from 8.57 to 2.39 for the Airbus A319 airliner with distance from 50.64km. Target's signal-to-clutter ratio increased from 4. 87 to 11. 22. This algorithm can effectively reduce the local standard deviation of image and is suitable for airborne infrared early warning system.
【作者单位】： 中国科学院长春光学精密机械与物理研究所中国科学院航空光学成像与测量重点实验室;中国科学院大学;中国科学院长春光学精密机械与物理研究所;
【基金】：国家自然科学基金(61308099)
【分类号】：TN215;TP391.41
，

本文编号：2028385