基于区域校正的大面阵红外探测器非均匀性校正方法

通过分析某大面阵红外探测器的响应特性,发现了由于相机自身特性引发的不同区域的响应非线性问题.传统的两点校正法或非线性曲线拟合办法对该大面阵探测器校正后,校正残差和目视效果都比较差.本文根据探测器的非线性响应特性,将整个面阵分成了8个区域分别进行非线性拟合校正,然后校正各个区域的偏置系数,最后利用改进的BP神经网络非均匀...

Non-uniformity Correction for Large Format Array Infrared Detectors Based on Regional Correction

By analyzing the response characteristics of large-format infrared detectors,we found that the response nonlinearity in different areas is caused by the characteristics of the camera itself.After the traditional two-point correction method or nonlinear curve fitting method corrects the large-format array detector,the correction residuals and visual effects are relatively poor.In this study,on the basis of eliminating blind elements,according to the nonlinear response characteristics of the detector,the entire array is divided into eight regions for nonlinear fitting correction,the bias coefficient of each region was corrected,and the non-uniformity correction algorithm of the BP neural network was used to deal with the non-uniformity problem caused by region division.After correction,the residual non-uniformity of each black body temperature point image was on the order of one-thousandth,the spatial noise was already very close to or smaller than the temporal noise,and the local residual non-uniformity reached below 0.002,which was significantly smaller than the temporal noise.