Non-uniformity seriously affects the imaging quality of infrared focal plane.To solve the problem,a non-uniformity correction algorithm is proposed based on the sub-pixel registration and the momentum-based BP neural network.Because of the shift of optical axis and imaging target location in the shortwave infrared camera,the sub-pixel registration algorithm based on matrix multiplication is used for registration.In order to accelerate the convergence of the algorithm,the two-point method is used to initialize the correction coefficient.As the BP neural network is easy to fall into the local optimal value,the correction effect is improved by increasing the momentum of the neural network method.The simulation results show that the proposed algorithm can eliminate the problems of ghost and edge blur in the traditional neural network correction method,obtain good correction effect and can improve the convergence speed of the algorithm,which provides a good foundation for short-wave infrared post-processing.
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徐全飞,冯旗.基于亚像素配准的神经网络非均匀性校正[J].激光与红外,2017,47(8):1033~1039 XU Quan-fei, FENG Qi. Non-uniformity correction algorithm based on sub-pixel registration and neural network[J]. LASER & INFRARED,2017,47(8):1033~1039