Neural Network Non-uniformity Correction Method for IRFPA Based on Median Filtering
基于中值滤波的红外焦平面阵列非均匀性神经网络校正

Since the traditional neural network non-uniformity correction algorithm has lower convergence speed and lower correction precision, it is more difficult to obtain satisfactory correction result when high background noise is present. For this reason, a neural network method for correcting the non-uniformity of an infrared focal plane array (IRFPA) based on median filtering is proposed. In the method, the median filtering is first used to preprocess the high noise and then an improved neural network algorithm is used to correct the non-uniformity of the IRFPA adaptively. The experimental result shows that the algorithm has higher convergence speed and higher correction precision than the traditional method and can make the peak signal to noise ratio be improved by 10dB at least.