摘要
Abstract
Nowadays IRFPA(infrared focal plane array)is the main trend in infrared system. Because of technique limitation, IRFPA can’t be as perfect as visible detectors. Nonuniformity has been the main defect of IRFPA for a long time. Many nonuniformity correction algorithms were developed in past decades, especially scene-based NUC algorithm. These algorithms remedy the defect of IRFPA largely. Up to now, every algorithm has its limitation and can’t solve the nonuniformity problem thoroughly. In this paper, several NUC algorithms in common use, include temporal high-pass filter algorithm, neural network algorithm, constant-statistics constrain algorithm and moving scene-based algorithm, are evaluated with sky, cloud, and water surface scenes, and comparative analysis is done with the results of these algorithms.关键词
红外焦平面阵列/非均匀性校正/时域高通滤波算法/神经网络算法/恒定统计量算法/空中场景/地面场景/算法仿真Key words
infrared focal plane array/nonuniformity correction/temporal high-pass filter algorithm/neural network algorithm/constant-statistics constrain algorithm/air field/surface field/algorithms simulation分类
信息技术与安全科学
