基于神经网络的红外焦平面非均匀性自适应校正算法
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TN911.73

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国家自然科学基金(60377034)资助项目


ADAPTIVE NON-UNIFORMITY CORRECTION ALGORITHM FOR IRFPA BASED ON NEURAL NETWORK
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    摘要:

    由于材料、工艺等原因,红外焦平面阵列(IRFPA)各单元普遍存在响应不一致的现象。从而导致IRFPA都存在非均匀性.非均匀性校正(NUC)是红外图像处理系统中的重要环节.本文在研究了传统的基于神经网络的NUC算法的基础上,提出了一种改进的基于神经网络的非均匀性自适应校正算法。并对比了传统的基于神经网络的算法和本文算法的校正效果和收敛速度,实验表明本文提出的算法校正效果好,收敛速度快.

    Abstract:

    Due to being influenced by detectors' material,related manufacturing technology etc,every detection element's responsivity of infrared focal plane arrays(IRFPA) is different,which results in non-uniformity of IRFPA.So non-uniformity correction(NUC) is an important technique for IRFPA.The traditional NUC algorithms based on neural network were analyzed in this study.And a new improved NUC algorithm based on neural network was presented. A comparison was made to these algorithms.Experiments results show that the algorithm proposed in this study prevails over other algorithms based on neural network in correction effective and convergence speed.

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王炳健 刘上乾 赖睿 李庆.基于神经网络的红外焦平面非均匀性自适应校正算法[J].红外与毫米波学报,2006,25(6):405~407]. WANG Bing-Jian, LIU Shang-Qian, LAI Rui, LI Qing. ADAPTIVE NON-UNIFORMITY CORRECTION ALGORITHM FOR IRFPA BASED ON NEURAL NETWORK[J]. J. Infrared Millim. Waves,2006,25(6):405~407.]

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  • 收稿日期:2005-09-27
  • 最后修改日期:2006-06-01
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