摘要
目前针对红外焦平面阵列(IRFPA)传统神经网络非均匀校正算法目标退化和收敛速度慢等问题,在综合分析传统神经网路相结合算法及基础上,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。该算法采用一点定标与神经网络相结合的方法,并对相应数据进行归一化以实现边缘清晰和收敛速度快等目的。仿真实验以及针对实际红外图像的实验结果表明,提出的方法是合理有效的。
Aiming at the problem of traditional neural network non-uniform correction algorithm such as target degradation and slow convergence for in- frared focal plane array（ IRFPA）, On the basis of comprehensive analysis advantages and disadvantages of traditional neural network algorithm in the non -uniformity correction ,an improved non-uniform of adaptive correction algorithm based on neural network is proposed. The algorithm adopts method combined one point correction with neural network,and normalizes corresponding data,which can realize clear edge and fast convergence speed. The com- parison experiment with simulated data and real IRFPA infrared data show that this seheme is effective.
出处
《电视技术》
北大核心
2013年第7期26-28,共3页
Video Engineering
基金
国家自然科学基金项目(61071196)
教育部新世纪优秀人才支持计划项目(NCET-10-0927)
信号与信息处理重庆市市级重点实验室建设项目(CSTC
2009CA2003)
重庆市自然科学基金项目(CSTC
2009BB2287
CSTC
2010BB2398
CSTC
2010BB2411)
