| CFNN在多传感器图像数据融合中的应用 |
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| 引用本文： | 苏金泷.CFNN在多传感器图像数据融合中的应用[J].哈尔滨工业大学学报,2009,41(3):205-208. |
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| 作者姓名： | 苏金泷 |
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| 作者单位： | 同济大学,电子与信息工程学院,上海,200092;泉州师范学院,陈守仁工商信息学院仰恩大学,计算机与信息学院,福建,泉州,362014
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| 基金项目： | 福建省教育厅科技项目 |
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| 摘 要： | 提出一种补偿模糊理论和神经网络的混合系统(CFNN),并将其应用于多传感器数据融合,力图以此提高多传感器图像数据融合算法的性能.CFNN混合系统引入了模糊神经元,使网络既能适当调整输入、输出模糊隶属函数,又能借助于补偿逻辑算法动态地优化模糊推理,大大提高了网络的容错性、稳定性和训练速度.文中介绍了图像数据融合的数学模型,并详细阐述了CFNN图像数据融合算法.仿真实验证明,CFNN图像融合算法能显著提高图像数据融合质量.
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| 关 键 词： | CFNN 传感器 图像数据融合 像素级融合 |
Application of CFNN in multi-sensor image data fusion |
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| SU Jin-long.Application of CFNN in multi-sensor image data fusion[J].Journal of Harbin Institute of Technology,2009,41(3):205-208. |
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| Authors: | SU Jin-long |
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| Affiliation: | SU Jin-long1,2,3(1.School of Electronics and Information,Tongji University,Shanghai 200092,China;2.TSL School of Business and Information Technology,Quanzhou Normal University,Quanzhou 362000,China;3.Yang En University,School of Information and Computer Science,Quanzhou,362014,China) |
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| Abstract: | A method of fuzzy optimization design combining neural networks and compensation cells is presented as a new method of image processing,and is applied to multi-sensor image data fusion.The fault tolerance,stability and working speed of the network are improved greatly due to the introduction of fuzzy neuron,which can make the network appropriately adjust the input and output of fuzzy membership functions,and optimize the fuzzy inference dynamically according to the logic compensation algorithm.The mathematical model and CFNN image data fusion are illustrated.Simulation results show that the algorithm designed by this method can significantly improve the fusion of multi-sensor,and is a practical and effective method in multi-sensor data fusion. |
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| Keywords: | CFNN |
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