To improve the quality of the infrared image and enhance the information of the object,a dual band infrared image fusion method based on feature extraction and a novel multiple pulse coupled neural network(multi-PCNN)...To improve the quality of the infrared image and enhance the information of the object,a dual band infrared image fusion method based on feature extraction and a novel multiple pulse coupled neural network(multi-PCNN)is proposed.In this multi-PCNN fusion scheme,the auxiliary PCNN which captures the characteristics of feature image extracting from the infrared image is used to modulate the main PCNN,whose input could be original infrared image.Meanwhile,to make the PCNN fusion effect consistent with the human vision system,Laplacian energy is adopted to obtain the value of adaptive linking strength in PCNN.After that,the original dual band infrared images are reconstructed by using a weight fusion rule with the fire mapping images generated by the main PCNNs to obtain the fused image.Compared to wavelet transforms,Laplacian pyramids and traditional multi-PCNNs,fusion images based on our method have more information,rich details and clear edges.展开更多
简化和改进了脉冲耦合神经网络(PCNN),建立了基于时间索引图的脉冲耦合神经网络海冰 SAR 图像分类器,用于海冰 SAR 图像的分割和海冰分类。在此基础上建立了基于人工解译的半自动海冰分类判读系统。将发展的分类器用于辽东海湾冰探测,...简化和改进了脉冲耦合神经网络(PCNN),建立了基于时间索引图的脉冲耦合神经网络海冰 SAR 图像分类器,用于海冰 SAR 图像的分割和海冰分类。在此基础上建立了基于人工解译的半自动海冰分类判读系统。将发展的分类器用于辽东海湾冰探测,结果表明这个分类器能够区分海冰和海水,识别不同海冰类型,且具有高效率。为了选择适合辽东湾海冰分类的 PCNN 参数,分析了链接半径、链接强度和索引图等级等参数,给出了各参数合适的取值范围及调节原则。展开更多
基金Supported by the National Natural Science Foundation of China(60905012,60572058)
文摘To improve the quality of the infrared image and enhance the information of the object,a dual band infrared image fusion method based on feature extraction and a novel multiple pulse coupled neural network(multi-PCNN)is proposed.In this multi-PCNN fusion scheme,the auxiliary PCNN which captures the characteristics of feature image extracting from the infrared image is used to modulate the main PCNN,whose input could be original infrared image.Meanwhile,to make the PCNN fusion effect consistent with the human vision system,Laplacian energy is adopted to obtain the value of adaptive linking strength in PCNN.After that,the original dual band infrared images are reconstructed by using a weight fusion rule with the fire mapping images generated by the main PCNNs to obtain the fused image.Compared to wavelet transforms,Laplacian pyramids and traditional multi-PCNNs,fusion images based on our method have more information,rich details and clear edges.
文摘简化和改进了脉冲耦合神经网络(PCNN),建立了基于时间索引图的脉冲耦合神经网络海冰 SAR 图像分类器,用于海冰 SAR 图像的分割和海冰分类。在此基础上建立了基于人工解译的半自动海冰分类判读系统。将发展的分类器用于辽东海湾冰探测,结果表明这个分类器能够区分海冰和海水,识别不同海冰类型,且具有高效率。为了选择适合辽东湾海冰分类的 PCNN 参数,分析了链接半径、链接强度和索引图等级等参数,给出了各参数合适的取值范围及调节原则。
