文件名称:Multiseural
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Multisensor image fusion has its effective utilization for surveillance.
In this paper, we utilize a pulse coupled neural network method to merge images
different sensors, in order to enhance visualization for surveillance. On the
basis of standard mathematical model of pulse coupled neural network, a novel
step function is adopted to generate pulses. Subjective and objective image
fusion performance measures are introduced to assess the performance of image
fusion schemes. Experimental results show that the image fusion method using
pulse coupled neural network is effective to merge images different
sensor-Multisensor image fusion has its effective utilization for surveillance.
In this paper, we utilize a pulse coupled neural network method to merge images
different sensors, in order to enhance visualization for surveillance. On the
basis of standard mathematical model of pulse coupled neural network, a novel
step function is adopted to generate pulses. Subjective and objective image
fusion performance measures are introduced to assess the performance of image
fusion schemes. Experimental results show that the image fusion method using
pulse coupled neural network is effective to merge images different
sensor
In this paper, we utilize a pulse coupled neural network method to merge images
different sensors, in order to enhance visualization for surveillance. On the
basis of standard mathematical model of pulse coupled neural network, a novel
step function is adopted to generate pulses. Subjective and objective image
fusion performance measures are introduced to assess the performance of image
fusion schemes. Experimental results show that the image fusion method using
pulse coupled neural network is effective to merge images different
sensor-Multisensor image fusion has its effective utilization for surveillance.
In this paper, we utilize a pulse coupled neural network method to merge images
different sensors, in order to enhance visualization for surveillance. On the
basis of standard mathematical model of pulse coupled neural network, a novel
step function is adopted to generate pulses. Subjective and objective image
fusion performance measures are introduced to assess the performance of image
fusion schemes. Experimental results show that the image fusion method using
pulse coupled neural network is effective to merge images different
sensor
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Multisensor Image Fusion Using a Pulse Coupled Neural.pdf