Infrared and visible image fusion method based on convolutional neural network
Aiming at the problems of the current infrared and visible image fusion methods such as poor fusion effect and low efficiency,in order to obtain better infrared and visible image fusion results,an infrared and visible im-age fusion method based on convolution neural network is proposed.First,collect the infrared and visible images to be fused,use the Retinex algorithm to enhance the image brightness and detail information,then use the convolution neu-ral network to extract the image fusion features,and design the infrared and visible image fusion rules,and get the im-age fusion results according to the rules.Finally,conduct the infrared and visible image fusion performance test on multiple data sets,and the results show that the image fusion of convolutional neural network has good overall visual effect,rich details,more than 6 values of entropy and average gradient,and the fusion time is less than 1 s.The over-all performance is better than its infrared and visible image contrast fusion method.
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