Abstract: Firstly, based on the convolutional neural network, we proposed a remote sensing image fusion model that used crosslayer copy connection operations to fuse feature maps of different scales, and solved the problem that traditional remote sensing image fusion methods needed to manually select different decomposition and fusion rules for different types of remote sensing images, w
hich led to the problem that the fusion image quality was greatly affected by selected rules. Secondly, the effectiveness of the method was verified by the Deimos satellite and QuickBird satellite data, and the fusion image quality was evaluated by the subjective and objective methods. Experimental results show that the proposed model can effectively combine the spatial information of panchromatic image with the spectral information of multispectral image, and control the spectral distortion.

Key words: convolutional neural network,  , machine learning, computer application, remote sensing image fusion