Ship Classification by the Fusion of Panchromatic Image and Multi-spectral Image Based on Pseudo Siamese LightweightNetwork

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The current rapid development of the remote sensing satellite industry provides a large amount of image data for ship classification tasks. Aiming at the problem of insufficient feature extraction of single source image, this paper designs a lightweight ship classification model based on the fusion of panchromatic image and multispectral image of pseudo Siamese network to extract image features more fully. First, establish a multi-source remote sensing image ship target classification dataset MPFS (MS and PAN Ship image Fusion Classification Dataset); secondly, send panchromatic images and multispectral images to the network through different convolutional layers, thendesign a multi-level feature extraction network for panchromatic images and an adaptive feature extraction network for spectral imagesrespectively; finally, concatenate the features along the channel dimension and send them to the classification network.