ing at the problem that the fused results of low resolution source images are not good for the subsequent target extraction, a multi-band image synchronous super-resolution and fusion method based on Wasserstein generative adversarial network with gradient penalty (WGAN-GP) is proposed. Firstly, the multi-band low-resolution source images are enlarged to the target size respectively based on the bicubic interpolation method. Secondly, the enlarged results are input to a feature extraction (encoding) network to extract features respectively and combine them in a high-level feature space. Then, the initial fused images are reconstructed by decoding network. Finally, a high-resolution fused image is obtained through a dynamic game between the generator and the discriminator. The experimental results show that the proposed method can not only achieve multi-band images super-resolution and fusion simultaneously, but also the information amount, clarity, and visual quality of the fused images are significantly higher than other representative methods.
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