| Popis: |
In view of the problem that the remote sensing image of UAV is greatly affected by the weather, this paper proposes a UAV remote sensing image enhancement technology based on improved GAN. Firstly, the noise feature is extracted by the noise feature extraction network based on convolutional neural network (CNN). Secondly, using the noise features extracted by CNNs, the generation of GAN for image enhancement is constructed. For the problem of large storage overhead, low computational efficiency and pixel block size limiting the size of the perceptual region, this paper introduces a full CNN model (FCN) as a generation network. Finally, a data set for training is constructed using image enhancement techniques based on damaged sample learning. The experimental results show that the enhanced algorithm in this paper shows excellent performance in remote sensing images of UAV. |
