Electronic Science and Technology ›› 2019, Vol. 32 ›› Issue (8): 61-65.doi: 10.16180/j.cnki.issn1007-7820.2019.08.013

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Aerial Image Reconstruction of Drone Based on GAN

CAO Kun,WU Fei,QIAN Xiaorui,YANG Zhaokun   

  1. School of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201600,China
  • Received:2018-08-13 Online:2019-08-15 Published:2019-08-12
  • Supported by:
    National Natural Science Foundation of China(61272097);Shanghai Municipal Committee of Science and Technology Project(13510501400);Shanghai Municipal Committee of Science and Technology Project(18511101600)


The amount of data transmitted during the traditional UAV acquisition and transmission process often resulted in high consumption of the UAV battery. Aiming at solving the problem, a CsRGAN model that combined super-resolution reconstruction and gray-scale image colorization was proposed. The low resolution grayscale image was reconstructed by generating a network: the image was first subjected to resolution amplification, color filling was performed, and then the image was corrected by the discriminator, and finally the image was reconstructed into a color high-definition image. The experimental results showed that under the fixed area, the model could reduce the transmission data of the drone aerial photography and improve the battery utilization of the drone under the condition of ensuring the imaging quality. These results proved the model had strong robustness.

Key words: UVA, super-resolution, image colorization, image reconstruction, GAN, fix area

CLC Number: 

  • TP391