The paper addresses the problem of low quality 3D terrain models enhancement. We propose the approach based on convolutional neural networks (CNN), namely, on Pix2Pix method that uses generative adversarial networks for imageto-image translation. We use heightmap 3D terrain models representation to use classical CNNs. The network was trained on a synthetic dataset that included 150000 images and heightmaps of different landscapes. Our model showed the relative mean absolute difference equal to 0.459% on synthetic testing dataset. In addition, we demonstrate landscapes generation on the real data from Google Maps using our model.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.