DSM Refinement with Deep Encoder-Decoder Networks

Understand

3D city models can be generated from aerial images.

• However, the calculated DSMs suffer from noise, artefacts, and data holes that have to be manually cleaned up in a time-consuming process.
• This work presents an approach that automatically refines such DSMs.
• The key idea is to teach a neural network the characteristics of urban area from reference data.