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arXiv · 1903.03519

DSM Building Shape Refinement from Combined Remote Sensing Images based on Wnet-cGANs

Ksenia Bittner·Marco Körner·Peter Reinartz
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Abstract

We describe the workflow of a digital surface models (DSMs) refinement algorithm using a hybrid conditional generative adversarial network (cGAN) where the generative part consists of two parallel networks merged at the last stage forming a WNet architecture. The inputs to the so-called WNet-cGAN are stereo DSMs and panchromatic (PAN) half-meter resolution satellite images. Fusing these helps to propagate fine detailed information from a spectral image and complete the missing 3D knowledge from a stereo DSM about building shapes. Besides, it refines the building outlines and edges making them more rectangular and sharp.

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Ksenia Bittner, Marco Körner, Peter Reinartz. 2019-03-08. DSM Building Shape Refinement from Combined Remote Sensing Images based on Wnet-cGANs. https://arxiv.org/abs/1903.03519

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