SARBake Overlays for the MSTAR Dataset

Published: 8 August 2017| Version 3 | DOI: 10.17632/jxhsg8tj7g.3
David Malmgren-Hansen,


SARBake is an algorithm described in my first article "Convolutional Neural Networks for SAR Image Segmentation" co-authored by Morten Nobel-Jørgensen. The algorithm converts 3D CAD models of objects in to a label mask given the specific details about SAR viewing angles. The mask defines for every pixel whether the radar wave illuminated the object, the background or was in shadow. A good segmentation of a SAR image is very relevant as it simplifies image information. For example can object height above ground be estimated from the length of an objects shadow. An annotated image also enables the possibility of using Supervised Machine Learning techniques to create a segmentation mask automatically. If used in scientific publications we kindly ask for a citation of our article, @article{cnnforsegmentation, author = {David Malmgren-Hansen and Morten Nobel-Jørgensen}, title = {Convolutional Neural Networks for SAR Image Segmentation}, journal = {IEEE International Symposium on Signal Processing and Information Technology}, year = 2015 }



Annotation, Synthetic Aperture Radar Images, Segmentation