170 citations · 358 across the 12 of their papers we have counts for
5 papers · 1 filter
Fusion of TanDEM-X and Cartosat-1 Elevation Data Supported by NeuralNetwork-Predicted Weight Maps
Hossein Bagheri, Michael Schmitt, Xiao Xiang Zhu
Recently, the bistatic SAR interferometry mission TanDEM-X provided a global terrain map with unprecedented accuracy. However, visual inspection and empirical assessment of TanDEM-…
A Framework for SAR-Optical Stereogrammetry over Urban Areas
Hossein Bagheri, Michael Schmitt, Pablo d'Angelo +1
Currently, numerous remote sensing satellites provide a huge volume of diverse earth observation data. As these data show different features regarding resolution, accuracy, coverag…
Fusion of Urban TanDEM-X raw DEMs using variational models
Hossein Bagheri, Michael Schmitt, Xiao Xiang Zhu
Recently, a new global Digital Elevation Model (DEM) with pixel spacing of 0.4 arcseconds and relative height accuracy finer than 2m for flat areas (slopes < 20%) and better than 4…
The SEN1-2 Dataset for Deep Learning in SAR-Optical Data Fusion
Michael Schmitt, Lloyd Haydn Hughes, Xiao Xiang Zhu
While deep learning techniques have an increasing impact on many technical fields, gathering sufficient amounts of training data is a challenging problem in remote sensing. In part…
Towards Automatic SAR-Optical Stereogrammetry over Urban Areas using Very High Resolution Imagery
Chunping Qiu, Michael Schmitt, Xiao Xiang Zhu
In this paper we discuss the potential and challenges regarding SAR-optical stereogrammetry for urban areas, using very-high-resolution (VHR) remote sensing imagery. Since we do th…