Dr.-Ing. Claas Grohnfeldt


Claas       Tel:      +49-8153-28-4075 (DLR)
      Fax:     +49-8153-28-1420 (DLR)
      Room:  2040 (DLR-EOC)
      E-mail: claas.grohnfeldt[at]dlr.de
      More information:

Curriculum Vitae

  • Since 07.2017, Senior Research Scientist, DLR & TUM-SiPEO
  • 03.2016 - 06.2017, Research Scientist, DLR & TUM-SiPEO
  • 03.2012 - 02.2016, PhD Research Fellow, DLR & Munich Aerospace e.V.
  • 06.2012 - 08.2012, Participant, Space Studies Program, International Space University, NASA KSC & FIT, Florida, USA
  • 02.2011 - 09.2011, Master's Thesis Student, Daimler AG (Mercedes Cars) Group Research & MCG Development
  • 04.2010 - 01.2011, Student Research Assistant, Group Optimization & Optimal Control, University of Bremen
  • 02.2009 - 04.2010, Student Software Module Developer, ESA-ESTEC, The Netherlands, & Centre of Industrial Mathematics, University of Bremen
  • 07.2009 - 10.2009, Intern, Airbus Defense and Space
  • 09.2008 - 06.2009, Studies in Mathematics (Erasmus Scholar), University of Warwick, England
  • 10.2006 - 02.2012, Master's (Diploma) Studies in Applied Mathematics, University of Bremen


  • IEEE IGARSS Best Paper Award (2016)
  • DLR Science Slam competition, First Prize (2013)
  • Munich Aerospace full Ph.D. research scholarship (2012)
  • ESA Scholarship for ISU Space Studies Program (2012)
  • Erasmus Scholarship for exchange studies at the University of Warwick, England (2008)

Reseach Interests

  • Machine/deep learning for computer vision and remote sensing.
  • Multi-sensor data fusion, image super-resolution and decurrption, data completion
  • High performance computing and sparse reconstruction.
  • Aerial and satellite-based Earth observation
  • Optical, hyperspectral and SAR remote sensing.

Key Publications

  • Grohnfeldt, C., Schmitt, M. and Zhu, X. (2018). A conditional generative adversarial network to fuse SAR and multispectral optical data for cloud removal from Sentinel-2 images. In: Proc. IGARSS, Valencia, Spain. in press.
  • Grohnfeldt C. (2017): Multi-sensor Data Fusion for Multi- and Hyperspectral Resolution Enhancement Based on Sparse Representations. Ph.D. Dissertation. Technische Universität München.
  • Yokoya N., Grohnfeldt C., Chanussot J. (2017): Hyperspectral and Multispectral Data Fusion: A comparative review of the recent literature. IEEE Geoscience and Remote Sensing Magazine 5 (2): 29–56.
  • Zhu X. X., Grohnfeldt C., Bamler R. (2016): Exploiting Joint Sparsity for Pansharpening: The J-SparseFI Algorithm. IEEE Transactions on Geoscience and Remote Sensing 54 (5): 2664-2681.
  • Grohnfeldt C., Zhu X. X. (2015): Towards a combined sparse representation and unmixing based hybrid hyperspectral resolution enhancement method. IEEE International Geoscience and Remote Sensing Symposium, 2872–2875.
  • Grohnfeldt C., Burns T. M., Zhu X. X. (2015): Dictionary Learning Strategies for Sparse Representation Based Hyperspectral Image Enhancement. Proceedings of the 7th IEEE Workshop on Hyperspectral Image and Signal Processing, IEEE Xplore, Tokyo, Japan, 1-4.
  • Grohnfeldt C., Zhu X. X., Bamler R. (2014): The J-SparseFI-HM Hyperspectral Resolution Enhancement Method - Now Fully Automated. Proceedings of the 6th IEEE Workshop on Hyperspectral Image and Signal Processing, IEEE Xplore, Lausanne, Switzerland, 1-4.
  • Grohnfeldt C., Zhu X. X., Bamler R. (2013): Jointly sparse fusion of hyperspectral and multispectral imagery. IEEE International Geoscience and Remote Sensing Symposium, 4090–4093.

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