Big Heterogeneous Data Sensing and Processing in Computer Vision

01 March 2016 → 31 August 2019
Regional and community funding: Special Research Fund
Research disciplines
  • Natural sciences
    • Physical geography and environmental geoscience
  • Engineering and technology
    • Communications technology
    • Modelling
    • Multimedia processing
    • Biological system engineering
    • Signal processing
    • Geomatic engineering
Big Data Compressed sensing Signal recovery remote sensing Signal- and image processing
Project description

We focus on building a new information-theoretic framework in computer vision for sensing and analysis of Big Data by upgrading recent results from homogeneous to heterogeneous data types. This include extending the compressed sensing framework towards handling prior information, structured noise and erroneous measurements, and towards applications for improved image reconstruction and content analysis in biomedical and remote sensing applications.