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1709.04881v1.pdf
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🔗 Source: arxiv.org
📊 Size: 22.41 MB
📄 Pages: 10 pages
⬇️ Downloads: 268

Summary

Researchers from the Pattern Recognition Lab and Multimedia Communications and Signal Processing at Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg, Germany, introduce the Super-Resolution Erlangen (SupER) database, a publicly available database of real low-resolution images with corresponding high-resolution ground truth data. The database comprises over 20,000 images from 14 scenes at four spatial resolution levels, captured using camera hardware binning to simulate real-world conditions. The team benchmarks 15 state-of-the-art single-image and multi-frame super-resolution (SR) algorithms using four full-reference quality measures, providing a comprehensive evaluation of SR techniques under realistic conditions. The study aims to address the lack of comparative validations of SR algorithms under practical conditions, where current studies often rely on simulated data or real data without ground truth.

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Researchers from the Pattern Recognition Lab and Multimedia Communications and Signal Processing at Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg,...

Technical Information

  • File Format: PDF
  • File Size: 22.41 MB
  • Pages: 10
  • Language: EN
  • Total Downloads: 268
  • Last Updated: 1 month ago

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