• Corpus ID: 229348751

HDR Denoising and Deblurring by Learning Spatio-temporal Distortion Models

@article{ogalan2020HDRDA,
  title={HDR Denoising and Deblurring by Learning Spatio-temporal Distortion Models},
  author={Ugur Çogalan and Mojtaba Bemana and Karol Myszkowski and Hans-Peter Seidel and Tobias Ritschel},
  journal={ArXiv},
  year={2020},
  volume={abs/2012.12009}
}
We seek to reconstruct sharp and noise-free high-dynamic range (HDR) video from a dual-exposure sensor that records different low-dynamic range (LDR) information in different pixel columns: Odd columns provide low-exposure, sharp, but noisy information; even columns complement this with less noisy, high-exposure, but motion-blurred data. Previous LDR work learns to deblur and denoise ( D ISTORTED → C LEAN ) supervised by pairs of C LEAN and D ISTORTED images. Regrettably, capturing D ISTORTED… 
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