IVCVMay 21, 2021

Helsinki Deblur Challenge 2021: description of photographic data

arXiv:2105.10233v14 citations
Originality Synthesis-oriented
AI Analysis

This provides a standardized dataset for researchers and practitioners working on image deblurring, though it is incremental as it builds on existing benchmarking efforts.

The paper introduces a photographic dataset for the Helsinki Deblur Challenge 2021, containing pairs of sharp and blurred images to test and benchmark image deblurring algorithms.

The photographic dataset collected for the Helsinki Deblur Challenge 2021 (HDC2021) contains pairs of images taken by two identical cameras of the same target but with different conditions. One camera is always in focus and produces sharp and low-noise images the other camera produces blurred and noisy images as it is gradually more and more out of focus and has a higher ISO setting. Even though the dataset was designed and captured with the HDC2021 in mind it can be used for any testing and benchmarking of image deblurring algorithms. The data is available here: https://doi.org/10.5281/zenodo.477228

Foundations

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