Helsinki Deblur Challenge 2021: description of photographic data
Markus Juvonen, Samuli Siltanen, Fernando Silva de Moura

TL;DR
The paper describes a photographic dataset created for the Helsinki Deblur Challenge 2021, comprising paired sharp and blurred images under varying focus and noise conditions, intended for benchmarking image deblurring algorithms.
Contribution
It introduces a novel dataset with paired images captured under controlled conditions, facilitating the evaluation of deblurring methods.
Findings
Dataset includes diverse focus and noise conditions.
Provides a benchmark for deblurring algorithm performance.
Accessible for research and testing purposes.
Abstract
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
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Taxonomy
TopicsAdvanced Image Processing Techniques · Digital Media Forensic Detection · Image and Signal Denoising Methods
