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Volume: 29 | Article ID: art00042
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Colourlab Image Database: Geometric Distortions
  DOI :  10.2352/issn.2169-2629.2021.29.258  Published OnlineNovember 2021
Abstract

Over the years, a high number of different objective image quality metrics have been proposed. While some image quality metrics show a high correlation with subjective scores provided in different datasets, there still exists room for improvement. Different studies have pointed to evaluating the quality of images affected by geometrical distortions as a challenge for current image quality metrics. In this work, we introduce the Colourlab Image Database: Geometric Distortions (CID:GD) with 49 different reference images made specifically to evaluate image quality metrics. CID:GD is one of the first datasets which include three different types of geometrical distortions; seam carving, lens distortion, and image rotation. 35 state-ofthe-art image quality metrics are tested on this dataset, showing that apart from a handful of these objective metrics, most are not able to show a high performance. The dataset is available at <ext-link ext-link-type="url" xlink:href="http://www.colourlab.no/cid">www.colourlab.no/cid</ext-link>.

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Marius Pedersen, Seyed Ali Amirshahi, "Colourlab Image Database: Geometric Distortionsin Proc. IS&T 29th Color and Imaging Conf.,  2021,  pp 258 - 263,  https://doi.org/10.2352/issn.2169-2629.2021.29.258

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Copyright © Society for Imaging Science and Technology 2021
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