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Colourlab Image Database: Geometric Distortions

Pedersen, Marius; Amirshahi, Seyed Ali
Peer reviewed, Journal article
Published version
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Pedersen (Locked)
URI
https://hdl.handle.net/11250/2987896
Date
2021
Metadata
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  • Institutt for datateknologi og informatikk [4881]
  • Publikasjoner fra CRIStin - NTNU [26591]
Original version
Color and Imaging Conference (CIC). 2021, 258-263.   10.2352/issn.2169-2629.2021.29.258
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>.
Publisher
Society for Imaging Science and Technology
Journal
Color and Imaging Conference (CIC)
Copyright
This version of the article will not be available due to copyright restrictions by Society for Imaging Science and Technology

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