dc.contributor.author | Pedersen, Marius | |
dc.contributor.author | Amirshahi, Seyed Ali | |
dc.date.accessioned | 2022-03-28T10:23:51Z | |
dc.date.available | 2022-03-28T10:23:51Z | |
dc.date.created | 2022-01-05T08:03:29Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Color and Imaging Conference (CIC). 2021, 258-263. | en_US |
dc.identifier.issn | 2166-9635 | |
dc.identifier.uri | https://hdl.handle.net/11250/2987896 | |
dc.description.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>. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Society for Imaging Science and Technology | en_US |
dc.title | Colourlab Image Database: Geometric Distortions | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.rights.holder | This version of the article will not be available due to copyright restrictions by Society for Imaging Science and Technology | en_US |
dc.source.pagenumber | 258-263 | en_US |
dc.source.journal | Color and Imaging Conference (CIC) | en_US |
dc.identifier.doi | 10.2352/issn.2169-2629.2021.29.258 | |
dc.identifier.cristin | 1974818 | |
dc.relation.project | Norges forskningsråd: 324663 | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |