dc.contributor.author | Farup, Ivar | |
dc.contributor.author | Pedersen, Marius | |
dc.contributor.author | Alsam, Ali | |
dc.date.accessioned | 2019-03-20T07:54:11Z | |
dc.date.available | 2019-03-20T07:54:11Z | |
dc.date.created | 2018-11-28T15:07:35Z | |
dc.date.issued | 2018 | |
dc.identifier.isbn | 978-1-5386-5645-7 | |
dc.identifier.uri | http://hdl.handle.net/11250/2590739 | |
dc.description.abstract | We present an algorithm for conversion of colour images to greyscale. The underlying idea is that local perceptual colour differences in the colour image should translate into local differences in greylevel in the greyscale image. This is obtained by constructing a gradient for the greyscale image from the eigenvalues and eigenvectors of the structure tensor of the colour image, which, in turn, is computed by means of perceptual colour difference metrics. The greyscale image is then constructed from the gradient by means of linear anisotropic diffusion, where the diffusion tensor is constructed from the same structure tensor. By means of psychometric experiments, it is found that the algorithm gives the most accurate image reproduction when used with the ΔE99 colour metric, and that it performs at the level of, or better than, other state-of-the-art spatial algorithms. Surprisingly, the only algorithm that can compete in terms of accuracy is a simple luminance map computed as the L* channel of the image represented in the CIELAB colour space. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | nb_NO |
dc.relation.ispartof | 2018 Colour and Visual Computing Symposium (CVCS); 19th and 20th September, 2018, Gjøvik, Norway | |
dc.title | Colour-to-greyscale image conversion by linear anisotropic diffusion of perceptual colour metrics | nb_NO |
dc.title.alternative | Colour-to-greyscale image conversion by linear anisotropic diffusion of perceptual colour metrics | nb_NO |
dc.type | Chapter | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.identifier.doi | 10.1109/CVCS.2018.8496651 | |
dc.identifier.cristin | 1636536 | |
dc.description.localcode | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | nb_NO |
cristin.unitcode | 194,63,10,0 | |
cristin.unitname | Institutt for datateknologi og informatikk | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |