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An Evaluation of Colour-to-Greyscale Image Conversion by Linear Anisotropic Diffusion and Manual Colour Grading

Barba, Aldo; Farup, Ivar; Pedersen, Marius
Journal article, Peer reviewed
Accepted version
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Barba (Locked)
URI
http://hdl.handle.net/11250/2632563
Date
2019
Metadata
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  • Institutt for datateknologi og informatikk [3866]
  • Publikasjoner fra CRIStin - NTNU [20804]
Original version
Final program and proceedings (Color and Imaging Conference). 2019, 69-74.   https://doi.org/10.2352/issn.2169-2629.2019.27.13
Abstract
In the paper "Colour-to-Greyscale Image Conversion by Linear Anisotropic Diffusion of Perceptual Colour Metrics", Farup et al. presented an algorithm to convert colour images to greyscale. The algorithm produces greyscale reproductions that preserve detail derived from local colour differences in the original colour image. Such detail is extracted by using linear anisotropic diffusion to build a greyscale reproduction from a gradient of the original image that is in turn calculated using Riemannised colour metrics. The purpose of the current paper is to re-evaluate one of the psychometric experiments for these two methods (CIELAB L* and anisotropic Δ99) by using a flipping method to compare their resulting images instead of the side by side method used in the original evaluation. In addition to testing the two selected algorithms, a third greyscale reproduction was manually created (colour graded) using a colour correction software commonly used to process motion pictures. Results of the psychometric experiment found that when comparing images using the flipping method, there was a statistically significant difference between the anisotropic Δ99 and CIELAB L* conversions that favored the anisotropic method. The comparison between Δ99 conversion and the manually colour graded image also showed a statistically significant difference between them, in this case favoring the colour graded version.
Publisher
Society for Imaging Science and Technology
Journal
Final program and proceedings (Color and Imaging Conference)

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