Paper
10 February 2009 Improved colour to greyscale via integrability correction
Author Affiliations +
Proceedings Volume 7240, Human Vision and Electronic Imaging XIV; 72401B (2009) https://doi.org/10.1117/12.810290
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States
Abstract
The classical approach to converting colour to greyscale is to code the luminance signal as a grey value image. However, the problem with this approach is that the detail at equiluminant edges vanishes, and in the worst case the greyscale reproduction of an equiluminant image is a single uniform grey value. The solution to this problem, adopted by all algorithms in the field, is to try to code colour difference (or contrast) in the greyscale image. In this paper we reconsider the Socolinsky and Wolff algorithm for colour to greyscale conversion. This algorithm, which is the most mathematically elegant, often scores well in preference experiments but can introduce artefacts which spoil the appearance of the final image. These artefacts are intrinsic to the method and stem from the underlying approach which computes a greyscale image by a) calculating approximate luminance-type derivatives for the colour image and b) re-integrating these to obtain a greyscale image. Unfortunately, the sign of the derivative vector is sometimes unknown on an equiluminant edge and, in the current theory, is set arbitrarily. However, choosing the wrong sign can lead to unnatural contrast gradients (not apparent in the colour original). Our contribution is to show how this sign problem can be ameliorated using a generalised definition of luminance and a Markov relaxation.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark S. Drew, David Connah, Graham D. Finlayson, and Marina Bloj "Improved colour to greyscale via integrability correction", Proc. SPIE 7240, Human Vision and Electronic Imaging XIV, 72401B (10 February 2009); https://doi.org/10.1117/12.810290
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CITATIONS
Cited by 10 scholarly publications and 3 patents.
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KEYWORDS
Magnetic resonance imaging

Image compression

Sun

Image analysis

Visualization

Diffusion

Electronic imaging

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