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Contours and Contrast


Smith,  Kaleigh
Computer Graphics, MPI for Informatics, Max Planck Society;
International Max Planck Research School, MPI for Informatics, Max Planck Society;

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Smith, K. (2008). Contours and Contrast. PhD Thesis, Universität des Saarlandes, Saarbrücken. doi:10.22028/D291-26103.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0027-B5AF-4
Contrast in photographic and computer-generated imagery communicates colour and
lightness differences that would be perceived when viewing the represented
scene. Due to depiction constraints, the amount of displayable contrast is
limited, reducing the image�s ability to accurately represent the scene. A
local contrast enhancement technique called unsharp masking can overcome these
constraints by adding high-frequency contours to an image that increase its
apparent contrast. In three novel algorithms inspired by unsharp masking,
specialized local contrast enhancements are shown to overcome constraints of a
limited dynamic range, overcome an achromatic palette, and to improve the
rendering of 3D shapes and scenes. The Beyond Tone Mapping approach restores
original HDR contrast to its tone mapped LDR counterpart by adding
highfrequency colour contours to the LDR image while preserving its luminance.
Apparent Greyscale is a multi-scale two-step technique that first converts
colour images and video to greyscale according to their chromatic lightness,
then restores diminished colour contrast with high- frequency luminance
contours. Finally, 3D Unsharp Masking performs scene coherent enhancement by
introducing 3D high-frequency luminance contours to emphasize the details,
shapes, tonal range and spatial organization of a 3D scene within the rendering
pipeline. As a perceptual justification, it is argued that a local contrast
enhancement made with unsharp masking is related to the Cornsweet
illusion, and that this may explain its effect on apparent contrast.