Contours and contrast

dc.contributor.authorSmith, Kaleighen_US
dc.coverage.spatialUniversität des Saarlandes, Germanyen_US
dc.date.accessioned2015-01-21T06:49:08Z
dc.date.available2015-01-21T06:49:08Z
dc.date.issued2008-12-11en_US
dc.description.abstractContrast 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.en_US
dc.formatapplication/pdfen_US
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/8206
dc.languageEnglishen_US
dc.publisherSmith, Kaleighen_US
dc.titleContours and contrasten_US
dc.typeText.PhDThesisen_US
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