Paper
7 June 2004 Decontouring: prevention and removal of false contour artifacts
Author Affiliations +
Proceedings Volume 5292, Human Vision and Electronic Imaging IX; (2004) https://doi.org/10.1117/12.526937
Event: Electronic Imaging 2004, 2004, San Jose, California, United States
Abstract
Contone imagery usually has eight bits per pixel for each of the three primaries in typical displays. However, there are often points in the imaging pipeline that constrain this number for cost reasons. Conversely, higher quality displays seek to achieve 9-10 bits/pixel/color, though there may be system bottlenecks limited at 8. In both cases, a goal is to achieve a higher perceived bit-depth quality than is afforded by the imaging system. The two main artifacts caused by reduced bitdepth are contouring and loss of low amplitude detail. Prevention of these distortions can be accomplished by applying a dithering process before the bit-depth limitation. A technique for achieving bit-depth extension via spatiotemporal dithering has been previously been presented [1]. In applications where it is only possible to affect the image after the bit-depth losses have already occurred, it is impossible to accurately restore the loss of low-amplitude detail. However, it is possible to remove the false contours. Of the several approaches used to remove false contours, we will discuss predictive cancellation and its dependence on the spatial frequency localization and masking properties of the visual system. We discuss the key visual properties that arose while investigating these two applications, which include the optical transfer function (OTF) of the eye, masking by noise, and contour integration.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Scott J. Daly and Xiaofan Feng "Decontouring: prevention and removal of false contour artifacts", Proc. SPIE 5292, Human Vision and Electronic Imaging IX, (7 June 2004); https://doi.org/10.1117/12.526937
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Cited by 71 scholarly publications and 10 patents.
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KEYWORDS
Visualization

Visual process modeling

Quantization

RGB color model

Image filtering

Visual system

LCDs

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