Paper
29 August 2016 Tone correction through a spherical color model
Tieling Chen, Jun Ma
Author Affiliations +
Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100334Y (2016) https://doi.org/10.1117/12.2244681
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China
Abstract
The paper introduces a new approach to tone correction of color images through a spherical color model. Although color changes more smoothly under the spherical model, some colors of the model cannot be displayed in the RGB color cube. The paper demonstrates the disadvantage does not affect the applications of the general techniques of tone correction in the spherical model. The achromatic component defined by the spherical model is separated from a given image with tonal imbalance, and then a tone correction function is performed on the component. The resulting achromatic component is combined with the original chromaticity to produce a tone corrected image. In the spherical color model, tone correction functions can be designed such that the corrected colors are within the RGB color cube for display. Technical requirements of the tone correction functions are discussed, and comparisons are made between the spherical color model and other similar color models including the commonly used HSV and HSL. Empirically, the effects of the general tone correction techniques in the spherical color model are close to those in the HSV color model.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tieling Chen and Jun Ma "Tone correction through a spherical color model", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100334Y (29 August 2016); https://doi.org/10.1117/12.2244681
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Cited by 1 scholarly publication.
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KEYWORDS
RGB color model

Spherical lenses

Image segmentation

Mathematical modeling

Visual process modeling

Visualization

Image processing

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