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Uniform color appearance model for color reproduction in graphic art.

机译：用于图形艺术中色彩还原的统一色彩外观模型。

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This dissertation proposes a new color appearance model for color reproduction applications in graphic arts called the Uniform Color Appearance Model (UCAM). UCAM incorporates a simplified chromatic adaptation transformation with a generalized tonal reproduction and color correction; in addition, UCAM includes a capability that accounts for changes in media and viewing conditions. An expanded Munsell color space is applied to calculate the metrics of lightness, chroma, hue, and color difference, as well as manipulate color in a perceptually uniform manner.; The algorithms to establish the new model are discussed. These algorithms include the simplified chromatic adaptation transformation, the generalized tonal reproduction and color correction, the Munsell color space expansion, and the color conversion for the Munsell color space.; Three experiments are designed and conducted to evaluate UCAM and its algorithms. The first experiment tests the chromatic adaptation transformation and color correction algorithm across various viewing conditions. The second experiment tests the uniformity of the Munsell color space for hue reproduction. The third experiment visually compares UCAM against the CIELAB and CIELUV models by using transparency-to-print color reproductions of three natural images.; Experiment results are as follows: first, UCAM produces a better fit to the test data for chromatic adaptation and a significant better fit to the test data for adapting level change than other tested models. Second, UCAM reproduces hues like their originals in the perceptual (Munsell) hue. However, the hues could be quite different when comparing to CIELAB and CIELUV models, especially the blue of CIELAB and the red of CIELUV. Finally, UCAM reproduces images closer to their originals than those of CIELAB and CIELUV models particularly for images with saturated colors.
机译：本文提出了一种新的用于图形艺术中色彩再现的色彩外观模型，称为统一色彩外观模型（UCAM）。 UCAM结合了简化的色彩适应变换和广义的音调再现和色彩校正。此外，UCAM还具有解决媒体变化和观看条件的功能。应用扩展的Munsell色彩空间来计算亮度，色度，色相和色差的度量，并以感知上统一的方式处理色彩。讨论了建立新模型的算法。这些算法包括简化的色彩适应变换，广义的色调再现和色彩校正，孟塞尔色彩空间扩展以及孟塞尔色彩空间的色彩转换。设计并进行了三个实验以评估UCAM及其算法。第一个实验在各种观看条件下测试了色彩适应转换和色彩校正算法。第二个实验测试了孟塞尔色彩空间用于色相再现的均匀性。第三个实验通过使用透明打印三个自然图像的彩色复制品，在视觉上将UCAM与CIELAB和CIELUV模型进行比较。实验结果如下：首先，与其他测试模型相比，UCAM可以更好地拟合测试数据以进行色彩适应，并且可以显着更好地拟合测试数据以适应电平变化。其次，UCAM在感性（蒙塞尔）色相中复制其原始色相。但是，与CIELAB和CIELUV模型相比，色相可能会有很大不同，尤其是CIELAB的蓝色和CIELUV的红色。最后，与CIELAB和CIELUV模型相比，UCAM再现的图像更接近原始图像，特别是对于色彩饱和的图像。

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