KEYWORDS: Visual process modeling, Data modeling, Colorimetry, Color vision, High dynamic range imaging, Color reproduction, Reverse modeling, Digital imaging, Light sources and illumination, Visual system
Color science is a multidisciplinary field with broad applications in industries such as digital imaging, coatings and textiles, food, lighting, archiving, art, and fashion. Accurate definition and measurement of color appearance is a challenging task that directly affects color reproduction in such applications. Color Appearance Models addresses those challenges and offers insight into the preferred solutions. Extensive research on the human visual system (HVS) and color vision has been performed in the last century, and this book contains a good overview of the most important and relevant literature regarding color appearance models.
A new EOTF based on human perception, called PQ (Perceptual Quantizer), was proposed in a previous work (SMPTE Mot. Imag. J 2013, 122:52-59) and its performance was evaluated for a wide range of luminance levels and encoding bitdepth values. This paper is an extension of that previous work to include the color aspects of the PQ signal encoding. The efficiency of the PQ encoding and bit-depth requirements were evaluated and compared for standard color gamuts of Rec 709 (SRGB), and the wide color gamuts of Rec 2020, P3, and ACES for a variety of signal representations as RGB, YC<sub>b</sub>C<sub>r</sub>, and XYZ. In a selected color space for any potential local gray level 26 color samples were simulated by deviating one quantization step from the original color in each signal dimension. The quantization step sizes were simulated based on the PQ and gamma curves for different bit-depth values and luminance ranges for each of the color gamut spaces and signal representations. Color differences between the gray field and the simulated color samples were computed using CIE DE2000 color difference equation. The maximum color difference values (quantization error) were used as a metric to evaluate the performance of the corresponding EOTF curve. Extended color gamuts were found to require more bits to maintain low quantization error. Extended dynamic range required fewer additional bits in to maintain quantization error. Regarding the visual detection thresholds, the minimum bit-depth required by the PQ and gamma encodings are evaluated and compared through visual experiments.
Many art objects have a size much larger than their softcopy reproductions. In order to develop a multiscale model that
accounts for the effect of image size on image appearance, a digital projector and LCD display were colorimetrically
characterized and used in a contrast matching experiment. At three different sizes and three levels of contrast and
luminance, a total of 63 images of noise patterns were rendered for both displays using three cosine log filters. Fourteen
observers adjusted mean luminance level and contrast of images on the projector screen to match the images displayed
on the LCD. The contrasts of the low frequency images on the screen were boosted while their mean luminance values
were decreased relative to the smaller LCD images. Conversely, the contrast of projected high frequency images were
reduced for the same images on LCD with a smaller size. The effect was more pronounced in the matching of projected
image to the smaller images on the LCD display. Compared to the mean luminance level of the LCD images, a reduction
of the mean luminance level of the adjusted images was observed for low frequency noise patterns. This decrease was
more pronounced for smaller images with lower contrast and high mean luminance level.