Testing uniform colour spaces using colour differences of a wide colour gamut.

An experimental dataset, WCG, was assembled. The set includes 416 pairs of samples that surround 28 colour centres and covers a wide colour gamut. The data were used to test the performance of seven colour-difference models, CIELAB, CIEDE2000, CAM16-UCS, DIN99d, OSAGP, and ICTCP, Jzazbz. Colour discrimination ellipses were also fitted to compare the uniformity of the colour spaces. Different versions of the models were derived to improve the fit to the data, including parametric factors, kL, kC, and a power factor. It was found that the kL optimised CAM16-UCS, DIN99d, OSAGP models significantly outperformed the other colour models. In addition, the magnitude of the colour difference had an impact on visual assessment.

Color difference evaluation for wide-color-gamut displays.

With the emerging demand for wide-color-gamut displays, an issue has been raised in which the commonly used color difference formulae or uniform color spaces that were derived based on the data produced in the relatively smaller color gamut could be unreliable for predicting color differences in the highly saturated color regions. A psychophysical experiment was carried out for evaluating color difference at a luminance level of 310cd/m2 on a wide-color-gamut display with an approximate DCI-P3 color gamut. Twelve color centers were selected to cover the entire gamut boundary. There were 192 pairs of samples over 12 color centers judged by 18 observers using the greyscale psychophysical method. The data set was used to test the performance of six uniform color spaces and color difference equations, CIELAB, CIEDE2000, CAM02-UCS, Jzazbz, ICTCP, and nICTCP, a newly revised ICTCP formula. The color discrimination ellipses were used to test local and global uniformity of color spaces and compared with previous studies. The results revealed that all formulae improved their performance to have a mean lightness parametric factor of about 0.5. CAM02-UCS significantly outperformed the others in overall, local, and global uniformity. The high-quality visual data set is recommended to evaluate or to derive color difference formulae for WCG applications in the future.

Hue linearity of color spaces for wide color gamut and high dynamic range media.

Hue linearity is an important property of uniform color spaces such that hues perceived to be similar should be located on a straight line, an iso-hue line, in that space. Previously derived hue linearity data only cover a limited color gamut. Two new psychophysical experiments were conducted that used a wide color gamut (WCG) and high dynamic range (HDR) display to extend the color range using both hue matching and unitary hue estimation methods. The new data were used to evaluate the CIELAB, CAM16-UCS, IPT, and Jzazbz uniform color spaces. The experimental results indicated that IPT and Jzazbz outperformed the other two, especially in the blue region. The same method was used to test these spaces using the other published data sets. The results from different data sets gave similar results. Finally, all results were combined to form a normalized data set to represent the data under HDR and WCG display conditions. Furthermore, the four unitary hue data can be used to develop or refine color appearance models.

Color gamut mapping between small and large color gamuts: part II. gamut extension.

A wide color gamut (WCG) display has great color rendering capability and offers the opportunity to achieve a pleasing and realistic appearance in terms of image quality. To take full advantage of the large display gamut, a new gamut extension algorithm (GEA) is proposed based on a new color appearance scale, vividness. The performance of the new GEA was investigated via a psychophysical experiment together with five commonly used GEAs. In addition, two different uniform color spaces (UCSs) were also studied including the CAM02-UCS color space and a space, Jzazbz, designed for high dynamic range (HDR) and WCG applications. The results showed that the newly proposed GEA, i.e. the vividness-extension (VE) algorithm, outperformed all the other GEAs and the Jzazbz space was a promising UCS for evaluating gamut extension.

Colour gamut mapping between small and large colour gamuts: Part I. gamut compression.

This paper describes an investigation into the performance of different gamut compression algorithms (GCAs) in different uniform colour spaces (UCSs) between small and large colour gamuts. Gamut mapping is a key component in a colour management system and has drawn much attention in the last two decades. Two new GCAs, i.e. vividness-preserved (VP) and depth-preserved (DP), based on the concepts of 'vividness' and 'depth' are proposed and compared with the other commonly used GCAs with the exception of spatial GCAs since the goal of this study was to develop an algorithm that could be implemented in real time for mobile phone applications. In addition, UCSs including CIELAB, CAM02-UCS, and a newly developed UCS, Jzazbz, were tested to verify how they affect the performance of the GCAs. A psychophysical experiment was conducted and the results showed that one of the newly proposed GCAs, VP, gave the best performance among different GCAs and the Jzazbz is a promising UCS for gamut mapping.