Color space conversion is the process of converting color values in an image from one color space to another. Color space conversion is challenging because different color spaces have different sized gamuts. For example, when converting an image encoded in a medium-sized color gamut (e.g., AdobeRGB or Display-P3) to a small color gamut (e.g., sRGB), color values may need to be compressed in a many-to-one manner (i.e., multiple colors in the source gamut will map to a single color in the target gamut). If we try to convert this sRGB-encoded image back to a wider gamut color encoding, it can be challenging to recover the original colors due to the color fidelity loss. We propose a method to address this problem by embedding wide-gamut metadata inside saved images captured by a camera. Our key insight is that in the camera hardware, a captured image is converted to an intermediate wide-gamut color space (i.e., ProPhoto) as part of the processing pipeline. This wide-gamut image representation is then saved to a display color space and saved in an image format such as JPEG or HEIC. Our method proposes to include a small sub-sampling of the color values from the ProPhoto image state in the camera to the final saved JPEG/HEIC image. We demonstrate that having this additional wide-gamut metadata available during color space conversion greatly assists in constructing a color mapping function to convert between color spaces. Our experiments show our metadata-assisted color mapping method provides a notable improvement (up to 60% in terms of E) over conventional color space methods using perceptual rendering intent. In addition, we show how to extend our approach to perform adaptive color space conversion based spatially over the image for additional improvements.
High Dynamic Range (HDR) and Wide Color Gamut (WCG) displays require adapted color measurements analysis. In this paper, we evaluate the viewing angle dependence of the color gamut and color volume of two HDR/WCG displays, one QLED TV and one OLED TV measured using a Fourier optics viewing angle system. The analysis is made using L*a*b* color space and ICtCp color space recently proposed by Dolby laboratories. The different interests of the ICtCp color space for direct comparison of the displays is discussed.
A new test target for defining the gamut boundary of a printing device is described, which results in a list of vertices on the boundary and the set of triangular faces that connect them. When used in conjunction with an ICC profile for the device in a procedure to compute the gamut volume, this target is shown to give highly-reproducible estimates independently of the CMM. A method of identifying irregularities in the gamut surface is described. Results are shown for a wide range of printers, both for conventional and digital ink-jet systems.
Colour gamuts can be described as a list of vertices and a list of triangular faces connecting these vertices. This method of encoding a colour gamut is convenient for both gamut mapping and gamut volume calculation. Particularly where the vertices describe a surface that is non-convex, as in most print processes, it can be difficult to obtain a face list that produces a connected and nonoverlapping surface. Methods for obtaining a face list from characterization data were evaluated using data from a wide range of printing processes, and it was found that defining a mesh and corresponding triangulation in CMYK space gave consistent results across all the data sets.
Different reproduction devices can have different sets of reproducible colours. These sets are called gamuts. The process of transforming colours from one device (or image) gamut to another is called gamut mapping. Gamut mapping has many technical issues to be considered: the used colour space, direction and magnitude of the mapping and whether and to which extent ingamut colours should be altered. Spatially invariant algorithms treat all the pixels independently on their position in the image. Spatially variant (local) algorithms allows a better rendition but introduces the problem of artefacts and/or haloing in the resulting image. In this paper we propose a spatially variant gamut mapping algorithm that creates virtually no artefacts nor haloing in the resulting image. We start from an analysis of the Retinex algorithm and devise proper functionals to build an algorithm which tries to maintain spatial ratios in the image while mapping it into the gamut and, at the same time, avoids all drawbacks of Retinex approaches. We suggest to perform the mapping in an RGB colour space rather than one of the perceptually more homogeneous ones. Although less homogeneous, we experimentally show that RGB colour spaces actually have better hue constancy according to a certain criterion.
This paper presents results of perceptible and acceptable ranges for color gamut change of transparent liquid crystal display (LCD) by luminous sources. Color gamut of transparent LCD can be changed by external luminous source because LCD cannot emit by itself. In this paper, perceptible and acceptable ranges to optimize color gamut for transparent LCD were found by psychophysical experiments. External luminous sources which have color temperatures of 3000, 5000 and 6500K were used. As a result, the differences of perceptible and acceptable ranges of color gamut using light sources are about 3% and 18% respectively. In addition, the differences of perceptible and acceptable range were investigated according to illuminance of external luminous. The difference of perceptible ranges does not affect the illuminance intensity. When the intensity of illuminance was high, the acceptable range was decreased than low illuminance. When the color gamut of transparent LCD has decreased within acceptable ranges, most observers can permit the image quality regardless of light source. In other words, transparent LCD which has somewhat narrow color gamut can be permitted.