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Gamut Mapping for Digital Cinema
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To ensure consistent presentation of wide gamut Digital Cinema Packages (DCPs) on standard gamut screens, a mandatory gamut mapping strategy has to be chosen. In this paper, current gamut mapping algorithms are evaluated with respect to their application in digital cinema. These algorithms include: "Simple Clip", "Cusp Clip", "Minimum delta E" (MindE), "Hue preserving MindE", "Weighted MindE" and the mapping strategy which is used in current projectors. The investigated gamut mapping algorithms will be provided as 3D lookup tables for comparison. These can also be used to retrofit a more advanced gamut mapping strategy to standard gamut projectors. Therefore, the paper closes with an analysis of the losses introduced by using 3D lookup tables for gamut mapping. The intent of this paper is to initiate a discussion about gamut mapping strategies for digital cinema, which may ultimately lead to an addendum to the SMPTE standards for digital cinema.
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... The color rendition quality is not satisfactory if we continuous to use the NTSC signal in a laser-based display directly [9]- [11]. Some works have been done for achieving high color quality by complex data processing method, which will result in long processing time and complex circuit [12]- [20]. ...
Laser-based displays can offer a wide color gamut to the viewers due to the narrow bandwidth of laser source, which is quite different from traditional display systems. Therefore, the color rendition standards for traditional displays are no longer suitable for laser-based displays. An optimized and practical color reproduction system is proposed and demonstrated for laser-based displays in this paper. Not only the three primary wavelengths (RGB) are well chosen by considering the luminance efficiency, color gamut and color matching function, but also the response function of camera system is optimized for a simplified color reproduction procedure. A remarkable high color rendition quality is presented in our experiment compared with traditional displays.
... The latest color appearance model, CIECAM02 [9], is believed to be the most accurate in predicting the appearance attributes, and is thought to be suitable for gamut mapping.[16] However, it has been reported that gamut mapping from wide-gamut digital cinema using CIECAM02 results in a significant hue discontinuity in the blue region.[17] One of the reasons for this is that even the latest color appearance model fails to predict the appearance attributes of saturated colors outside the psychophysical data from which the model was derived.[18] ...
With the advent of Recommendation ITU-R BT.2020 (Rec. 2020) color space for ultra-high definition television (UHDTV), the development of a gamut mapping algorithm for wide to standard gamuts is greatly needed. In wide-gamut UHDTV production, particularly under the assumption of simultaneous live UHDTV and high-definition television (HDTV) broadcast scenarios, real-time gamut mapping from UHDTV to HDTV is vital. Designing such an algorithm requires a careful consideration of the shape and size of significantly different gamuts. In this paper, we set some requirements for gamut mapping from UHDTV to HDTV, and propose a hue-preserved gamut mapping algorithm. The mapping paths are designed in the CIE 1976 L*a*b* (CIELAB) color space through modifications of the hue prediction based on our subjective experimental results on the constant perceived hue. To prevent an excessive chroma reduction, the lightness of the out-of-gamut colors is changed. The design process and mathematical expressions of our proposed gamut mapping algorithm are provided. In addition, we demonstrate the improvements in image quality.
This article presents an introductory review of color correction—a color remapping of image and video between different source and destination color spaces. The review specifically focuses on two main aspects of color remapping—primary color space conversion and gamut mapping—and outlines the requirements, algorithms, methods, and possible implementation options.
Ultrahigh-definition television (UHDTV) is a wide-color-gamut system, as standardized in Rec. ITU-R BT. 2020 and SMPTE ST 2036-1, that covers most real object colors and encompasses the gamuts of high-definition television (HDTV), Adobe RGB, and Digital Cinema Initiative Primary 3 (DCI-P3). The development of wide-gamut displays and high-quality gamut mapping is a major challenge in the workflow of UHDTV production today. While monochromatic light sources, such as lasers, are ideal for UHDTV wide-gamut displays, wide-gamut liquid crystal displays with nonmonochromatic backlight sources, such as quantum dot light-emitting diodes, may well be used from the viewpoint of both cost and performance. Furthermore, a highquality gamut mapping algorithm between UHDTV and HDTV for live broadcast production is essential. This paper offers solutions to these challenges.
With the advent of wide-gamut system colorimetry for ultra-high definition television, the development of a gamut mapping algorithm for wide to standard gamuts is greatly needed. Most gamut mapping techniques have been developed to retain the perceived hues of the source as predicted by a color appearance model. However, some color appearance models erroneously predict the saturated colors, generating a serious hue discontinuity in wide-color gamut mapping onto the Rec. 709 gamut boundary. This paper presents a heuristic approach to determining whether a color appearance model may create such artifacts when used in hue-preserved gamut mapping algorithms.
Laser light sources used in digital projectors have the potential to increase quality for several image parameters, including high brightness, dynamic range, and color space. This paper discusses advantages of laser illumination for digital projection, as well as considerations for the design of future cinema parameters such as luminance standards, high dynamic range projection, and a wider color space, including the practicality of the color space of The International Telecommunications Union Radiocommunication Sector Recommendation ITU-R BT.2020 (Rec. 2020)1 as a projection gamut. Practical concerns and limits of lasers are examined in the context of near-term implementations, and suggestions for future theater and projector design are discussed.
Computer Generated (CG) images on a CRT monitor cannot be accurately reproduced on a hardcopy output when the gamut of the CRT monitor exceeds that of the printer. Such cases require that the out-of-gamut colors be mapped inside the output device's gamut while preserving the appearance of original image as much as possible. This technique is called gamut mapping. While several gamut mapping techniques have been suggested for the natural images, 1-7 techniques for CG images 8-9 have rarely been discussed. In this paper, a three-dimensional gamut mapping technique for CG images is considered. A weighted color difference equation for lightness, chroma, and hue, along with normal CIE 1976 color difference equation 10 were used in the gamut mapping. Visual experiments were performed to evaluate the importance of these attributes in image appearance. Results showed that human visual system is most sensitive to lightness change, and least sensitive for chroma change. Surprisingly, for CG images, hue change was less noticeable than the lightness change.
We propose a numerical method to determine a transformation of a color space into a hue linear color space with a maximum degree of perceptual uniformity. In a first step, a transformation of the initial color space into a nearly perceptually uniform space is computed using multigrid optimization. In a second step, a hue correction is applied to the resulting color space while preserving the perceptual uniformity as far as possible. The two-stage transformation can be stored as a single lookup table for convenient usage in gamut map-ping applications. We evaluated our approach on the CIELAB color space using the CIEDE2000 color-difference formula as a measure of percep-tual uniformity and the Hung and Berns data as a reference of con-stant perceived hue. Our experiments show a mean disagreement of 5.0% and a STRESS index of 9.43 between CIEDE2000 color dif-ferences and Euclidean distances in the resulting hue linear color space. Comparisons with the hue linear IPT color space illustrate the performance of our method.
This series of articles on the color processing for digital cinema is based on the Engineering Guideline, SMPTE 432–1. The DC28 committee thought the information in that guideline would be more widely available if it were published as a series of articles in the SMPTE Journal. This second article in the series describes the reasons for choosing the constants 4095 and 52.37 in the Digital Cinema Distribution Master (DCDM) encoding and decoding equations and discusses white and black points.
CIECAM02 has been used to predict colour appearance under a wide range of viewing conditions, to quantify colour differences, to provide a uniform colour space and to provide a profile connection space for colour management. However, several problems have been identified with the CIECAM02. This talk is to present a new version of the CIECAM02 with the Hunt-Pointer-Estevez (HPE) matrix. The new version overcomes some problems and is simpler. The performance of the new version is verified.
It has been reported that CIECAM02, the appearance model standardized by the CIE to be used for imaging applications, contains a number of mathematical inconsistencies. These shortcomings cannot be solved easily without changing the behavior of the model and hence a fundamental redesign seems to be needed. At the moment, the main problems with CIECAM02 are known, but there is no clear strategy yet to fix the model. To have an idea about the impact of the inconsistencies of the currently standardized CIECAM02 model and several proposed corrections, the shortcomings are visualized for a number of color/illuminant combinations. From this visualization, a practical and natural approach is obtained to adjust the model without changing the mathematics drastically. © 2011 Wiley Periodicals, Inc. Col Res Appl, 38, 188–195, 2013.