Carlos Eduardo Rodríguez-Pardo

The Dark Side of CIELAB

Standardized in 1976 as a uniform color space, CIELAB is extensively utilized in color science and engineering applications. CIELAB provides both a color difference formula and correlates for common perceptual descriptors of color. Deficiencies in both areas are well-known, and based on these known limitations, numerous fixes have been developed yielding alternative color difference formulae that are derived as modifications of the color difference in CIELAB. In addition, several new color appearance spaces have also been proposed as modifications of the basic CIELAB framework. In this paper, we point out other, lesser-known and poorly-appreciated, limitations of CIELAB that occur particularly in the dark regions of color space. We demonstrate via examples, how these limitations not only cause performance compromises but lead to fundamental breakdowns in system optimization and design problems, making CIELAB unusable in these problems. We consider the reasons why these fundamental limitations were overlooked in the original development of CIELAB and analyze the mathematical representations contributing to the undesired behavior. We argue that fundamental new research is required to overcome this dark side of CIELAB; the development of uniform color spaces and new color appearance spaces must be revisited afresh using new experimental data and keeping in mind newer devices and applications.

Optimal gamut volume design for three primary and multiprimary display systems

Primary selection plays a fundamental role in display design. Primaries affect not only the gamut of colors the systems is able to reproduce, but also, they have an impact on the power consumption and other cost related variables. Using more than the traditional three primaries has been shown to be a versatile way of extending the color gamut, widening the angle view of LCD screens and improving power consumption of displays systems. Adequate selection of primaries requires a trade-off between the multiple benefits the system offers, the costs and the complexity it implies, among other design parameters. The purpose of this work is to present a methodology for optimal design for three primary and multiprimary display systems. We consider the gamut in perceptual spaces, which offer the advantage of an evaluation that correlates with human perception, and determine a design that maximize the gamut volume, constrained to a certain power budget, and analyze the benefits of increasing number of primaries, and their effect on other variables of performance like gamut coverage.

Primary selection for uniform display response

Traditional methodologies for primary selection usually consider the optimization of parameters that characterize the global performance of the display system, such as the luminance of the white point, gamut volume, and power consumption. We propose a methodology for primary design that optimizes a figure of merit designed to favor gamuts for which maximum luminance at each chromaticity is uniformly related to the corresponding maximum luminance over the set of optimal colors. We contrast the results obtained with the proposed methodology with those obtained by an alternative strategy based on the optimization of gamut volume, and analyze differences in performance between these approaches for both three and four primary systems. Results indicate that the global vs local design choices result in significantly different primary designs.

Pareto Optimal Primary Designs for Color Displays

The choice of primaries for a color display involves tradeoffs between different desirable attributes such as a large color gamut, high spectral reproduction accuracy, minimal observer metamerism, and low power consumption. Optimization of individual attributes often drives primary choices in different directions. For example, expansion of color gamut favors narrow spectral bandwidth saturated primaries and minimization of observer metamerism favors broadband primaries. To characterize the tradeoffs between the different attributes in primary design for three primary and multiprimary displays, we propose a Pareto optimization framework for determining the complete range of available primary choices that optimally negotiate the tradeoffs between the metrics for the different attributes. Using results obtained in our proposed framework, we explore the impact of number of primaries, the relation between alternative design objectives, and the underlying primary spectral characteristics. The proposed strategy is more informative and comprehensive for primary design and primary selection, and can also be extended to co-optimize primary design and selection of control values to fully leverage the advantages of multiprimary displays. Introduction The design of the spectral power distribution (SPD) of the primaries plays a critical role in color display systems. The choice of primaries determines the display gamut, i.e., the range of colors that the display can reproduce. For example, to maximize the (chromaticity) gamut, the chromaticities of the RGB primaries in the recent Rec. 2020 standard [1] are defined such that correspond approximately to spectrally-monochromatic primaries with wavelengths of 630nm, 532nm, and 467nm, respectively. An alternative strategy for realizing a wider gamut is to utilize more than three primaries, which is done in multiprimary displays. For both three primary and multiprimary color displays, other display metrics like luminance or power consumption also depend on the primaries’ characteristics, which means deliberate design is essential to construct practical display systems. Prior work has considered several different metrics for evaluating a set of display primaries. Going beyond the simplistic consideration of only the 2D gamut chromaticity area, several metrics have also been defined in terms of the SPDs of the primaries, and designs that optimize these metrics have also been obtained. Specifically, primary designs have been optimized for maximizing coverage of a pre-specified target gamut volume [2] or absolute gamut volume in a perceptually uniform color space [3]. For wide gamut designs based on narrow spectral bandwidth primaries, observer metamerism is often a concern, and designs have been proposed to optimize spectral reproduction [4] and minimize observer metamerism [5, 6, 7]. These prior works, however, focus on single objective to be optimized, and the question of how to adequately trade off these metrics against each other has received little attention. Primary designs have been proposed to mitigate the tradeoff between color gamut volume and optical power [8, 9], and between color gamut area and observer metamerism [7]. Alternatively an importance-weighted optimization has also been proposed [10], where the overall objective function for display primary design is formulated as a weighted sum of several metrics. However, the assignment of importance weights is empirical, and may be hard to set a priori without knowing the nature of the inter-relations between the different metrics. In this paper, we propose a multi-objective/Pareto optimization framework to investigate the optimal tradeoff relations among different display metrics. Instead of a single design optimizing a numerical metric quantifying a single display trait (or a weighted combination), the Pareto optimization framework characterizes the complete set of solutions for which none of the metrics quantifying the different traits can be improved upon without compromising performance of at least one of the other metrics. As a result, instead of optimizing a single trait while disregarding all others, the Pareto optimal solution space fully characterizes the range of available primary choices that optimally negotiate the tradeoffs between the different traits for color displays. Using results obtained in our proposed framework, we explore and quantify the impact of number of primaries and the relation between alternative design objectives. The proposed strategy is more informative and comprehensive for primary design and selection, and can also be extended to co-optimization of primary design and selection of control values to fully leverage the advantages of multiprimary displays. This paper is organized as follows. The next section lays the mathematical foundation for our problem setting by introducing spectral models for the display system and for object colors and their inter-relations via colorimetric/spectral reproduction objectives. Metrics quantifying the display attributes of color gamut coverage, power consumption, and observer metamerism, are then defined and the multi-objective optimization problem is formulated in terms of these metrics. The following section describes our implementation of the Pareto optimization framework using a parameterized representation of the primaries for computational efficiency. Results obtained using the framework are presented next where the nature of the optimal tradeoff relations and the underlying spectral properties of the primaries are discussed. As summary of the conclusions and a discussion of the results forms the final section. Preliminaries In this section, we introduce a spectral model for the display, the spectral representation for the surface colors that the display will attempt to reproduce, and corresponding color representations taking into account observer variability. Finally, we discuss the control process for the display by which the control values for the primaries are determined. 84 IS&T International Symposium on Electronic Imaging 2017 Color Imaging XXII: Displaying, Processing, Hardcopy, and Applications https://doi.org/10.2352/ISSN.2470-1173.2017.18.COLOR-040

An Interactive App for Color Deficient Viewers

Color deficient individuals have trouble seeing color contrasts that could be very apparent to individuals with normal color vision. For example, for some color deficient individuals, red and green apples do not have the striking contrast they have for those with normal color vision, or the abundance of red cherries in a tree is not immediately clear due to a lack of perceived contrast. We present a smartphone app that enables color deficient users to visualize such problematic color contrasts in order to help them with daily tasks. The user interacts with the app through the touchscreen. As the user traces a path around the touchscreen, the colors in the image change continuously via a transform that enhances contrasts that are weak or imperceptible for the user under native viewing conditions. Specifically, we propose a transform that shears the data along lines parallel to the dimension corresponding to the affected cone sensitivity of the user. The amount and direction of shear are controlled by the user’s finger movement over the touchscreen allowing them to visualize these contrasts. Using the GPU, this simple transformation, consisting of a linear shear and translation, is performed efficiently on each pixel and in real-time with the changing position of the user’s finger. The user can use the app to aid daily tasks such as distinguishing between red and green apples or picking out ripe bananas.

Two dimensional color calibration for four primary displays

The process to ensure a fixed and desired response from a color display generally consists of a per-channel calibration transform combined with a multi-dimensional characterization transformation. In this paper We focus on the former, i.e., the channel calibration. Conventional one-dimensional channel calibration strategies are inadequate for high resolution LCD displays because of inter-channel crosstalk. We address this problem by developing a color calibration strategy for a four primary LCD display, based on a two dimensional structure for channel calibration, which allows for simultaneously meeting the dual objectives of perceptual linearization of individual channels and gray balance along the device gray axes, despite inter-channel crosstalk. The two-dimensional nature of the transform represents a good balance between the dual objectives of low complexity and accurate control of key attributes of the displayed colors via channel calibration and experimental results demonstrate that the proposed scheme accomplishes its objectives offering a significant improvement over the per channel calibration for our four primary display system.

Dichromatic color perception in a two stage model: Testing for cone replacement and cone loss models

We formulate a two stage model of dichromatic color perception that consists of a first sensor layer with gain control followed by an opponent encoding transformation. We propose a method for estimating the unknown parameters in the model by utilizing pre-existing data from psychophysical experiments on unilateral dichromats. The model is validated using this existing data and by using predictions on known test images for detecting dichromacy. Using the model and analysis we evaluate the feasibility of cone loss and cone replacement hypotheses that have previously been proposed for modeling dichromatic color vision. Results indicate that the two stage model offers good agreement with test data. The cone loss and cone replacement models are shown to have fundamental limitations in matching psychophysical observations.

Multiobjective optimization for color display primary designs

Abstract. The choice of primaries for a color display involves tradeoffs among different desirable attributes, such as a large color gamut, high spectral reproduction accuracy, minimal observer metamerism, and low power consumption. Optimization of individual attributes often drives primary choices in different directions. For example, expansion of color gamut favors narrow spectral bandwidth saturated primaries, and minimization of observer metamerism typically favors broadband primaries. We propose a multiobjective optimization framework to characterize the tradeoffs among the different attributes for three-primary and multiprimary displays. Instead of a single design, the framework determines the complete range of available primary choices that optimally negotiate the tradeoffs among the metrics for the different attributes. Using results obtained in our proposed framework, we explore the impact of the number of primaries, the relation between alternative design objectives, and the underlying primary spectral characteristics. For primary design and primary selection, the proposed strategy is more informative and comprehensive than alternative single objective optimization approaches. Furthermore, within the proposed framework, we also consider alternative strategies for selection of control values for multiprimary displays and demonstrate that we can better leverage the advantages of multiprimary displays by selecting the control strategy to align with desired objectives. Specifically, observer metamerism is significantly reduced if control values are selected to explicitly optimize multiobserver tristimulus accuracy.

Multiprimary Display Color Calibration: A Variational Frame-work for Robustness to Device Variation

For multiprimary displays, color within the interior of the gamut can be reproduced with several different control values, a situation that is in contrast with the three primary scenario, where the control values are unique. For a given color, the selection of the control values, or color calibration, becomes a fundamental step for color rendition on multiprimary devices. Because spatially smooth variations in color are common in imagery and it is critical that despite device variations these be maintained as smooth variations in renditions, it is also desirable that the calibration strategy preserve smoothness of the device control values over color space. Based on this motivation, we propose a variational framework for color calibration of multiprimary displays that emphasizes smoothness by minimizing the squared norm of the gradient of the calibration function over the display gamut. We test our proposed methodology on a four primary system, and compare its performance with calibrations obtained from other standard methodologies. Results indicate that, compared with the alternatives, the proposed variational approach offers the smoothest variation in the control values over the entire color space and as a result also exhibits enhanced robustness in the presence of device variations.