Spectral Color Management in Virtual Reality Scenes
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sensors Article Spectral Color Management in Virtual Reality Scenes Francisco Díaz-Barrancas 1,* , Halina Cwierz 1 , Pedro J. Pardo 1 , Ángel Luis Pérez 2 and María Isabel Suero 2 1 Department of Computer and Network Systems Engineering, University of Extremadura, E06800 Mérida, Spain; [email protected] (H.C.); [email protected] (P.J.P.) 2 Department of Physics, University of Extremadura, E06071 Badajoz, Spain; [email protected] (Á.L.P.); [email protected] (M.I.S.) * Correspondence: [email protected] Received: 21 July 2020; Accepted: 28 September 2020; Published: 3 October 2020 Abstract: Virtual reality has reached a great maturity in recent years. However, the quality of its visual appearance still leaves room for improvement. One of the most difficult features to represent in real-time 3D rendered virtual scenes is color fidelity, since there are many factors influencing the faithful reproduction of color. In this paper we introduce a method for improving color fidelity in virtual reality systems based in real-time 3D rendering systems. We developed a color management system for 3D rendered scenes divided into two levels. At the first level, color management is applied only to light sources defined inside the virtual scene. At the second level, we applied spectral techniques over the hyperspectral textures of 3D objects to obtain a higher degree of color fidelity. To illustrate the application of this color management method, we simulated a virtual version of the Ishihara test for color blindness deficiency detection. Keywords: virtual reality; hyperspectral textures; Ishihara test; color fidelity 1. Introduction Technology is constantly evolving, offering possibilities that were previously unthinkable. This is the case for image sensors that allow us to capture the three spatial dimensions and the temporal dimension of the real world and virtually represent that real world through digital images, digital videos, and, in recent years, virtual and augmented reality devices. In all cases, color is an essential part of the virtual representation of the world using digital media. This is because the recipient of that representation is a human being. For humans, color is a fundamental part of the external information they receive from their environment through their senses. The sense of sight provides more than 80% of the information received by the brain through the senses [1]. The color information captured by imaging devices often requires processing techniques to ensure correct color reproduction on various digital devices. First, it is necessary to carry out a correct chromatic characterization of both the capture device and the reproduction device. In this way, it is possible to establish a biunivocal correspondence between the device-dependent color coordinates (typically RGB or CMYK) and the device-independent color coordinates (CIE XYZ or CIE Lab). Over the last few years, a multitude of studies have been carried out on the color characterization of devices, from CRTS and TFT technology to Near-Eye Displays [2–5]. The differences in the calibration and colorimetric characterization of a color display device are always confusing [6]. Calibration of these devices consists of setting the device’s state to a known value. This can be done by fixing the media’s white point, the gain, and the offset of each channel for a cathode ray tube, for example. This process ensures that the device produces consistent results and that the calibration process can be completed without any information on the relationship between the device’s Sensors 2020, 20, 5658; doi:10.3390/s20195658 www.mdpi.com/journal/sensors Sensors 2020, 20, 5658 2 of 16 Sensors 2020, 20, x 2 of 16 input coordinates and the colorimetric coordinates of the output. The colorimetric characterization of thecharacterization, device, however, the requires relationship this relationship between the to bedevi known.ce’s input From coordinates this characterization, (typically theRGB relationship values in betweendisplays theand device’s other device-indepen input coordinatesdent (typically coordinates RGB values(i.e., the in displaysCIE 1931 and XYZ other tristimulus device-independent value)) are coordinatesobtained. 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Figure 1. Simplified graphic representation of a lighting and shadowing method for rendering a 3D sceneFigure and 1. Simplified how the final graphic 2D image representation is generated of a [12 lighting]. and shadowing method for rendering a 3D scene and how the final 2D image is generated [12]. From a visual point of view, Virtual Reality (VR) technology is based on the generation of two differentFrom images a visual corresponding point of view, to Virt twoual di ffRealityerent views (VR) technology of the same is three-dimensional based on the generation scene. Oneof two of thesedifferent images images is shown corresponding to each eye,