Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

Effect of selected luminescent layers on CCT, CRI, and response times

Phosphors have been used as wavelength converters in illumination for many years. When it is excited with blue light, the frequently used yttrium aluminium garnet doped with cerium (YAG:Ce) phosphor converts a part of blue light to a wideband yellow light, resulting in the generated light having a white color. By combining an appropriate concentration of the YAG:Ce phosphor and blue excitant light, white light of a desired correlated color temperature (CCT) can be obtained. However, this type of illumination has a lower color rendering index value (CRI). In an attempt to improve the CRI value, we mixed the YAG:Ce phosphor with europium-doped calcium sulfide phosphor (CaS:Eu), which resulted in a considerably increased CRI value. This article examines an experiment with luminescent layers consisting of a mixture of selected phosphors and polydimethylsiloxane (PDMS). Different thicknesses in these layers were achieved by changing the speed of rotation during their accumulation onto laboratory glass using the method of spin coating. The spectral characteristics of these luminescent layers as they were excited with blue light emitting diode (LED) and laser diode (LD) were then determined. A suitable combination of the YAG:Ce phosphor with a phosphor containing europium, as it was excited with a blue LED, yielded a source of white light with a CRI value of greater than 85. The response time in the tested luminescent layers to a rectangular excitant impulse (generated by a signal generator and transmitted by LD) was also measured in order to examine their potential use in visible light communications (VLC).Web of Science1213art. no. 209

Characteristics of flight simulator visual systems

The physical parameters of the flight simulator visual system that characterize the system and determine its fidelity are identified and defined. The characteristics of visual simulation systems are discussed in terms of the basic categories of spatial, energy, and temporal properties corresponding to the three fundamental quantities of length, mass, and time. Each of these parameters are further addressed in relation to its effect, its appropriate units or descriptors, methods of measurement, and its use or importance to image quality

Color science of nanocrystal quantum dots for lighting and displays

Cataloged from PDF version of article.Colloidal nanocrystals of semiconductor quantum dots (QDs) are gaining prominence among the optoelectronic materials in the photonics industry. Among their many applications, their use in artificial lighting and displays has attracted special attention thanks to their high efficiency and narrow emission band, enabling spectral purity and fine tunability. By employing QDs in color-conversion LEDs, it is possible to simultaneously accomplish successful color rendition of the illuminated objects together with a good spectral overlap between the emission spectrum of the device and the sensitivity of the human eye, in addition to a warm white color, in contrast to other conventional sources such as incandescent and fluorescent lamps, and phosphor-based LEDs, which cannot achieve all of these properties at the same time. In this review, we summarize the color science of QDs for lighting and displays, and present the recent developments in QD-integrated LEDs and display research. First, we start with a general introduction to color science, photometry, and radiometry. After presenting an overview of QDs, we continue with the spectral designs of QD-integrated white LEDs that have led to efficient lighting for indoor and outdoor applications. Subsequently, we discuss QD color-conversion LEDs and displays as proof-of-concept applications - a new paradigm in artificial lighting and displays. Finally, we conclude with a summary of research opportunities and challenges along with a future outlook

Parametric effects on the evaluation of threshold chromaticity differences using red printed samples

This paper was published in JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: https://doi.org/10.1364/JOSAA.36.000510. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law.[EN] Results from different authors showed deviations of radial orientation in the a*-b* plane (tilt) for the major axes of chromaticity-discrimination ellipses centered around the International Commission on Illumination (CIE) red color center [Color Res. Appl. 3, 149 (1978)], which are not considered by most of the current advanced color-difference formulas (e.g., CIEDE2000). We performed a visual experiment using red printed samples in order to test the influence of the separation between samples (gap) on the mentioned tilt. Our results confirm a counterclockwise tilt of fitted a*-b* ellipses with a magnitude of approximately 36 degrees for samples with no separation, which is similar to that detected by other authors, and a reduction of the mentioned tilt owing to the separation of the samples. We detected a tilt of approximately 22 degrees for samples with a black gap of 0.5 mm and a tilt of approximately 25 degrees for samples with a white gap of 3 mm. Notably, the uncertainty of previous values given by the corresponding credibility intervals of 95% posterior probability is approximately +/- 8 degrees of the mean values. Finally, we study the performance of the most widely used color-difference formulas in the graphic arts sector using our current experimental results, and conclude that the performance of the CAM02-SCD and CAM02-UCS color-difference formulas is significantly better than that of the CIEDE2000 formula.Brusola Simón, F.; Tortajada Montañana, I.; Jorda-Albiñana, B.; Melgosa, M. (2019). Parametric effects on the evaluation of threshold chromaticity differences using red printed samples. Journal of the Optical Society of America A. 36(4):510-517. https://doi.org/10.1364/JOSAA.36.000510S510517364Melgosa, M. (2007). Request for existing experimental datasets on color differences. Color Research & Application, 32(2), 159-159. doi:10.1002/col.20300Luo, M. R., Cui, G., & Rigg, B. (2001). The development of the CIE 2000 colour-difference formula: CIEDE2000. Color Research & Application, 26(5), 340-350. doi:10.1002/col.1049Luo, M. R., & Rigg, B. (1986). Chromaticity-discrimination ellipses for surface colours. Color Research & Application, 11(1), 25-42. doi:10.1002/col.5080110107Alman, D. H., Berns, R. S., Snyder, G. D., & Larsen, W. A. (1989). Performance testing of color-difference metrics using a color tolerance dataset. Color Research & Application, 14(3), 139-151. doi:10.1002/col.5080140308Berns, R. S., Alman, D. H., Reniff, L., Snyder, G. D., & Balonon-Rosen, M. R. (1991). Visual determination of suprathreshold color-difference tolerances using probit analysis. Color Research & Application, 16(5), 297-316. doi:10.1002/col.5080160505Witt, K. (1999). Geometric relations between scales of small colour differences. Color Research & Application, 24(2), 78-92. doi:10.1002/(sici)1520-6378(199904)24:23.0.co;2-mMelgosa, M., Hita, E., Poza, A. J., Alman, D. H., & Berns, R. S. (1997). Suprathreshold color-difference ellipsoids for surface colors. Color Research & Application, 22(3), 148-155. doi:10.1002/(sici)1520-6378(199706)22:33.0.co;2-rIndow, T., Robertson, A. R., Von Grunau, M., & Fielder, G. H. (1992). Discrimination ellipsoids of aperture and simulated surface colors by Matching and paired comparison. Color Research & Application, 17(1), 6-23. doi:10.1002/col.5080170106Xu, H., & Yaguchi, H. (2005). Visual evaluation at scale of threshold to suprathreshold color difference. Color Research & Application, 30(3), 198-208. doi:10.1002/col.20106Huang, M., Liu, H., Cui, G., Luo, M. R., & Melgosa, M. (2012). Evaluation of threshold color differences using printed samples. Journal of the Optical Society of America A, 29(6), 883. doi:10.1364/josaa.29.000883Wen, S. (2012). A color difference metric based on the chromaticity discrimination ellipses. Optics Express, 20(24), 26441. doi:10.1364/oe.20.026441Huang, M., Liu, H., Cui, G., & Luo, M. R. (2011). Testing uniform colour spaces and colour-difference formulae using printed samples. Color Research & Application, 37(5), 326-335. doi:10.1002/col.20689Rich, R. M., Billmeyer, F. W., & Howe, W. G. (1975). Method for deriving color-difference-perceptibility ellipses for surface-color samples. Journal of the Optical Society of America, 65(8), 956. doi:10.1364/josa.65.000956MacAdam, D. L. (1942). Visual Sensitivities to Color Differences in Daylight*. Journal of the Optical Society of America, 32(5), 247. doi:10.1364/josa.32.000247Witt, K. (1995). Cie guidelines for coordinated future work on industrial colour-difference evaluation. Color Research & Application, 20(6), 399-403. doi:10.1002/col.5080200609García, P. A., Huertas, R., Melgosa, M., & Cui, G. (2007). Measurement of the relationship between perceived and computed color differences. Journal of the Optical Society of America A, 24(7), 1823. doi:10.1364/josaa.24.001823Guan, S.-S., & Luo, M. R. (1999). Investigation of parametric effects using small colour differences. Color Research & Application, 24(5), 331-343. doi:10.1002/(sici)1520-6378(199910)24:53.0.co;2-9Montag, E. D., & Wilber, D. C. (2002). A comparison of constant stimuli and gray-scale methods of color difference scaling. Color Research & Application, 28(1), 36-44. doi:10.1002/col.10112Strocka, D., Brockes, A., & Paffhausen, W. (1983). 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Visual determination of hue suprathreshold tolerances

A visual experiment was performed to generate suprathreshold tolerances sampling the direction of CIELAB hue, thereby extending the RIT-Dupont dataset. Thirty nine color centers including three complete hue circles at different lightness or chroma levels and three CIE recommended colors (red, green, blue) were evaluated for hue discrimination. Forty five observers participated in the pass/fail experiments. A total of 32,226 visual observations were made. The statistical method, logit analysis with 3-dimensional normit function, was used to determine the hue discrimination suprathreshold for each color center. The results indicated that the hue discrimination suprathresholds of observers varied with hue angle. The suprathreshold also increased with the chroma position of a given color center. The results were compared with current color-difference formulae, CMC, BFD and CIE94. A mathematical equation was derived from the present dataset

High Dynamic Range (HDR) Display Perception

Displays have undergone a huge development in the last several decades. From cathode-ray tube (CRT), liquid crystal display (LCD), to organic light-emitting diode (OLED), even Q-OLED, the new configurations of the display bring more and more functions into industry and daily life. In the recent several years, high dynamic range (HDR) displays become popular. HDR displays usually refer to that the black level of the display is darker and the peak being brighter compared with the standard dynamic range (SDR) display. Traditionally, the peak luminance level can be used as the white in characterization and calibration. However, for HDR displays, the peak luminance is higher than the traditional diffuse white level. Exploration of the perceptual diffuse white in HDR image when presented in displays is proposed, which can be beneficial to the characterizing and the optimizing the usage of the HDR display. Moreover, in addition to the ``diffuse white , 3D color gamut volume can be calculated in some specific color appearance models. Calculation and modeling of the 3D color gamut volume can be very useful for display design and better characterizing display color reproduction capability. Furthermore, the perceptional color gamut volume can be measured through psychophysical experiments. Comparison between the perceptional color gamut volume and the theoretical 3D gamut volume calculations will reveal some insights for optimizing the usage of HDR displays. Another advantage of the HDR display is its darker black compared with the SDR display. Compared with the real black object, what level of black is `perfect\u27 enough in displays? Experiments were proposed and conducted to evaluate that if the HDR display is capable of showing ``perfect black for different types of background images/patterns. A glare-based model was proposed to predict the visual ``perfect black. Additionally, the dynamic range of human vision system is very large. However, the simultaneous dynamic range of human vision system is much smaller and is important for the fine tuning usage of HDR displays. The simultaneous dynamic range was measured directly for different stimulus sizes. Also, it was found that the simultaneous dynamic range was peak luminance level dependent. A mathematical model was proposed based on the experimental data to predict the simultaneous dynamic range. Also the spatial frequency effect of the target pattern on the simultaneous dynamic range was measured and modeled. The four different assessments about HDR displays perception would provide experimental data and models for a better understanding of HDR perception and tuning of the HDR display