Television Colorimetry Elements
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Package 'Colorscience'
Package ‘colorscience’ October 29, 2019 Type Package Title Color Science Methods and Data Version 1.0.8 Encoding UTF-8 Date 2019-10-29 Maintainer Glenn Davis <[email protected]> Description Methods and data for color science - color conversions by observer, illuminant, and gamma. Color matching functions and chromaticity diagrams. Color indices, color differences, and spectral data conversion/analysis. License GPL (>= 3) Depends R (>= 2.10), Hmisc, pracma, sp Enhances png LazyData yes Author Jose Gama [aut], Glenn Davis [aut, cre] Repository CRAN NeedsCompilation no Date/Publication 2019-10-29 18:40:02 UTC R topics documented: ASTM.D1925.YellownessIndex . .5 ASTM.E313.Whiteness . .6 ASTM.E313.YellownessIndex . .7 Berger59.Whiteness . .7 BVR2XYZ . .8 cccie31 . .9 cccie64 . 10 CCT2XYZ . 11 CentralsISCCNBS . 11 CheckColorLookup . 12 1 2 R topics documented: ChromaticAdaptation . 13 chromaticity.diagram . 14 chromaticity.diagram.color . 14 CIE.Whiteness . 15 CIE1931xy2CIE1960uv . 16 CIE1931xy2CIE1976uv . 17 CIE1931XYZ2CIE1931xyz . 18 CIE1931XYZ2CIE1960uv . 19 CIE1931XYZ2CIE1976uv . 20 CIE1960UCS2CIE1964 . 21 CIE1960UCS2xy . 22 CIE1976chroma . 23 CIE1976hueangle . 23 CIE1976uv2CIE1931xy . 24 CIE1976uv2CIE1960uv . 25 CIE1976uvSaturation . 26 CIELabtoDIN99 . 27 CIEluminanceY2NCSblackness . 28 CIETint . 28 ciexyz31 . 29 ciexyz64 . 30 CMY2CMYK . 31 CMY2RGB . 32 CMYK2CMY . 32 ColorBlockFromMunsell . 33 compuphaseDifferenceRGB . 34 conversionIlluminance . 35 conversionLuminance . 36 createIsoTempLinesTable . 37 daylightcomponents . 38 deltaE1976 -
Applying CIECAM02 for Mobile Display Viewing Conditions
Applying CIECAM02 for Mobile Display Viewing Conditions YungKyung Park*, ChangJun Li*, M. R. Luo*, Youngshin Kwak**, Du-Sik Park **, and Changyeong Kim**; * University of Leeds, Colour Imaging Lab, UK*, ** Samsung Advanced Institute of Technology, Yongin, South Korea** Abstract Small displays are widely used for mobile phones, PDA and 0.7 Portable DVD players. They are small to be carried around and 0.6 viewed under various surround conditions. An experiment was carried out to accumulate colour appearance data on a 2 inch 0.5 mobile phone display, a 4 inch PDA display and a 7 inch LCD 0.4 display using the magnitude estimation method. It was divided into v' 12 experimental phases according to four surround conditions 0.3 (dark, dim, average, and bright). The visual results in terms of 0.2 lightness, colourfulness, brightness and hue from different phases were used to test and refine the CIE colour appearance model, 0.1 CIECAM02 [1]. The refined model is based on continuous 0 functions to calculate different surround parameters for mobile 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 displays. There was a large improvement of the model u' performance, especially for bright surround condition. Figure 1. The colour gamut of the three displays studied. Introduction Many previous colour appearance studies were carried out using household TV or PC displays viewed under rather restricted viewing conditions. In practice, the colour appearance of mobile displays is affected by a variety of viewing conditions. First of all, the display size is much smaller than the other displays as it is built to be carried around easily. -
Computational Color Harmony Based on Coloroid System
Computational Aesthetics in Graphics, Visualization and Imaging (2005) L. Neumann, M. Sbert, B. Gooch, W. Purgathofer (Editors) Computational Color Harmony based on Coloroid System László Neumanny, Antal Nemcsicsz, and Attila Neumannx yGrup de Gràfics de Girona, Universitat de Girona, and Institució Catalana de Recerca i Estudis Avançats, ICREA, Barcelona, Spain zBudapest University of Technology and Economics, Hungary xInstitute of Computer Graphics and Algorithms, Vienna University of Technology, Austria [email protected], [email protected], [email protected] (a) (b) Figure 1: (a) visualization of the overall appearance of a dichromatic color set with `caleidoscope' option of the Color Plan Designer software and (b) interactive color selection of a dichromatic color set in multi-layer mode, applying rotated regular grid. Abstract This paper presents experimentally based rules and methods for the creation of harmonic color sets. First, dichro- matic rules are presented which concern the harmony relationships of two hues. For an arbitrarily given hue pair, we define the just harmonic saturation values, resulting in minimally harmonic color pairs. These values express the fuzzy border between harmony and disharmony regions using a single scalar. Second, the value of harmony is defined corresponding to the contrast of lightness, i.e. the difference of perceptual lightness values. Third, we formulate the harmony value of the saturation contrast, depending on hue and lightness. The results of these investigations form a basis for a unified, coherent dichromatic harmony formula as well as for analysis of polychromatic color harmony. Introduced color harmony rules are based on Coloroid, which is one of the 5 6 main color-order systems and − furthermore it is an aesthetically uniform continuous color space. -
Color Space Conversion
L Technical Color Space Information Conversion The role of color space conversion in the process of scanning and reproduc- ing a color image begins the moment an image is captured by a scanner and continues through the point at which it is output on film. For the purpose of this article we will discuss conversions between three types of color systems: RGB, CIE, and CMYK. The RGB (Red, Green, & Blue) and CMYK (Cyan, Magenta, Yellow, & Black) color models have been described in greater detail in the Linotype-Hell Technical information piece entitled Color in Printing. For some background information on the CIE (Commission Internationale de l’Eclairage), please refer to Color Spaces and PostScript Level 2. CIE as a reference color space Most scanners acquire color in the form of RGB data. The majority of non- photographic printing methods employ CMYK inks or toners. In a closed sys- tem, where the characteristics of both the scanner and the printing method are well-defined, conversions may be made from RGB to CMYK through tables that maintain a reasonable level of color consistency. The process becomes somewhat more difficult as you add monitors, other scanners, proofing devices or printing processes that have different characteristics. It becomes critical to have a consistent yardstick, if you will, a means of con- verting between different color systems (and back again) without a loss in color fidelity. This is what CIE provides. Let’s start with some background on CIE, and then we will look at how it can be applied in an open system. Measuring color Light reflected off of, or transmitted through a colored object can be mea- sured by the wavelengths of light that are reflected or transmitted. -
Package 'Colorspace'
Package ‘colorspace’ February 15, 2013 Version 1.2-1 Date 2013-01-24 Title Color Space Manipulation Description Carries out mapping between assorted color spaces including RGB, HSV, HLS, CIEXYZ, CIELUV, HCL (polar CIELUV),CIELAB and po- lar CIELAB. Qualitative, sequential, and diverging color palettes based on HCL colors are provided. Depends R (>= 2.10.0), methods Suggests KernSmooth, MASS, kernlab, mvtnorm, vcd, tcltk, dichromat License BSD LazyData yes Author Ross Ihaka [aut], Paul Murrell [aut], Kurt Hornik [aut], Jason C. Fisher [aut], Achim Zeileis [aut, cre] Maintainer Achim Zeileis <[email protected]> Repository CRAN Date/Publication 2013-01-24 14:59:08 NeedsCompilation yes R topics documented: choose_palette . .2 color-class . .3 coords . .4 desaturate . .5 hex..............................................6 hex2RGB . .7 HLS.............................................8 1 2 choose_palette HSV.............................................9 LAB............................................. 10 LUV............................................. 11 mixcolor . 12 polarLAB . 13 polarLUV . 14 rainbow_hcl . 15 readhex . 18 readRGB . 19 RGB............................................. 20 sRGB ............................................ 21 USSouthPolygon . 22 writehex . 22 XYZ............................................. 23 Index 25 choose_palette Graphical User Interface for Choosing HCL Color Palettes Description A graphical user interface (GUI) for viewing, manipulating, and choosing HCL color palettes. Usage choose_palette(pal -
Video Compression for New Formats
ANNÉE 2016 THÈSE / UNIVERSITÉ DE RENNES 1 sous le sceau de l’Université Bretagne Loire pour le grade de DOCTEUR DE L’UNIVERSITÉ DE RENNES 1 Mention : Traitement du Signal et Télécommunications Ecole doctorale Matisse présentée par Philippe Bordes Préparée à l’unité de recherche UMR 6074 - INRIA Institut National Recherche en Informatique et Automatique Adapting Video Thèse soutenue à Rennes le 18 Janvier 2016 devant le jury composé de : Compression to new Thomas SIKORA formats Professeur [Tech. Universität Berlin] / rapporteur François-Xavier COUDOUX Professeur [Université de Valenciennes] / rapporteur Olivier DEFORGES Professeur [Institut d'Electronique et de Télécommunications de Rennes] / examinateur Marco CAGNAZZO Professeur [Telecom Paris Tech] / examinateur Philippe GUILLOTEL Distinguished Scientist [Technicolor] / examinateur Christine GUILLEMOT Directeur de Recherche [INRIA Bretagne et Atlantique] / directeur de thèse Adapting Video Compression to new formats Résumé en français Adaptation de la Compression Vidéo aux nouveaux formats Introduction Le domaine de la compression vidéo se trouve au carrefour de l’avènement des nouvelles technologies d’écrans, l’arrivée de nouveaux appareils connectés et le déploiement de nouveaux services et applications (vidéo à la demande, jeux en réseau, YouTube et vidéo amateurs…). Certaines de ces technologies ne sont pas vraiment nouvelles, mais elles ont progressé récemment pour atteindre un niveau de maturité tel qu’elles représentent maintenant un marché considérable, tout en changeant petit à petit nos habitudes et notre manière de consommer la vidéo en général. Les technologies d’écrans ont rapidement évolués du plasma, LED, LCD, LCD avec rétro- éclairage LED, et maintenant OLED et Quantum Dots. Cette évolution a permis une augmentation de la luminosité des écrans et d’élargir le spectre des couleurs affichables. -
Chromatic Adaptation Transform by Spectral Reconstruction Scott A
Chromatic Adaptation Transform by Spectral Reconstruction Scott A. Burns, University of Illinois at Urbana-Champaign, [email protected] February 28, 2019 Note to readers: This version of the paper is a preprint of a paper to appear in Color Research and Application in October 2019 (Citation: Burns SA. Chromatic adaptation transform by spectral reconstruction. Color Res Appl. 2019;44(5):682-693). The full text of the final version is available courtesy of Wiley Content Sharing initiative at: https://rdcu.be/bEZbD. The final published version differs substantially from the preprint shown here, as follows. The claims of negative tristimulus values being “failures” of a CAT are removed, since in some circumstances such as with “supersaturated” colors, it may be reasonable for a CAT to produce such results. The revised version simply states that in certain applications, tristimulus values outside the spectral locus or having negative values are undesirable. In these cases, the proposed method will guarantee that the destination colors will always be within the spectral locus. Abstract: A color appearance model (CAM) is an advanced colorimetric tool used to predict color appearance under a wide variety of viewing conditions. A chromatic adaptation transform (CAT) is an integral part of a CAM. Its role is to predict “corresponding colors,” that is, a pair of colors that have the same color appearance when viewed under different illuminants, after partial or full adaptation to each illuminant. Modern CATs perform well when applied to a limited range of illuminant pairs and a limited range of source (test) colors. However, they can fail if operated outside these ranges. -
ARC Laboratory Handbook. Vol. 5 Colour: Specification and Measurement
Andrea Urland CONSERVATION OF ARCHITECTURAL HERITAGE, OFARCHITECTURALHERITAGE, CONSERVATION Colour Specification andmeasurement HISTORIC STRUCTURESANDMATERIALS UNESCO ICCROM WHC VOLUME ARC 5 /99 LABORATCOROY HLANODBOUOKR The ICCROM ARC Laboratory Handbook is intended to assist professionals working in the field of conserva- tion of architectural heritage and historic structures. It has been prepared mainly for architects and engineers, but may also be relevant for conservator-restorers or archaeologists. It aims to: - offer an overview of each problem area combined with laboratory practicals and case studies; - describe some of the most widely used practices and illustrate the various approaches to the analysis of materials and their deterioration; - facilitate interdisciplinary teamwork among scientists and other professionals involved in the conservation process. The Handbook has evolved from lecture and laboratory handouts that have been developed for the ICCROM training programmes. It has been devised within the framework of the current courses, principally the International Refresher Course on Conservation of Architectural Heritage and Historic Structures (ARC). The general layout of each volume is as follows: introductory information, explanations of scientific termi- nology, the most common problems met, types of analysis, laboratory tests, case studies and bibliography. The concept behind the Handbook is modular and it has been purposely structured as a series of independent volumes to allow: - authors to periodically update the -
Color Spaces YCH and Ysch for Color Specification and Image Processing in Multi-Core Computing and Mobile Systems
Programación Matemática y Software (2012) Vol. 4. No 2. ISSN: 2007-3283 Recibido: 14 de septiembre del 2011 Aceptado: 3 de enero del 2012 Publicado en línea: 8 de enero del 2013 Color spaces YCH and YScH for color specification and image processing in multi-core computing and mobile systems Yuriy Kotsarenko, Fernando Ramos Tecnológico de Monterrey, Campus Cuernavaca [email protected], [email protected] Resumen. En este trabajo dos nuevos espacios de color se describen para especificación de colores y procesamiento de imágenes utilizando la forma cilíndrica del espacio de color YIQ. Los espacios de colores clásicos tales como HSL y HSV no toman en cuenta la visión humana y son perceptualmente inexactos. Los espacios de colores perceptualmente uniformes como CIELAB y CIELUV son muy costosos computacionalmente para aplicaciones interactivas de tiempo real y son difíciles de implementar. Las alternativas propuestas, por otro lado, tienen un balance entre uniformidad perceptual, desempeño y simplicidad de cálculo. Estos espacios modelan colores de forma más exacta y son rápidos de calcular. Los resultados experimentales en este trabajo comparan espacios de colores clásicos con los propuestos en términos de uniformidad, riqueza de colores y desempeño, incluyendo numerosas pruebas de rapidez en procesadores de varios núcleos y sistemas móviles tales como ultra portátiles y los tablets tipo iPad. Los resultados evidencian que los espacios de colores propuestos son mejores alternativas para la industria de computación donde actualmente se utilicen los espacios de colores clásicos. Abstract. Two novel color spaces are described for color specification and image processing using cylindrical variants of YIQ color space. -
AMSA Meat Color Measurement Guidelines
AMSA Meat Color Measurement Guidelines Revised December 2012 American Meat Science Association http://www.m eatscience.org AMSA Meat Color Measurement Guidelines Revised December 2012 American Meat Science Association 201 West Springfi eld Avenue, Suite 1202 Champaign, Illinois USA 61820 800-517-2672 [email protected] http://www.m eatscience.org iii CONTENTS Technical Writing Committee .................................................................................................................... v Preface ..............................................................................................................................................................vi Section I: Introduction ................................................................................................................................. 1 Section II: Myoglobin Chemistry ............................................................................................................... 3 A. Fundamental Myoglobin Chemistry ................................................................................................................ 3 B. Dynamics of Myoglobin Redox Form Interconversions ........................................................................... 3 C. Visual, Practical Meat Color Versus Actual Pigment Chemistry ........................................................... 5 D. Factors Affecting Meat Color ............................................................................................................................... 6 E. Muscle -
Exploiting Colorimetry for Fidelity in Data Visualization Arxiv
Exploiting Colorimetry for Fidelity in Data Visualization Michael J. Waters,y Jessica M. Walker,y Christopher T. Nelson,z Derk Joester,y and James M. Rondinelli∗,y yDepartment of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, USA zOak Ridge National Laboratory, Oak Ridge, Tennessee 37830, USA E-mail: [email protected] Abstract Advances in multimodal characterization methods fuel a generation of increasing immense hyper-dimensional datasets. Color mapping is employed for conveying higher dimensional data in two-dimensional (2D) representations for human consumption without relying on multiple projections. How one constructs these color maps, however, critically affects how accurately one perceives data. For simple scalar fields, perceptually uniform color maps and color selection have been shown to improve data readability arXiv:2002.12228v1 [cs.HC] 27 Feb 2020 and interpretation across research fields. Here we review core concepts underlying the design of perceptually uniform color map and extend the concepts from scalar fields to two-dimensional vector fields and three-component composition fields frequently found in materials-chemistry research to enable high-fidelity visualization. We develop the software tools PAPUC and CMPUC to enable researchers to utilize these colorimetry principles and employ perceptually uniform color spaces for rigorously meaningful color mapping of higher dimensional data representations. Last, we demonstrate how these 1 approaches deliver immediate improvements in -
Appendix G: the Pantone “Our Color Wheel” Compared to the Chromaticity Diagram (2016) 1
Appendix G - 1 Appendix G: The Pantone “Our color Wheel” compared to the Chromaticity Diagram (2016) 1 There is considerable interest in the conversion of Pantone identified color numbers to other numbers within the CIE and ISO Standards. Unfortunately, most of these Standards are not based on any theoretical foundation and have evolved since the late 1920's based on empirical relationships agreed to by committees. As a general rule, these Standards have all assumed that Grassman’s Law of linearity in the visual realm. Unfortunately, this fundamental assumption is not appropriate and has never been confirmed. The visual system of all biological neural systems rely upon logarithmic summing and differencing. A particular goal has been to define precisely the border between colors occurring in the local language and vernacular. An example is the border between yellow and orange. Because of the logarithmic summations used in the neural circuits of the eye and the positions of perceived yellow and orange relative to the photoreceptors of the eye, defining the transition wavelength between these two colors is particularly acute.The perceived response is particularly sensitive to stimulus intensity in the spectral region from 560 to about 580 nanometers. This Appendix relies upon the Chromaticity Diagram (2016) developed within this work. It has previously been described as The New Chromaticity Diagram, or the New Chromaticity Diagram of Research. It is in fact a foundation document that is theoretically supportable and in turn supports a wide variety of less well founded Hering, Munsell, and various RGB and CMYK representations of the human visual spectrum.