Report ITU-R BT.2407-0 (10/2017)
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Color Models
Color Models Jian Huang CS456 Main Color Spaces • CIE XYZ, xyY • RGB, CMYK • HSV (Munsell, HSL, IHS) • Lab, UVW, YUV, YCrCb, Luv, Differences in Color Spaces • What is the use? For display, editing, computation, compression, …? • Several key (very often conflicting) features may be sought after: – Additive (RGB) or subtractive (CMYK) – Separation of luminance and chromaticity – Equal distance between colors are equally perceivable CIE Standard • CIE: International Commission on Illumination (Comission Internationale de l’Eclairage). • Human perception based standard (1931), established with color matching experiment • Standard observer: a composite of a group of 15 to 20 people CIE Experiment CIE Experiment Result • Three pure light source: R = 700 nm, G = 546 nm, B = 436 nm. CIE Color Space • 3 hypothetical light sources, X, Y, and Z, which yield positive matching curves • Y: roughly corresponds to luminous efficiency characteristic of human eye CIE Color Space CIE xyY Space • Irregular 3D volume shape is difficult to understand • Chromaticity diagram (the same color of the varying intensity, Y, should all end up at the same point) Color Gamut • The range of color representation of a display device RGB (monitors) • The de facto standard The RGB Cube • RGB color space is perceptually non-linear • RGB space is a subset of the colors human can perceive • Con: what is ‘bloody red’ in RGB? CMY(K): printing • Cyan, Magenta, Yellow (Black) – CMY(K) • A subtractive color model dye color absorbs reflects cyan red blue and green magenta green blue and red yellow blue red and green black all none RGB and CMY • Converting between RGB and CMY RGB and CMY HSV • This color model is based on polar coordinates, not Cartesian coordinates. -
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 -
An Improved SPSIM Index for Image Quality Assessment
S S symmetry Article An Improved SPSIM Index for Image Quality Assessment Mariusz Frackiewicz * , Grzegorz Szolc and Henryk Palus Department of Data Science and Engineering, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland; [email protected] (G.S.); [email protected] (H.P.) * Correspondence: [email protected]; Tel.: +48-32-2371066 Abstract: Objective image quality assessment (IQA) measures are playing an increasingly important role in the evaluation of digital image quality. New IQA indices are expected to be strongly correlated with subjective observer evaluations expressed by Mean Opinion Score (MOS) or Difference Mean Opinion Score (DMOS). One such recently proposed index is the SuperPixel-based SIMilarity (SPSIM) index, which uses superpixel patches instead of a rectangular pixel grid. The authors of this paper have proposed three modifications to the SPSIM index. For this purpose, the color space used by SPSIM was changed and the way SPSIM determines similarity maps was modified using methods derived from an algorithm for computing the Mean Deviation Similarity Index (MDSI). The third modification was a combination of the first two. These three new quality indices were used in the assessment process. The experimental results obtained for many color images from five image databases demonstrated the advantages of the proposed SPSIM modifications. Keywords: image quality assessment; image databases; superpixels; color image; color space; image quality measures Citation: Frackiewicz, M.; Szolc, G.; Palus, H. An Improved SPSIM Index 1. Introduction for Image Quality Assessment. Quantitative domination of acquired color images over gray level images results in Symmetry 2021, 13, 518. https:// the development not only of color image processing methods but also of Image Quality doi.org/10.3390/sym13030518 Assessment (IQA) methods. -
COLOR SPACE MODELS for VIDEO and CHROMA SUBSAMPLING
COLOR SPACE MODELS for VIDEO and CHROMA SUBSAMPLING Color space A color model is an abstract mathematical model describing the way colors can be represented as tuples of numbers, typically as three or four values or color components (e.g. RGB and CMYK are color models). However, a color model with no associated mapping function to an absolute color space is a more or less arbitrary color system with little connection to the requirements of any given application. Adding a certain mapping function between the color model and a certain reference color space results in a definite "footprint" within the reference color space. This "footprint" is known as a gamut, and, in combination with the color model, defines a new color space. For example, Adobe RGB and sRGB are two different absolute color spaces, both based on the RGB model. In the most generic sense of the definition above, color spaces can be defined without the use of a color model. These spaces, such as Pantone, are in effect a given set of names or numbers which are defined by the existence of a corresponding set of physical color swatches. This article focuses on the mathematical model concept. Understanding the concept Most people have heard that a wide range of colors can be created by the primary colors red, blue, and yellow, if working with paints. Those colors then define a color space. We can specify the amount of red color as the X axis, the amount of blue as the Y axis, and the amount of yellow as the Z axis, giving us a three-dimensional space, wherein every possible color has a unique position. -
Camera Raw Workflows
RAW WORKFLOWS: FROM CAMERA TO POST Copyright 2007, Jason Rodriguez, Silicon Imaging, Inc. Introduction What is a RAW file format, and what cameras shoot to these formats? How does working with RAW file-format cameras change the way I shoot? What changes are happening inside the camera I need to be aware of, and what happens when I go into post? What are the available post paths? Is there just one, or are there many ways to reach my end goals? What post tools support RAW file format workflows? How do RAW codecs like CineForm RAW enable me to work faster and with more efficiency? What is a RAW file? In simplest terms is the native digital data off the sensor's A/D converter with no further destructive DSP processing applied Derived from a photometrically linear data source, or can be reconstructed to produce data that directly correspond to the light that was captured by the sensor at the time of exposure (i.e., LOG->Lin reverse LUT) Photometrically Linear 1:1 Photons Digital Values Doubling of light means doubling of digitally encoded value What is a RAW file? In film-analogy would be termed a “digital negative” because it is a latent representation of the light that was captured by the sensor (up to the limit of the full-well capacity of the sensor) “RAW” cameras include Thomson Viper, Arri D-20, Dalsa Evolution 4K, Silicon Imaging SI-2K, Red One, Vision Research Phantom, noXHD, Reel-Stream “Quasi-RAW” cameras include the Panavision Genesis In-Camera Processing Most non-RAW cameras on the market record to 8-bit YUV formats -
Accurately Reproducing Pantone Colors on Digital Presses
Accurately Reproducing Pantone Colors on Digital Presses By Anne Howard Graphic Communication Department College of Liberal Arts California Polytechnic State University June 2012 Abstract Anne Howard Graphic Communication Department, June 2012 Advisor: Dr. Xiaoying Rong The purpose of this study was to find out how accurately digital presses reproduce Pantone spot colors. The Pantone Matching System is a printing industry standard for spot colors. Because digital printing is becoming more popular, this study was intended to help designers decide on whether they should print Pantone colors on digital presses and expect to see similar colors on paper as they do on a computer monitor. This study investigated how a Xerox DocuColor 2060, Ricoh Pro C900s, and a Konica Minolta bizhub Press C8000 with default settings could print 45 Pantone colors from the Uncoated Solid color book with only the use of cyan, magenta, yellow and black toner. After creating a profile with a GRACoL target sheet, the 45 colors were printed again, measured and compared to the original Pantone Swatch book. Results from this study showed that the profile helped correct the DocuColor color output, however, the Konica Minolta and Ricoh color outputs generally produced the same as they did without the profile. The Konica Minolta and Ricoh have much newer versions of the EFI Fiery RIPs than the DocuColor so they are more likely to interpret Pantone colors the same way as when a profile is used. If printers are using newer presses, they should expect to see consistent color output of Pantone colors with or without profiles when using default settings. -
Iec 61966-2-4
This is a preview - click here to buy the full publication IEC 61966-2-4 Edition 1.0 2006-01 INTERNATIONAL STANDARD Multimedia systems and equipment – Colour measurement and management – Part 2-4: Colour management – Extended-gamut YCC colour space for video applications – xvYCC INTERNATIONAL ELECTROTECHNICAL COMMISSION PRICE CODE R ICS 33.160.40 ISBN 2-8318-8426-8 This is a preview - click here to buy the full publication – 2 – 61966-2-4 IEC:2006(E) CONTENTS FOREWORD...........................................................................................................................3 INTRODUCTION.....................................................................................................................5 1 Scope...............................................................................................................................6 2 Normative references .......................................................................................................6 3 Terms and definitions.........................................................................................................6 4 Colorimetric parameters and related characteristics .........................................................7 4.1 Primary colours and reference white........................................................................7 4.2 Opto-electronic transfer characteristics ...................................................................7 4.3 YCC (luma-chroma-chroma) encoding methods.......................................................8 -
Creating 4K/UHD Content Poster
Creating 4K/UHD Content Colorimetry Image Format / SMPTE Standards Figure A2. Using a Table B1: SMPTE Standards The television color specification is based on standards defined by the CIE (Commission 100% color bar signal Square Division separates the image into quad links for distribution. to show conversion Internationale de L’Éclairage) in 1931. The CIE specified an idealized set of primary XYZ SMPTE Standards of RGB levels from UHDTV 1: 3840x2160 (4x1920x1080) tristimulus values. This set is a group of all-positive values converted from R’G’B’ where 700 mv (100%) to ST 125 SDTV Component Video Signal Coding for 4:4:4 and 4:2:2 for 13.5 MHz and 18 MHz Systems 0mv (0%) for each ST 240 Television – 1125-Line High-Definition Production Systems – Signal Parameters Y is proportional to the luminance of the additive mix. This specification is used as the color component with a color bar split ST 259 Television – SDTV Digital Signal/Data – Serial Digital Interface basis for color within 4K/UHDTV1 that supports both ITU-R BT.709 and BT2020. 2020 field BT.2020 and ST 272 Television – Formatting AES/EBU Audio and Auxiliary Data into Digital Video Ancillary Data Space BT.709 test signal. ST 274 Television – 1920 x 1080 Image Sample Structure, Digital Representation and Digital Timing Reference Sequences for The WFM8300 was Table A1: Illuminant (Ill.) Value Multiple Picture Rates 709 configured for Source X / Y BT.709 colorimetry ST 296 1280 x 720 Progressive Image 4:2:2 and 4:4:4 Sample Structure – Analog & Digital Representation & Analog Interface as shown in the video ST 299-0/1/2 24-Bit Digital Audio Format for SMPTE Bit-Serial Interfaces at 1.5 Gb/s and 3 Gb/s – Document Suite Illuminant A: Tungsten Filament Lamp, 2854°K x = 0.4476 y = 0.4075 session display. -
246E9QSB/00 Philips LCD Monitor with Ultra Wide-Color
Philips LCD monitor with Ultra Wide-Color E Line 24 (23.8" / 60.5 cm diag.) Full HD (1920 x 1080) 246E9QSB Stunning color, stylish design The Philips E line monitor features stylish design with extraordinary picture performance. A narrow border Full HD display with Ultra Wide-Color brings you to real true-to-life visuals. Enjoy superior viewing in a stylish design. Superb Picture Quality • Ultra Wide-Color wider range of colors for a vivid picture • IPS LED wide view technology for image and color accuracy • 16:9 Full HD display for crisp detailed images Features designed for you • Narrow border display for a seamless appearance • Less eye fatigue with Flicker-free technology • LowBlue Mode for easy on-the-eyes productivity • EasyRead mode for a paper-like reading experience Greener everyday • Eco-friendly materials meet major international standards • Low power consumption saves energy bills LCD monitor with Ultra Wide-Color 246E9QSB/00 E Line 24 (23.8" / 60.5 cm diag.), Full HD (1920 x 1080) Highlights Ultra Wide-Color Technology 16:9 Full HD display a new solution to regulate brightness and reduce flicker for more comfortable viewing. LowBlue Mode Ultra Wide-Color Technology delivers a wider Picture quality matters. Regular displays deliver spectrum of colors for a more brilliant picture. quality, but you expect more. This display Ultra Wide-Color wider "color gamut" features enhanced Full HD 1920 x 1080 produces more natural-looking greens, vivid resolution. With Full HD for crisp detail paired Studies have shown that just as ultra-violet rays reds and deeper blues. -
Specification of Srgb
How to interpret the sRGB color space (specified in IEC 61966-2-1) for ICC profiles A. Key sRGB color space specifications (see IEC 61966-2-1 https://webstore.iec.ch/publication/6168 for more information). 1. Chromaticity co-ordinates of primaries: R: x = 0.64, y = 0.33, z = 0.03; G: x = 0.30, y = 0.60, z = 0.10; B: x = 0.15, y = 0.06, z = 0.79. Note: These are defined in ITU-R BT.709 (the television standard for HDTV capture). 2. Reference display‘Gamma’: Approximately 2.2 (see precise specification of color component transfer function below). 3. Reference display white point chromaticity: x = 0.3127, y = 0.3290, z = 0.3583 (equivalent to the chromaticity of CIE Illuminant D65). 4. Reference display white point luminance: 80 cd/m2 (includes veiling glare). Note: The reference display white point tristimulus values are: Xabs = 76.04, Yabs = 80, Zabs = 87.12. 5. Reference veiling glare luminance: 0.2 cd/m2 (this is the reference viewer-observed black point luminance). Note: The reference viewer-observed black point tristimulus values are assumed to be: Xabs = 0.1901, Yabs = 0.2, Zabs = 0.2178. These values are not specified in IEC 61966-2-1, and are an additional interpretation provided in this document. 6. Tristimulus value normalization: The CIE 1931 XYZ values are scaled from 0.0 to 1.0. Note: The following scaling equations can be used. These equations are not provided in IEC 61966-2-1, and are an additional interpretation provided in this document. 76.04 X abs 0.1901 XN = = 0.0125313 (Xabs – 0.1901) 80 76.04 0.1901 Yabs 0.2 YN = = 0.0125313 (Yabs – 0.2) 80 0.2 87.12 Zabs 0.2178 ZN = = 0.0125313 (Zabs – 0.2178) 80 87.12 0.2178 7. -
Khronos Data Format Specification
Khronos Data Format Specification Andrew Garrard Version 1.2, Revision 1 2019-03-31 1 / 207 Khronos Data Format Specification License Information Copyright (C) 2014-2019 The Khronos Group Inc. All Rights Reserved. This specification is protected by copyright laws and contains material proprietary to the Khronos Group, Inc. It or any components may not be reproduced, republished, distributed, transmitted, displayed, broadcast, or otherwise exploited in any manner without the express prior written permission of Khronos Group. You may use this specification for implementing the functionality therein, without altering or removing any trademark, copyright or other notice from the specification, but the receipt or possession of this specification does not convey any rights to reproduce, disclose, or distribute its contents, or to manufacture, use, or sell anything that it may describe, in whole or in part. This version of the Data Format Specification is published and copyrighted by Khronos, but is not a Khronos ratified specification. Accordingly, it does not fall within the scope of the Khronos IP policy, except to the extent that sections of it are normatively referenced in ratified Khronos specifications. Such references incorporate the referenced sections into the ratified specifications, and bring those sections into the scope of the policy for those specifications. Khronos Group grants express permission to any current Promoter, Contributor or Adopter member of Khronos to copy and redistribute UNMODIFIED versions of this specification in any fashion, provided that NO CHARGE is made for the specification and the latest available update of the specification for any version of the API is used whenever possible. -
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.