Growing Importance of Color in a World of Displays and Data Color In
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High Dynamic Range Metadata for Apple Devices (Preliminary)
High Dynamic Range Metadata For Apple Devices (Preliminary) " Version 0.9 May 31, 2019 ! Copyright © 2019 Apple Inc. All rights reserved. Apple, the Apple logo and QuickTime are trademarks of Apple Inc., registered in the U.S. and other countries. Dolby, Dolby Vision, and the double-D symbol are trademarks of Dolby Laboratories. 1" Introduction 3 Dolby Vision™ 4 HDR10 6 Hybrid Log-Gamma (HLG) 8 References 9 Document Revision History 10 ! Copyright © 2019 Apple Inc. All rights reserved. Apple, the Apple logo and QuickTime are trademarks of Apple Inc., registered in the U.S. and other countries. Dolby, Dolby Vision, and the double-D symbol are trademarks of Dolby Laboratories. 2" Introduction This document describes the metadata and constraints for High Dynamic Range (HDR) video stored in a QuickTime Movie or ISO Base Media File required for proper display on Apple Plat- forms. Three types of HDR are detailed. 1. Dolby Vision™ 2. HDR10 3. Hybrid Log-Gamma (HLG) Note: The QuickTime Movie File Format Specification and the ISO Base Media File Format Specification use different terminology for broadly equivalent concepts: atoms and boxes; sam- ple descriptions and sample entries. This document uses the former specification's terminolo- gies without loss of generality. This document covers file-based workflows, for HLS streaming requirements go to: https://developer.apple.com/documentation/http_live_streaming/hls_authoring_specification_- for_apple_devices ! Copyright © 2019 Apple Inc. All rights reserved. Apple, the Apple logo and QuickTime are trademarks of Apple Inc., registered in the U.S. and other countries. Dolby, Dolby Vision, and the double-D symbol are trademarks of Dolby Laboratories. -
Live Single-Stream HDR Production for HDR and SDR Cable Distribution
Live Single-Stream HDR Production for HDR and SDR Cable Distribution What Happens When “Post Production” Is Real-Time prepared for SCTE•ISBE by Chris Seeger Director, Advanced Content Production NBC Universal, LLC 900 Sylvan Avenue Englewood Cliffs, NJ 07632 [email protected] © 2020 SCTE•ISBE and NCTA. All rights reserved. 1 Table of Contents Title Page Number 1. INTRODUCTION 3 2. CONTENT CONVERSION AND PERCEPTUAL MEASUREMENT 3 2.1. How the Human Visual System Sees Light and Color 5 2.2. SINGLE-STREAM HDR AND SDR PRODUCTION 9 2.3. Hybrid Log-Gamma 11 2.4. HLG from camera to display 12 2.5. Color Conversion and objective color accuracy measurements 12 3. SINGLE-STREAM HDR-SDR PRODUCTION 15 4. HDR/SDR SINGLE-STREAM DISTRIBUTION 18 5. CONCLUSION 20 ABBREVIATIONS 21 BIBLIOGRAPHY & REFERENCES 21 List of Figures Title Page Number Figure 1 - How Do We See Light and Color? (© Universal Pictures from PacRim) ..................................... 4 Figure 2 - The Human Visual System and Color .......................................................................................... 6 Figure 3 - Static versus Dynamic Adjustments to Light Levels ..................................................................... 6 Figure 4 - The Human Visual System is Relative ......................................................................................... 7 Figure 5 - Color Appearance and HDR Production ...................................................................................... 8 Figure 6 - Nothing in This Image is Actually Moving .................................................................................... -
COLORFRONT ENGINE™ Challenge a SIMPLE COMMON SINGLE MASTER IMAGE PIPELINE IS NEEDED
COLORFRONT ENGINE™ Challenge A SIMPLE COMMON SINGLE MASTER IMAGE PIPELINE IS NEEDED ► Today there is ever increasing number of acquisition sources and delivery requirements ► Neither practical nor affordable to separately support each individual standard, color space, brightness level, source or delivery format ► A simple common image pipeline is needed from on-set through final delivery to ensure image integrity COLORFRONT ENGINE SDRSDR SDR HDRHDR HDR10 LogCLogC HLG SLog3SLog3 What is Colorfront Engine? AUTOMATICALLY MANAGED COLOR PIPELINE ► Colorfront Engine is a state-of-the-art, automatically managed, ACES-compliant color pipeline ► Brings true plug-and-play simplicity to today’s complex production requirements ► The technology applies various format-specific input and output transformations to the image • camera-specific live signal • camera recorded footage • projector in P3 color space • display in either SDR or HDR mode Why Colorfront Engine? IMAGE INTEGRITY AND COLOR FIDELITY ► Bring all types of input color spaces and formats into one common denominator ► Ensure image integrity and color fidelity from the on-set world to the multitude of current and future delivery requirements ► Simplify them into a single workflow ► Maintaining an industry-leading color quality Advantages of using Colorfront Engine UHD/HDR/WCG PROCESSING BASED ON HUMAN PERCEPTION Linear Mathematical model vs. Perceptually Uniform model ► Colorfront Engine differs from any other systems because it’s algorithms are based on how the human eye actually sees the world ► Not just on a linear mathematics system ► The perceived relationships of color and brightness remain constant across differing dynamic ranges, brightnesses, and color gamuts Maintaining perceptual integrity PRESERVING ORIGINAL CREATIVE INTENT With a perceptually optimized color volume remapping technology, Colorfront Engine is designed to preserve the original creative intent when converting between numerous original camera and delivery formats, no matter what the color space, brightness level, or dynamic range is. -
Visor: Hao-Chung Kuo 李柏璁 Po-Tsung Lee
國立交通大學 顯示科技研究所 碩士論文 應用於 紅,藍,綠 發光二極體色彩穩定之 控制回饋系統設計 Light Output Feedback Control System Design for RGB LED Color Stabilization 研究生:李仕龍 指導教授:郭浩中 教授 李柏璁 教授 中華民國九十七年六月 應用於 紅,藍,綠 發光二極體色彩穩定之 控制回饋系統設計 Light Output Feedback Control System Design for RGB LED Color Stabilization 研 究 生: 李仕龍 Student: Shih-Lung Lee 指導教授: 郭浩中 Advisor: Hao-chung Kuo 李柏璁 Po-Tsung Lee 國立交通大學 顯示科技研究所 碩士論文 A Thesis Submitted to Display Institute College of Electrical and Computer Engineering National Chiao Tung University in Partial Fulfillment of the Requirements for the Degree of Master In Display Institute June 2008 HsinChu, Taiwan, Republic of China. 中華民國九十七年六月 應用於 紅,藍,綠 發光二極體色彩穩定之 控制回饋系統設計 碩士班研究生:李仕龍 指導教授: 郭浩中,李柏璁 國立交通大學 顯示科技研究所 摘要 顯示科技蓬勃發展,液晶顯示器(Liquid Crystal Display)已成為取 代陰極射線管顯示器(Cathode Ray Tube Monitor)最強大的主流產品,由 於液晶顯示器並非主動發光元件,必須仰賴一個外加的光源系統,此即所 謂的背光模組,而背光模組使用冷陰極射線管(Cold Cathode Fluorescent Lamp)充當光源已行之有年;發光二極體(Light Emitting Diode)因較冷 陰極射線管具有壽命長,廣色域、省電、環保、反應快速等多項優點,已 成為液晶顯示器背光源的新選擇。然而,長時間使用下而產生的熱,往往 造成發光二極體的發光顏色偏移,此在顯示器要求高色彩品質的標準下, 是最不樂見的。 本論文提出了使用光二極體感測發光二極體的光輸出訊號,經類比數 位轉換的裝置,套用反覆逼近的程式,設計建立一組μA等級的電流逼近 的發光二極體色彩穩定回饋系統。回饋系統在 13 位元解析下,可將對應 於使用 3250, 3969, 及4462小時的紅色,藍色及綠色發光二極體的色偏 值(Δu'v')維持在內 0.005 (人眼恰可接受的範圍) 內。使用 14 位元 解析下,可將紅,藍及綠色發光二極體的色偏值維持在內 0.004 之內。 I Light Output Feedback Control System Design for RGB LED Color Stabilization Student : Shih-Lung Lee Advisor: Hao-chung Kuo Po-Tsung Lee Display Institute National Chiao-Tung University Abstract LCD (Liquid Crystal Display) is the mainstream product to replace CRT (Cathode Ray Tube). Conventionally, CCFL (Cold Cathode Fluorescent Lamp) is used as a light source of LCD backlight. However, LED (Light Emitting Diode) is regarded as the candidate to replace CCFL (Cold Cathode Fluorescent Lamp) as light source of LCD backlight due to its wide color gamut, low operation voltage, mercuryfree characteristic, and fast switch response. -
Characterization, Modeling, and Optimization of Light-Emitting Diode Systems
Downloaded from orbit.dtu.dk on: Oct 09, 2021 Characterization, Modeling, and Optimization of Light-Emitting Diode Systems Thorseth, Anders Publication date: 2011 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Thorseth, A. (2011). Characterization, Modeling, and Optimization of Light-Emitting Diode Systems. Technical University of Denmark. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. FACULTY OF SCIENCE UNIVERSITY OF COPENHAGEN Ph.D. thesis Anders Thorseth Characterization, Modeling, and Optimiza- tion of Light-Emitting Diode Systems Principal supervisor: Jan W. Thomsen Co-supervisor: Carsten Dam-Hansen Submitted: 31/03/2011 i \Here forms, here colours, here the character of every part of the universe are concentrated to a point." Leonardo da Vinci, on the eye [156, p. 20] ii Abstract This thesis explores, characterization, modeling, and optimization of light-emitting diodes (LED) for general illumination. -
Electronic Supplementary Material
1 2 Electronic Supplementary Material 3 This Electronic Supplimentary Material has been provided by the authors to give readers 4 additional information about the technical details of their work. 5 Supplement to: 6 Elliott JT, Wirth DJ, Davis SC, et al. Seeing the light: Improving the usability of fluorescence- 7 guided surgery by adding an optimized secondary light source. 8 9 10 11 Optimizing the Secondary Illuminant Filters and Intensity 12 Hyperspectral Imaging Instrumentation and Light Source Adapter 13 An in-house hyperspectral imaging system (HIS) enabled acquisition of spectrally resolved 14 images during reflectance and fluorescence illumination of the surgical field. The detection module 15 consisted of an achromatic lens that focused light transmitted from the accessory port, through a liquid 16 crystal tunable filter (LCTF; VariSpec VIS 450-750, Perkin-Elmer, Waltham, MA) with 7-nm bandwidth 17 onto a CMOS camera (Edge 4.2, PCO, Kelheim, Germany). Hyperspectral imaging data were acquired 18 every 100 ms while the LCTF was swept across wavelengths at 5 nm intervals to characterize the 19 spectrum within the 450-720 nm range, generating data (every 5 minutes) with dimensions 540 px x 640 20 px x 55 wavelengths. Simultaneously, the Zeiss camera acquired images and video during the reflectance 21 and fluorescence mode acquisitions.. 22 Figure ESM1 shows the adapter that was used to mount a secondary illuminant onto the Pentero. 23 24 Figure ESM1. Bottom and side views of the secondary illuminant adapter, which attaches to the Zeiss OPMI via its 25 dove-tail plate adapter (not shown). An arc-shaped light baffle prevented glare from the primary light source. -
Color Volume Analysis Workflow
Setup Guide Color Volume Analysis Workflow Rev. 1.2 CalMAN Setup Guide: Color Volume Analysis Workflow Introduction Until the introduction of HDR, a video display’s color reproduction range was typically represented with a two-dimensional chromaticity diagram such as the 1931 or 1976 CIE chromaticity diagram. A triangle overlaid on the chromaticity diagram indicated the bounds of the color gamut reproduced by a given device or specified by a particular color standard. However, a color gamut triangle on a 2D chromaticity diagram represents a display’s range of colors at only one luminance level, typically 75% of the display’s peak luminance. As the luminance of any color decreases toward black or increases toward white, the saturation of the color decreases. Thus, at lower and higher luminance levels, the range (gamut) of colors produced by a display decreases; the gamut triangle gets smaller. Adding luminance levels to the 2D color gamut diagram results in a 3- dimensional color volume that represents the combined ranges of hue, saturation, and luminance that a display can produce. The CalMAN Color Volume Analysis workflow provides two different metrics to analyze the volume of a display’s color reproduction range, CIE L*a*b* and ICtCp. The CIE L*a*b* Color Volume metric measures 140 points and calculates the CIE L* a*b* volume as a percentage of BT.709, DCI-P3, and BT.2020. There is also a Relative or Absolute calculation selection in the workflow page. The ICtCp Color Volume metric measures 393 point on the gamut shell and calculates how many Millions of Distinguishable Colors (MDC) the display can reproduce. -
CCS Series Spectrometer 1 General Information the CCS Series Spectrometer Is Designed for General Laboratory Use
Spectrometer CCS Series Operation Manual 2014 Version: 2.02 Date: 21-Mar-2014 Copyright © 2014 Thorlabs Contents Foreword 3 1 General Information 4 1.1 Safety 4 1.2 Ordering Codes and Accessories 5 1.3 Requirements 5 2 Installation 6 2.1 Parts List 6 2.2 Installing Software 7 3 Getting Started 12 4 Operating Instruction 14 4.1 Main Menu 15 4.1.1 File 15 4.1.2 Sweep 18 4.1.3 Display 22 4.1.4 Level 25 4.1.5 Marker 26 4.1.5.1 Movable Markers 26 4.1.5.2 Fixed Markers 28 4.1.6 Analysis 31 4.1.6.1 Peak Track Analysis 31 4.1.6.2 Color Analysis 33 4.1.6.3 Statistics 34 4.1.6.4 Long Term Analysis 35 4.1.7 Math 39 4.1.8 Setup 45 4.1.8.1 Tab Active Device 45 4.1.8.2 Tab Display 50 4.1.8.3 Tab Peak Track 51 4.1.8.4 Tab Reset 52 4.1.9 Help 52 4.2 Settings Bar 53 4.3 Trace Controls 54 5 Write Your Own Application 57 5.1 NI VISA Instrument driver 32bit on 32bit systems 58 5.2 NI VISA Instrument driver 32bit on 64bit systems 60 5.3 NI VISA Instrument driver 64bit on 64bit systems 62 6 Maintenance and Service 64 6.1 Version Information 64 6.2 Troubleshooting 65 7 Appendix 66 7.1 Technical Data 66 7.2 Dimensions 67 7.3 Tutorial 68 7.4 Shortcuts Used in OSA Software 72 7.5 Certifications and Compliances 73 7.6 Warranty 74 7.7 Copyright and Exclusion of Reliability 75 7.8 Thorlabs 'End of Life' Policy (WEEE) 76 7.9 List of Acronyms 77 7.10 Thorlabs Worldwide Contacts 78 We aim to develop and produce the best solution for your application in the field of optical measurement techniques. -
Effect of Peak Luminance on Perceptual Color Gamut Volume
https://doi.org/10.2352/issn.2169-2629.2020.28.3 ©2020 Society for Imaging Science and Technology Effect of Peak Luminance on Perceptual Color Gamut Volume Fu Jiang,∗ Mark D. Fairchild,∗ Kenichiro Masaoka∗∗; ∗Munsell Color Science Laboratory, Rochester Institute of Technology, Rochester, New York, USA; ∗∗NHK Science & Technology Research Laboratories, Setagaya, Tokyo, Japan Abstract meaningless in terms of color appearance. In this paper, two psychophysical experiments were con- Color appearance models, as proposed and tested by CIE ducted to explore the effect of peak luminance on the perceptual Technical Committee 1-34, are required to have predictive corre- color gamut volume. The two experiments were designed with lates of at least the relative appearance attributes of lightness, two different image data rendering methods: clipping the peak chroma, and hue [3]. CIELAB is the widely used and well- luminance and scaling the image luminance to display’s peak lu- known example of such a color appearance space though its orig- minance capability. The perceptual color gamut volume showed inal goal was supra-threshold color-difference uniformity. How- a close linear relationship to the log scale of peak luminance. ever, CIELAB does not take the other attributes of the view- The results were found not consistent with the computational ing environment and background, such as absolute luminance 3D color appearance gamut volume from previous work. The level, into consideration. CIECAM02 is CIE-recommended difference was suspected to be caused by the different perspec- color appearance model for more complex viewing situations tives between the computational 3D color appearance gamut vol- [4]. -
Wide Color Gamut SET EXPO 2016
Wide Color Gamut SET EXPO 2016 31 AUGUST 2016 Eliésio Silva Júnior Reseller Account Manager E/ [email protected] T/ +55 11 3530-8940 M/ +55 21 9 7242-4211 tek.com Anatomy Human Vision CIE Chart Color Gamuts Wide Color Gamut Gamma and High Dynamic Range 2 Basic Anatomy - Human vision system PHYSICAL PART/ELEMENTS • Eye, Lens and Retina ▪ Rods ▫ Sensitive to Blue-green light ▫ Used for vision under dark-dim conditions. ▪ Cones ▫ 3 Types of Cones Sensitive to either long wavelengths of light (red light) medium wavelengths of light (green light) short wavelengths of light (blue light) ◦ Optic nerve http://webvision.med.utah.edu/index.html 3 Color Model – CIE color spaces NTSC (1953) BT709/sRGB BT2020 ~SMPTE C D65 white BT2020 NTSC (1953) Black BT709/sRGB (70% NTSC) White ~SMPTE C D65 white CIE-1931 chart CIE-1976 chart (More perceptually uniform than CIE-1931) • CIE 1931 XYZ color space ◦ Still foundation of most color models • Trichromatic stimulus (color value) • Lightness decreases towards not shown third dimmension • Saturation increases towards edges 4 ITU 601-7 & 709-5 Chromaticity ITU-R BT 601-7 601-7 525 CIE x CIE y Red 0.630 0.340 Green 0.310 0.595 Blue 0.155 0.070 White 0.3127 0.3290 ITU-R BT 709-5 709-5/601 625 CIE x CIE y Red 0.640 0.330 Green 0.300 0.600 Blue 0.150 0.060 White 0.3127 0.3290 31 AUGUST 2016 5 Wider Color - Chromaticity ITU-R BT 2020 CIE x CIE y Red 0.708 0.292 Green 0.170 0.797 Blue 0.131 0.046 White 0.31272 0.32903 ITU-R BT 709-5 709-5 CIE x CIE y Red 0.640 0.330 Green 0.300 0.600 Blue 0.150 0.060 White 0.3127 0.3290 -
Measuring Perceptual Color Volume V7.1
EEDS TO CHANG Perceptual Color Volume Measuring the Distinguishable Colors of HDR and WCG Displays INTRODUCTION Metrics exist to describe display capabilities such as contrast, bit depth, and resolution, but none yet exist to describe the range of colors produced by high-dynamic-range and wide-color-gamut displays. This paper proposes a new metric, millions of distinguishable colors (MDC), to describe the range of both colors and luminance levels that a display can reproduce. This new metric is calculated by these steps: 1) Measuring the XYZ values for a sample of colors that lie on the display gamut boundary 2) Converting these values into a perceptually-uniform color representation 3) Computing the volume of the 3D solid The output of this metric is given in millions of distinguishable colors (MDC). Depending on the chosen color representation, it can relate to the number of just-noticeable differences (JND) that a display (assuming sufficient bit-depth) can produce. MEASURING THE GAMUT BOUNDARY The goal of this display measurement is to have a uniform sampling of the boundary capabilities of the display. If the display cannot be modeled by a linear combination of RGB primaries, then a minimum of 386 measurements are required to sample the input RGB cube (9x9x6). Otherwise, the 386 measurements may be simulated through five measurements (Red, Green, Blue, Black, and White). We recommend the following measuring techniques: - For displaying colors, use a center-box pattern to cover 10% area of the screen - Using a spectroradiometer with a 2-degree aperture, place it one meter from the display - To exclude veiling-glare, use a flat or frustum tube mask that does not touch the screen Version 7.1 Dolby Laboratories, Inc. -
Quick Reference HDR Glossary
Quick Reference HDR Glossary updated 11.2018 Quick Reference HDR Glossary technicolor Contents 1 AVC 10 MaxCLL Metadata 1 Bit Depth or Colour Depth 10 MaxFALL Metadata 2 Bitrate 10 Nits (cd/m2) 2 Color Calibration of Screens 10 NRT Workflow 2 Contrast Ratio 11 OETF 3 CRI (Color Remapping 11 OLED Information) 11 OOTF 3 DCI-P3, D65-P3, ST 428-1 11 Peak Code Value 3 Dynamic Range 11 Peak Display Luminance 4 EDID 11 PQ 4 EOTF 12 Quantum Dot (QD) Displays 4 Flicker 12 Rec. 2020 or BT.2020 4 Frame Rate 13 Rec.709 or BT.709 or sRGB 5 f-stop of Dynamic Range 13 RT (Real-Time) Workflow 5 Gamut or Color Gamut 13 SEI Message 5 Gamut Mapping 13 Sequential Contrast / 6 HDMI Simultaneous Contrast 6 HDR 14 ST 2084 6 HDR System 14 ST 2086 7 HEVC 14 SDR/SDR System 7 High Frame Rate 14 Tone Mapping/ Tone Mapping 8 Image Resolution Operator (TMO) 8 IMF 15 Ultra HD 8 Inverse Tone Mapping (ITM) 15 Upscaling / Upconverting 9 Judder/Motion Blur 15 Wide Color Gamut (WCG) 9 LCD 15 White Point 9 LUT 16 XML 1 Quick Reference HDR Glossary AVC technicolor Stands for Advanced Video Coding. Known as H.264 or MPEG AVC, is a video compression format for the recording, compression, and distribution of video content. AVC is best known as being one of the video encoding standards for Blu-ray Discs; all Blu-ray Disc players must be able to decode H.264. It is also widely used by streaming internet sources, such as videos from Vimeo, YouTube, and the iTunes Store, web software such as the Adobe Flash Player and Microsoft Silverlight, and also various HDTV broadcasts over terrestrial (ATSC, ISDB-T, DVB-T or DVB-T2), cable (DVB-C), and satellite (DVB-S and DVB-S2).