39 Color Variations in Pseudo Color Processing of Graphical Images
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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. -
NEC Multisync® PA311D Wide Gamut Color Critical Display Designed for Photography and Video Production
NEC MultiSync® PA311D Wide gamut color critical display designed for photography and video production 1419058943 High resolution and incredible, predictable color accuracy. The 31” MultiSync PA311D is the ultimate desktop display for applications where precise color is essential. The innovative wide-gamut LED backlight provides 100% coverage of Adobe RGB color space and 98% coverage of DCI-P3, enabling more accurate colors to be displayed on screen. Utilizing a high performance IPS LCD panel and backed by a 4 year warranty with Advanced Exchange, the MultiSync PA311D delivers high quality, accurate images simply and beautifully. Impeccable Image Performance The wide-gamut LED LCD backlight combined with NEC’s exclusive SpectraView Engine deliver precise color in every environment. • True 4K resolution (4096 x 2160) offers a high pixel density • Up to 100% coverage of Adobe RGB color space and 98% coverage of DCI-P3 • 10-bit HDMI and DisplayPort inputs display up to 1.07 billion colors out of a palette of 4.3 trillion colors Ultimate Color Management The sophisticated SpectraView Engine provides extensive, intuitive control over color settings. • MultiProfiler software and on-screen controls provide access to thousands of color gamut, gamma, white point, brightness and contrast combinations • Internal 14-bit 3D lookup tables (LUTs) work with optional SpectraViewII color calibration solution for unparalleled color accuracy A Perfect Fit for Your Workspace A Better Workflow Future-proof connectivity, great ergonomics, and VESA mount Exclusive, -
Colour Space Conversion
Colour 1 Shan He 2013 What is light? 'White' light is a combination of many different light wavelengths 2 Shan He 2013 Colour spectrum – visible light • Colour is how we perceive variation in the energy (oscillation wavelength) of visible light waves/particles. Ultraviolet Infrared 400 nm Wavelength 700 nm • Our eye perceives lower energy light (longer wavelength) as so-called red; and higher (shorter wavelength) as so-called blue • Our eyes are more sensitive to light (i.e. see it with more intensity) in some frequencies than in others 3 Shan He 2013 Colour perception . It seems that colour is our brain's perception of the relative levels of stimulation of the three types of cone cells within the human eye . Each type of cone cell is generally sensitive to the red, blue and green regions of the light spectrum Images of living human retina with different cones sensitive to different colours. 4 Shan He 2013 Colour perception . Spectral sensitivity of the cone cells overlap somewhat, so one wavelength of light will likely stimulate all three cells to some extent . So by mixing multiple components pure light (i.e. of a fixed spectrum) and altering intensity of the mixed components, we can vary the overall colour that is perceived by the brain. 5 Shan He 2013 Colour perception: Eye of Brain? • Stroop effect 6 Shan He 2013 Do you see same colours I see? • The number of color-sensitive cones in the human retina differs dramatically among people • Language might affect the way we perceive colour 7 Shan He 2013 Colour spaces . -
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 -
Er.Heena Gulati, Er. Parminder Singh
International Journal of Computer Science Trends and Technology (IJCST) – Volume 3 Issue 2, Mar-Apr 2015 RESEARCH ARTICLE OPEN ACCESS SWT Approach For The Detection Of Cotton Contaminants Er.Heena Gulati [1], Er. Parminder Singh [2] Research Scholar [1], Assistant Professor [2] Department of Computer Science and Engineering Doaba college of Engineering and Technology Kharar PTU University Punjab - India ABSTRACT Presence of foreign fibers’ & cotton contaminants in cotton degrades the quality of cotton The digital image processing techniques based on computer vision provides a good way to eliminate such contaminants from cotton. There are various techniques used to detect the cotton contaminants and foreign fibres. The major contaminants found in cotton are plastic film, nylon straps, jute, dry cotton, bird feather, glass, paper, rust, oil grease, metal wires and various foreign fibres like silk, nylon polypropylene of different colors and some of white colour may or may not be of cotton itself. After analyzing cotton contaminants characteristics adequately, the paper presents various techniques for detection of foreign fibres and contaminants from cotton. Many techniques were implemented like HSI, YDbDR, YCbCR .RGB images are converted into these components then by calculating the threshold values these images are fused in the end which detects the contaminants .In this research the YCbCR , YDbDR color spaces and fusion technique is applied that is SWT in the end which will fuse the image which is being analysis according to its threshold value and will provide good results which are based on parameters like mean ,standard deviation and variance and time. Keywords:- Cotton Contaminants; Detection; YCBCR,YDBDR,SWT Fusion, Comparison I. -
HD-SDI, HDMI, and Tempus Fugit
TECHNICALL Y SPEAKING... By Steve Somers, Vice President of Engineering HD-SDI, HDMI, and Tempus Fugit D-SDI (high definition serial digital interface) and HDMI (high definition multimedia interface) Hversion 1.3 are receiving considerable attention these days. “These days” really moved ahead rapidly now that I recall writing in this column on HD-SDI just one year ago. And, exactly two years ago the topic was DVI and HDMI. To be predictably trite, it seems like just yesterday. As with all things digital, there is much change and much to talk about. HD-SDI Redux difference channels suffice with one-half 372M spreads out the image information The HD-SDI is the 1.5 Gbps backbone the sample rate at 37.125 MHz, the ‘2s’ between the two channels to distribute of uncompressed high definition video in 4:2:2. This format is sufficient for high the data payload. Odd-numbered lines conveyance within the professional HD definition television. But, its robustness map to link A and even-numbered lines production environment. It’s been around and simplicity is pressing it into the higher map to link B. Table 1 indicates the since about 1996 and is quite literally the bandwidth demands of digital cinema and organization of 4:2:2, 4:4:4, and 4:4:4:4 savior of high definition interfacing and other uses like 12-bit, 4096 level signal data with respect to the available frame delivery at modest cost over medium-haul formats, refresh rates above 30 frames per rates. distances using RG-6 style video coax. -
新動画用拡張色空間xvycc(IEC61966-2-4)
xvYCC制定の背景 1. 現在のテレビシステムの色再現は、CRT の蛍光 新動画用拡張色空間 体の特性をもとに決められており、実在する物体 xvYCC(IEC61966-2-4) 色の約55%しか表現できないという問題があった。 2. これまでのテレビ信号との互換性を保持しつつ、よ り鮮やかな色を表現するため、新しい動画用拡張 (社)電子情報技術産業協会 AV&IT機器標準化委員会 色空間規格IEC61966-2-4: xvYCC(エックスブイ・ ・カラーマネージメント標準化グループ ワイシーシー)の制定に至った。 主査: 杉浦博明 [三菱電機㈱] ・61966-2sRGB等対応グループ 副主査: 加藤直哉 [ソニー㈱] 2006/08/30 @JEITA 1 2 xvYCC制定の経緯 動画用拡張色域YCC色空間 - Extended-gamut YCC colour space [2004 年9 月] for video applications - xvYCC JEITA カラーマネジメント標準化委員会(後にカラー マネジメント標準化グループに改組)において、動画用 拡張色空間xvYCCの国際規格化の審議を開始した。 拡張色域色空間制定の背景 表示装置の現状 [2004 年10 月] 規格の現状(cf. 静止画) 韓国 ソウルで開催された第68 回IEC(国際電気標準 会議)総会と同時開催の第10回TC100 総会において、 撮像装置の現状 日本から提案した本規格案は、次世代のテレビシステ ムあるいは、動画システムにおいて非常に重要との産 IECにおける標準化の経緯 業的判断から、加速化プロセスにて迅速な審議を行うこ xvYCC – IEC61966-2-4 とが決定された。 各種色空間の比較 [2006 年1 月] メディア色域包括率 IEC に設けられたプロジェクトチームにおいて、数回 の国際的な審議を経た後、ほぼJEITA からの提案どお 期待される効果 りの内容で国際規格IEC 61966-2-4 として正式に発行 された。 関連プレスリリース 他規格(MPEG,HDMI)への波及 3 4 sRGB色域外の高彩度物体色の例 拡張色域色空間の必要性(背景1) CRT以外の技術を用いて色再現域(色域)を拡張させた 様々な表示装置が市場に出現してきている. 0.9 しかしながら,現在の動画コンテンツの多くは従来の(sRGB 0.8 色域に制限された)CRTテレビ向けに画作りされている. 0.7 その結果,表示装置側が広色域となったメリットを活かしき 0.6 れていないのが現状である. 0.5 0.4 sRGB 0.6 0.3 (CRT色域) 0.2 0.4 0.1 CIE sRGB 0 Triluminos 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 色域外 0.2 x sRGB(709) NTSC Wide-gamut xy Chromaticity Diagram 0 0 0.2 0.4 0.6 これらの色は,CRT特性をもとに決められた従来のテレビ信号では表現できません. 5 6 SID 2005 @ Boston SID 2006 @ San Francisco 広色域関連発表:計5件(4社) 広色域関連発表:計4件(3社) Session 25: Spatial and Temporal Color Session 19: Applications and Vision STColor: Hybrid Spatial-Temporal Color Synthesis for Enhanced (Applications/Applied Vision) Display Image Quality Improved Six-Primary-Color 23-in. WXGA LCD Using Six-Color LEDs L. D. Silverstein, VCD Sciences, Inc., USA Hiroaki Sugiura, Mitsubishi Electric Corp., Japan A Wide-Gamut-Color High-Aperture-Ratio Mobile Spectrum xvYCC: A new Standard for Video Systems Using Extended-Gamut Sequential LCD YCC Color Space S. -
Color Images, Color Spaces and Color Image Processing
color images, color spaces and color image processing Ole-Johan Skrede 08.03.2017 INF2310 - Digital Image Processing Department of Informatics The Faculty of Mathematics and Natural Sciences University of Oslo After original slides by Fritz Albregtsen today’s lecture ∙ Color, color vision and color detection ∙ Color spaces and color models ∙ Transitions between color spaces ∙ Color image display ∙ Look up tables for colors ∙ Color image printing ∙ Pseudocolors and fake colors ∙ Color image processing ∙ Sections in Gonzales & Woods: ∙ 6.1 Color Funcdamentals ∙ 6.2 Color Models ∙ 6.3 Pseudocolor Image Processing ∙ 6.4 Basics of Full-Color Image Processing ∙ 6.5.5 Histogram Processing ∙ 6.6 Smoothing and Sharpening ∙ 6.7 Image Segmentation Based on Color 1 motivation ∙ We can differentiate between thousands of colors ∙ Colors make it easy to distinguish objects ∙ Visually ∙ And digitally ∙ We need to: ∙ Know what color space to use for different tasks ∙ Transit between color spaces ∙ Store color images rationally and compactly ∙ Know techniques for color image printing 2 the color of the light from the sun spectral exitance The light from the sun can be modeled with the spectral exitance of a black surface (the radiant exitance of a surface per unit wavelength) 2πhc2 1 M(λ) = { } : λ5 hc − exp λkT 1 where ∙ h ≈ 6:626 070 04 × 10−34 m2 kg s−1 is the Planck constant. ∙ c = 299 792 458 m s−1 is the speed of light. ∙ λ [m] is the radiation wavelength. ∙ k ≈ 1:380 648 52 × 10−23 m2 kg s−2 K−1 is the Boltzmann constant. T ∙ [K] is the surface temperature of the radiating Figure 1: Spectral exitance of a black body surface for different body. -
Compsci 372 – Tutorial
CompSci 372 – Tutorial Part 10 Colour 20/10/2008 CompSci 372 - Tutorial 10 1 Electromagnetic Radiation 20/10/2008 CompSci 372 - Tutorial 10 2 Spectrum ● Spectral Density Function (SDF) Energy Energy 400nm Wavelength 700nm 400nm Wavelength 700nm Energy Energy 400nm Wavelength 700nm 400nm Wavelength 700nm 20/10/2008 CompSci 372 - Tutorial 10 3 Spectrum Energy 400nm Wavelength 700nm ● Hue: Dominant wavelength ● Luminance: Sum of energy, Brightness ● Saturation: Ratio Hue part/Luminance 20/10/2008 CompSci 372 - Tutorial 10 4 Spectrum Energy 400nm Wavelength 700nm ● Hue High S High S Med L Low L ● Luminance ● Saturation 20/10/2008 CompSci 372 - Tutorial 10 5 Spectrum Energy 400nm Wavelength 700nm ● Hue Low S Low S High L Low L ● Luminance ● Saturation 20/10/2008 CompSci 372 - Tutorial 10 6 Interaction with Materials ● Absorption ● Transmission ● Reflection ● (Combination) ● Preservation of Energy 20/10/2008 CompSci 372 - Tutorial 10 7 Spectrum ● Spectral Response Function (SRF) Energy Energy 400nm Wavelength 700nm 400nm Wavelength 700nm Energy Energy 400nm Wavelength 700nm 400nm Wavelength 700nm 20/10/2008 CompSci 372 - Tutorial 10 8 Result ● SDF · SRF = Result SDF Energy 400nm Wavelength 700nm Energy 400nm Wavelength 700nm Energy 400nm Wavelength 700nm 20/10/2008 CompSci 372 - Tutorial 10 9 Result ● Light sources defined by their SDF ● Materials defined by their SRF – Absorbed Light SRF ● Surfaces, Eye, CCD chip, ... – Reflected Light SRF ● Mirror, polished surface,... – Transmitted Light SRF ● Glass, water, ... 20/10/2008 CompSci 372 - Tutorial -
Ipf-White-Paper-Farbsensorik Ohne
ipf_Brief_u_Rechn_Bg_Verw_27_04_09.qx7:IPF_Bb_Verwaltung_070206.qx5 27.04.2009 16:04 Uhr Seite 1 12 White Paper ‘True color’ sensors - See colors like a human does Author: Dipl.-Ing. Christian Fiebach Management Assistant © ipf electronic 2013 ipf_Brief_u_Rechn_Bg_Verw_27_04_09.qx7:IPF_Bb_Verwaltung_070206.qx5 27.04.2009 16:04 Uhr Seite 1 White Paper: ‘True color’ sensors - See colors like a human does _____________________________________________________________________ table of contents introduction 3 ‘normal observer’ determines the average value 4 Different color perception 5 standard colormetric system 6 three-dimensional color system 7 other color systems 9 sensors for ‘True color’detection 10 stating L*a*b* values is not possible with color sensors 11 2D presentations 12 3D presentations 13 different models for different tasks 14 the evaluation of ‘primary light sources’ 14 large detection areas 14 suitable for every surface 15 averages cope with difficult surfaces 15 application examples 16 1. type based selection of glass bottels 16 2. color markings on stainless steel 18 3. automated checking of paint 20 © ipf electronic 2013 2 ipf_Brief_u_Rechn_Bg_Verw_27_04_09.qx7:IPF_Bb_Verwaltung_070206.qx5 27.04.2009 16:04 Uhr Seite 1 White Paper: ‘True color’ sensors - See colors like a human does _____________________________________________________________________ introduction Applications where the color of certain objects has to be securely checked repeatedly present sensors with immense challenges. In particular, the different properties of artificial surfaces make it harder to reliably evaluate color. Why is that? And what solutions are available? In order to come closer to answering these questions, one must first know what abilities the human eye is capable of in the field of color recognition. -
Basics of Video
Basics of Video Yao Wang Polytechnic University, Brooklyn, NY11201 [email protected] Video Basics 1 Outline • Color perception and specification (review on your own) • Video capture and disppy(lay (review on your own ) • Analog raster video • Analog TV systems • Digital video Yao Wang, 2013 Video Basics 2 Analog Video • Video raster • Progressive vs. interlaced raster • Analog TV systems Yao Wang, 2013 Video Basics 3 Raster Scan • Real-world scene is a continuous 3-DsignalD signal (temporal, horizontal, vertical) • Analog video is stored in the raster format – Sampling in time: consecutive sets of frames • To render motion properly, >=30 frame/s is needed – Sampling in vertical direction: a frame is represented by a set of scan lines • Number of lines depends on maximum vertical frequency and viewingg, distance, 525 lines in the NTSC s ystem – Video-raster = 1-D signal consisting of scan lines from successive frames Yao Wang, 2013 Video Basics 4 Progressive and Interlaced Scans Progressive Frame Interlaced Frame Horizontal retrace Field 1 Field 2 Vertical retrace Interlaced scan is developed to provide a trade-off between temporal and vertical resolution, for a given, fixed data rate (number of line/sec). Yao Wang, 2013 Video Basics 5 Waveform and Spectrum of an Interlaced Raster Horizontal retrace Vertical retrace Vertical retrace for first field from first to second field from second to third field Blanking level Black level Ӈ Ӈ Th White level Tl T T ⌬t 2 ⌬ t (a) Խ⌿( f )Խ f 0 fl 2fl 3fl fmax (b) Yao Wang, 2013 Video Basics 6 Color -
High-Speed Interface Bridge LSI for 4K-Video MN869124
High-speed Interface Bridge LSI for 4K-video [ HDMI to HDMI ] MN869124 Overview MN869124 is one of “HV series” that are high-speed interface bridge LSIs for 4K-video. This LSI supports color space conversion for input video. HDMI inputs and output support HDMI2.0/1.4 with HDCP2.2/1.4 contents protection. • Input : HDMI2.0/1.4 (max. 60Hz), HDCP2.2/1.4 support • Output : HDMI2.0/1.4 (max. 60Hz), HDCP2.2/1.4 support • Color space conversion • Up/ Down-scale conversion (Option) * 'HDMI' is a trademark or registered trademark of HDMI Licensing, LLC. 2K to 4K Up-scale conversion with “SUPER RESOLUTION” (Option) Detail Improvement Suppress Overshoot Internal Configuration HDMI1.4 MN869124 HDMI1.4 or or HDMI2.0/ Color Space HDMI2.0/ HDCP Conversion HDCP HDCP2.2 HDMI HDMI HDCP2.2 1.4/2.2 1.4/2.2 3/6Gbps Rx Tx 3/6Gbps Decrypt Up/ Down Encrypt Scaler I2C I2C Specifications Function Specifications Package Type: FBGA, Size: 17mm square HDMI input 4 ports (HDMI2.0/1.4, HDCP2.2/1.4) I/O HDMI output 1 port (HDMI2.0/1.4, HDCP2.2/1.4) Color Space Conversion Refer to the following table. • 2K to 4K Up-scale Conversion with Super Resolution (Option) Up/ Down Scale Conversion * Frame Rate: 24Hz, 25Hz, 30Hz, 50Hz, 60Hz • 4K to 2K Down-scale Conversion (Option) Frame Rate Conversion None Input I2Sx4(8ch), SPDIFx1 Audio Output I2Sx4(8ch), SPDIFx1 Power 1.2V/ 3.3V Color Space Conversion YCbCr / xvYCC sRGB Output ITU-R ITU-R Limit Full BT.601 BT.709 Range Range Input 422 444 420 422 444 444 444 (4k only) ITU-R 422 BT.601 444 YCbCr 420 /xvYCC ITU-R (4K only) BT.709 422 444 Limit Range 444 sRGB Full Range 444 The Products and product specifications described in this document are subject to change Socionext without notice for modification and/or improvement.