Display Issues Ed Angel

Slides:



Advertisements
Similar presentations
2002 by Jim X. Chen: 1 Understand brightness, intensity, eye characteristics, and gamma correction, halftone technology,
Advertisements

Light Light is fundamental for color vision Unless there is a source of light, there is nothing to see! What do we see? We do not see objects, but the.
Fundamentals of Digital Imaging
School of Computing Science Simon Fraser University
CS 4731: Computer Graphics Lecture 24: Color Science
SWE 423: Multimedia Systems Chapter 4: Graphics and Images (2)
Display Issues Ed Angel Professor of Computer Science, Electrical and Computer Engineering, and Media Arts University of New Mexico.
1 CSCE441: Computer Graphics: Color Models Jinxiang Chai.
CS559-Computer Graphics Copyright Stephen Chenney Color Recap The physical description of color is as a spectrum: the intensity of light at each wavelength.
9/14/04© University of Wisconsin, CS559 Spring 2004 Last Time Intensity perception – the importance of ratios Dynamic Range – what it means and some of.
CS 376 Introduction to Computer Graphics 01 / 26 / 2007 Instructor: Michael Eckmann.
1 Introduction to Computer Graphics with WebGL Ed Angel Professor Emeritus of Computer Science Founding Director, Arts, Research, Technology and Science.
1 Introduction to Computer Graphics with WebGL Ed Angel Professor Emeritus of Computer Science Founding Director, Arts, Research, Technology and Science.
Any questions about the current assignment? (I’ll do my best to help!)
1 © 2010 Cengage Learning Engineering. All Rights Reserved. 1 Introduction to Digital Image Processing with MATLAB ® Asia Edition McAndrew ‧ Wang ‧ Tseng.
Color. Contents Light and color The visible light spectrum Primary and secondary colors Color spaces –RGB, CMY, YIQ, HLS, CIE –CIE XYZ, CIE xyY and CIE.
Color 2011, Fall. Colorimetry : Definition (1/2) Colorimetry  Light is perceived in the visible band from 380 to 780 nm  distribution of wavelengths.
Color Theory ‣ What is color? ‣ How do we perceive it? ‣ How do we describe and match colors? ‣ Color spaces.
1 Introduction to Computer Graphics with WebGL Ed Angel Professor Emeritus of Computer Science Founding Director, Arts, Research, Technology and Science.
CSC361/ Digital Media Burg/Wong
COLORCOLOR Angel 1.4 and 2.4 J. Lindblad
CS6825: Color 2 Light and Color Light is electromagnetic radiation Light is electromagnetic radiation Visible light: nm. range Visible light:
A color model is a specification of a 3D color co-ordinate system and a visible subset in the co-ordinate System within all colors in a particular color.
Three-Receptor Model Designing a system that can individually display thousands of colors is very difficult Instead, colors can be reproduced by mixing.
1 CSCE441: Computer Graphics: Color Models Jinxiang Chai.
Introduction to Computer Graphics
EEL Introduction to Computer Graphics PPT12: Color models Yamini Bura – U
Color Models. Color models,cont’d Different meanings of color: painting wavelength of visible light human eye perception.
Greg Humphreys CS445: Intro Graphics University of Virginia, Fall 2003 Raster Graphics and Color Greg Humphreys University of Virginia CS 445, Fall 2003.
1 CSCE441: Computer Graphics: Color Models Jinxiang Chai.
CS-321 Dr. Mark L. Hornick 1 Color Perception. CS-321 Dr. Mark L. Hornick 2 Color Perception.
David Luebke 1 2/5/2016 Color CS 445/645 Introduction to Computer Graphics David Luebke, Spring 2003.
Color Measurement and Reproduction Eric Dubois. How Can We Specify a Color Numerically? What measurements do we need to take of a colored light to uniquely.
1 of 32 Computer Graphics Color. 2 of 32 Basics Of Color elements of color:
1 Chapter 4 Color in Image and Video 4.1 Color Science 4.2 Color Models in Images 4.3 Color Models in Video 4.4 Further Exploration.
Color Models Light property Color models.
ITEC2110, Digital Media Chapter 2 Fundamentals of Digital Imaging
© 2016 Pearson Education, Inc., Hoboken, NJ. All rights reserved.
Half Toning Dithering RGB CMYK Models
Color Image Processing
Color Image Processing
Color Image Processing
(c) University of Wisconsin, CS559 Spring 2002
COLOR space Mohiuddin Ahmad.
Pengenalan Warna Teori Warna.
Color 2017, Fall.
Angel: Interactive Computer Graphics5E © Addison-Wesley 2009
Yuanfeng Zhou Shandong University
Color Image Processing
Color 2015, Fall.
Achromatic and Colored Light
CITA 342 Section 7 Working with Color.
CS 4722 Computer Graphics and Multimedia Spring 2018
Perception and Measurement of Light, Color, and Appearance
Color & Light CMSC 435/634.
Introduction to Computer Graphics with WebGL
Image Formation Ed Angel Professor Emeritus of Computer Science,
Color Representation Although we can differentiate a hundred different grey-levels, we can easily differentiate thousands of colors.
Isaac Gang University of Mary Hardin-Baylor
Introduction to Perception and Color
Color Image Processing
Slides taken from Scott Schaefer
Angel: Interactive Computer Graphics4E © Addison-Wesley 2005
Color Image Processing
Image Formation Ed Angel
Image Perception and Color Space
Color Model By : Mustafa Salam.
Color Models l Ultraviolet Infrared 10 Microwave 10
University of New Mexico
Color Theory What is color? How do we perceive it?
Presentation transcript:

Display Issues Ed Angel Professor of Computer Science, Electrical and Computer Engineering, and Media Arts University of New Mexico Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Objectives Consider perceptual issues related to displays Introduce chromaticity space Color systems Color transformations Standard Color Systems Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Perception Review Light is the part of the electromagnetic spectrum between ~350-750 nm A color C(l) is a distribution of energies within this range The human visual system has three types of cones on the retina, each with its own spectral sensitivity Consequently, only three values, the tristimulus values, are “seen” by the brain Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Tristimulus Values The human visual center has three cones with sensitivity curves S1(l), S2(l), and S3(l) For a color C(l), the cones output the tristimulus values C(l) optic nerve T1, T2, T3 cones Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Three Color Theory Any two colors with the same tristimulus values are perceived to be identical Thus a display (CRT, LCD, film) must only produce the correct tristimulus values to match a color Is this possible? Not always Different primaries (different sensitivity curves) in different systems Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 The Problem The sensitivity curves of the human are not the same as those of physical devices Human: curves centered in blue, green, and green-yellow CRT: RGB Print media: CMY or CMYK Which colors can we match and, if we cannot match, how close can we come? Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Representing Colors Consider a color C(l) It generates tristimulus values T1, T2, T3 Write C = (T1, T2, T3 ) Conventionally,we assume 1 T1, T2, T3  0 because there is a maximum brightness we can produce and energy is nonnegative C is a point in color solid 1 C T2 T1 1 T3 1 Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Producing Colors Consider a device such as a CRT with RGB primaries and sensitivity curves Tristimulus values Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Matching This T1, T2, T3 is dependent on the particular device If we use another device, we will get different values and these values will not match those of the human cone curves Need a way of matching and a way of normalizing Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Color Systems Various color systems are used Based on real primaries: NTSC RGB UVW CMYK HLS Theoretical XYZ Prefer to separate brightness (luminance) from color (chromatic) information Reduce to two dimensions Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Tristimulus Coordinates For any set of primaries, define Note Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Maxwell Triangle 1 color solid T1 + T2+T3 =1 1 1 Project onto 2D: chromaticity space 1 t1 + t2 =1 t1 possible colors t2 1 Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 NTSC RGB r+g+b=1 1 r+g=1 g 1 r Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Producing Other Colors However colors producible on one system (its color gamut) is not necessarily producible on any other Not that if we produce all the pure spectral colors in the 350-750 nm range, we can produce all others by adding spectral colors With real systems (CRT, film), we cannot produce the pure spectral colors We can project the color solid of each system into chromaticity space (of some system) to see how close we can get Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Color Gamuts 600 nm spectral colors printer colors producible color on CRT but not on printer CRT colors unproducible color 750 nm producible color on both CRT and printer 350 nm Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 XYZ Reference system in which all visible pure spectral colors can be produced Theoretical systems as there are no corresponding physical primaries Standard reference system Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Color Systems Most correspond to real primaries National Television Systems Committee (NTSC) RGB matches phosphors in CRTs Film both additive (RGB) and subtractive (CMY) for positive and negative film Print industry CMYK (K = black) K used to produce sharp crisp blacks Example: ink jet printers Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Color Transformations Each additive color system is a linear transformation of another G’ G C = (T1, T2, T3) = (T’1, T’2, T’3) R’ in R’G’B’system R B B’ in RGB system Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 RGB, CMY, CMYK Assuming 1 is max of a primary C = 1 – R M = 1 – G Y = 1 – B Convert CMY to CMYK by K = min(C, M, Y) C’ = C – K M’ = M – K Y’ = Y - K Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Color Matrix Exists a 3 x 3 matrix to convert from representation in one system to representation in another Example: XYZ to NTSC RGB find in colorimetry references Can take a color in XYZ and find out if it is producible by transforming and then checking if resulting tristimulus values lie in (0,1) Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 YIQ NTSC Transmission Colors Here Y is the luminance Arose from need to separate brightness from chromatic information in TV broadcasting Note luminance shows high green sensitivity Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Other Color Systems UVW: equal numerical errors are closer to equal perceptual errors HLS: perceptual color (hue, saturation, lightness) Polar representation of color space Single and double cone versions Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009

Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009 Gamma Intensity vs CRT voltage is nonlinear I = cVg Can use a lookup table to correct Human brightness response is logarithmic Equal steps in gray levels are not perceived equally Can use lookup table CRTs cannot produce a full black Limits contrast ratio Angel: Interactive Computer Graphics 5E © Addison-Wesley 2009