The Elements of Colour

Similar documents
CS635 Spring Department of Computer Science Purdue University

Spectral Color and Radiometry

Digital Image Processing COSC 6380/4393. Lecture 19 Mar 26 th, 2019 Pranav Mantini

Introduction to color science

Reading. 2. Color. Emission spectra. The radiant energy spectrum. Watt, Chapter 15.

Electromagnetic waves and power spectrum. Rays. Rays. CS348B Lecture 4 Pat Hanrahan, Spring 2002

Computer Graphics. Bing-Yu Chen National Taiwan University The University of Tokyo

The Display pipeline. The fast forward version. The Display Pipeline The order may vary somewhat. The Graphics Pipeline. To draw images.

CSE 167: Lecture #6: Color. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2012

Digital Image Processing

CSE 167: Lecture #6: Color. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2011

Why does a visual system need color? Color. Why does a visual system need color? (an incomplete list ) Lecture outline. Reading: Optional reading:

Color. Reading: Optional reading: Chapter 6, Forsyth & Ponce. Chapter 4 of Wandell, Foundations of Vision, Sinauer, 1995 has a good treatment of this.

Image Formation. Camera trial #1. Pinhole camera. What is an Image? Light and the EM spectrum The H.V.S. and Color Perception

ECE-161C Color. Nuno Vasconcelos ECE Department, UCSD (with thanks to David Forsyth)

Digital Image Processing. Introduction

Lecture 1 Image Formation.

(0, 1, 1) (0, 1, 1) (0, 1, 0) What is light? What is color? Terminology

Color Vision. Spectral Distributions Various Light Sources

Colour Reading: Chapter 6. Black body radiators

CS452/552; EE465/505. Color Display Issues

Game Programming. Bing-Yu Chen National Taiwan University

Fall 2015 Dr. Michael J. Reale

Lecture 12 Color model and color image processing

Color and Shading. Color. Shapiro and Stockman, Chapter 6. Color and Machine Vision. Color and Perception

Announcements. Lighting. Camera s sensor. HW1 has been posted See links on web page for readings on color. Intro Computer Vision.

Image Analysis and Formation (Formation et Analyse d'images)

Image Formation. Ed Angel Professor of Computer Science, Electrical and Computer Engineering, and Media Arts University of New Mexico

When this experiment is performed, subjects find that they can always. test field. adjustable field

Measuring Light: Radiometry and Photometry

Physical Color. Color Theory - Center for Graphics and Geometric Computing, Technion 2

Reading. 4. Color. Outline. The radiant energy spectrum. Suggested: w Watt (2 nd ed.), Chapter 14. Further reading:

Chapter 4 Color in Image and Video

Visible Color. 700 (red) 580 (yellow) 520 (green)

Measuring Light: Radiometry and Photometry

CHAPTER 3 COLOR MEASUREMENT USING CHROMATICITY DIAGRAM - SOFTWARE

Introduction to Computer Graphics with WebGL

Lighting. Camera s sensor. Lambertian Surface BRDF

Lecture 11. Color. UW CSE vision faculty

Colour computer vision: fundamentals, applications and challenges. Dr. Ignacio Molina-Conde Depto. Tecnología Electrónica Univ.

Measuring Light: Radiometry and Cameras

Color to Binary Vision. The assignment Irfanview: A good utility Two parts: More challenging (Extra Credit) Lighting.

CSE 167: Lecture #7: Color and Shading. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2011

Color. Computational Photography MIT Feb. 14, 2006 Bill Freeman and Fredo Durand

Color Space Transformations

Chapter 1. Light and color

Image Processing. Color

Color. Phillip Otto Runge ( )

1. Final Projects 2. Radiometry 3. Color. Outline

CSE 167: Introduction to Computer Graphics Lecture #6: Colors. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2013

ITP 140 Mobile App Technologies. Colors

COMP3421. Global Lighting Part 2: Radiosity

Chapter 5 Extraction of color and texture Comunicação Visual Interactiva. image labeled by cluster index

Computer Graphics. Bing-Yu Chen National Taiwan University

Application of CIE with Associated CRI-based Colour Rendition Properties

MODELING LED LIGHTING COLOR EFFECTS IN MODERN OPTICAL ANALYSIS SOFTWARE LED Professional Magazine Webinar 10/27/2015

What is color? What do we mean by: Color of an object Color of a light Subjective color impression. Are all these notions the same?

Pick up Light Packet & Light WS

Light Transport Baoquan Chen 2017

Colorimetric Quantities and Laws

this is processed giving us: perceived color that we actually experience and base judgments upon.

Lecture 2 5 Aug 2004

3D graphics, raster and colors CS312 Fall 2010

Color. making some recognition problems easy. is 400nm (blue) to 700 nm (red) more; ex. X-rays, infrared, radio waves. n Used heavily in human vision

Color, Edge and Texture

Radiometry. Computer Graphics CMU /15-662, Fall 2015

E (sensor) is given by; Object Size

Computer Vision Course Lecture 02. Image Formation Light and Color. Ceyhun Burak Akgül, PhD cba-research.com. Spring 2015 Last updated 04/03/2015

Color Image Processing

Color. Today s Class. Reading for This Week. Reading for This Week. Mid- Term PresentaCons. Today s Class 2/29/12

Announcements. Camera Calibration. Thin Lens: Image of Point. Limits for pinhole cameras. f O Z

VISUAL SIMULATING DICHROMATIC VISION IN CIE SPACE

Causes of color. Radiometry for color

Illumination and Shading

Computer Vision James L. Crowley

INTRODUCTION. Slides modified from Angel book 6e

CS681 Computational Colorimetry

CS770/870 Spring 2017 Color and Shading

ELEC Dr Reji Mathew Electrical Engineering UNSW

Lecture #13. Point (pixel) transformations. Neighborhood processing. Color segmentation

Optics Part 1. Vern Lindberg. March 5, 2013

Lecture #2: Color and Linear Algebra pt.1

Sources, Surfaces, Eyes

Lenses: Focus and Defocus

Physics-based Methods in Vision

Module 3. Illumination Systems. Version 2 EE IIT, Kharagpur 1

Multimedia Information Retrieval

Lecture 1. Computer Graphics and Systems. Tuesday, January 15, 13

Color Appearance in Image Displays. O Canada!

Photometric Stereo.

Siggraph Course 2017 Path Tracing in Production Part 1 Manuka: Weta Digital's Spectral Renderer

2003 Steve Marschner 7 Light detection discrete approx. Cone Responses S,M,L cones have broadband spectral sensitivity This sum is very clearly a dot

OptisWorks. SolidWorks - integrated solutions for the modeling and perception of light

Main topics in the Chapter 2. Chapter 2. Digital Image Representation. Bitmaps digitization. Three Types of Digital Image Creation CS 3570

What is it? How does it work? How do we use it?

Chapter 6 Color Image Processing

CIE L*a*b* color model

Digital Image Processing. Week 4

Lecture 16 Color. October 20, 2016

4. A bulb has a luminous flux of 2400 lm. What is the luminous intensity of the bulb?

Transcription:

Color science 1

The Elements of Colour Perceived light of different wavelengths is in approximately equal weights achromatic. <3% from black object. Reflected light perceived as colour 2

Colorimétrie et perception Œil humain «Optique» Cônes et bâtonnets

Colorimétrie Physiologie Ganglion Cells Bipolar Cells Horizontal Cells Rod Cone Light Light Amacrine Cells Retina Optic Nerve

Colorimétrie De la physiologie à la physique

Colorimétrie Physique et physiologie L œil sensible à la Luminance Du fait de l optique de l œil Sensibilité dépend de la longueur d onde L(λ)

Colorimétrie Deux types de vison Scotopique Nocturne Dénuée d impression colorée Photopique Diurne Impression colorée

The Visible Spectrum 8

Photons The basic quantity in lighting is the photon The energy (in Joule) of a photon with wavelength λ is: q λ = hc / λ c is the speed of light In vacuum, c = 299.792.458m/s h 6.63*10-34 Js is Planck s constant 9

Radiometry and Photometry 10

Radiant Energy and Power Power: Watts vs. Lumens Energy per unit time Φ Spectral Energy: Joules vs. Talbot Exposure Film response Skin - sunburn 11

(Spectral) Radiant Energy The spectral radiant energy, Q λ, in n λ photons with wavelength λ is Q = n λ λ The radiant energy, Q, is the energy of a collection of photons, and is given as the integral of Q λ over all possible wavelengths: Q q λ = Q λ λ d 0 12

Radiometry vs. Photometry Radiometry [Units = Watts] Physical measurement of electromagnetic energy Photometry and Colorimetry [Lumen] Sensation as a function of wavelength Relative perceptual measurement Brightness, Lightness [Brils] Sensation at different brightness levels Absolute perceptual measurement Obeys Steven s Power Law B = Y 1 3 13

Radiance Definition: The surface radiance (luminance) is the intensity per unit area leaving a surface Lxω (, ) dω L(x,ω) = d 2 Φ(x,ω) dωda da W cd lm = = nit 2 2 2 sr m m sr m 14

Radiometry vs. Photometry Radiometry and photometry Photometric quantity = product of the radiometric quantity by the luminous efficiency V (λ) Y = V( λ) L( λ) dλ 15

Daylight Vision UV Clear Sky Pat Hanrahan. 16

17 Human Colour Vision There are 3 light sensitive pigments in your cones (L,M,S), each with different spectral response curve. = = = ) ( ) ( ) ( ) ( ) ( ) ( λ λ λ λ λ λ E S S E M M E L L Pat Hanrahan.

Colour Matching is Linear! Grassman s Laws Scaling the colour and the primaries by the same factor preserves the match : 2C=2R+2G+2B To match a colour formed by adding two colours, add the primaries for each colour C 1 +C 2 =(R 1 +R 2 )+(G 1 +G 2 )+(B 1 +B 2 ) 18

Spectral Matching Curves Match each pure colour in the visible spectrum with the 3 primaries, and record the values of the three as a function of wavelength. Red, Green & Blue primaries. Note : We need to specify a negative amount of one primary to represent all colours. 19

Luminance Compare colour source to a grey source Luminance Y =.30R +.59G +.11B Colour signal on a B&W TV (Except for gamma, of course) Perceptual measure : Lightness L = Y 1/3 20

CIE Colour Space For only positive mixing coefficients, the CIE (Commission Internationale d Eclairage) defined 3 new hypothetical light sources x, y and z (as shown) to replace red, green and blue. Primary Y intentionally has same response as luminance response of the eye. The weights X, Y, Z form the 3D CIE XYZ space (see next slide). 21

CIE-XYZ Color Space Color-matching curves x(λ) y(λ) z(λ) 22

Chromaticity Diagram CIE Colour Coordinates & X # & 2. 77 1. 75 1. 13# & R $ Y! $! $ $! = $ 1. 00 4. 59 0. 06! $ G $ % Z!" $ % 0. 00 0. 57 5. 59! " $ % B X x = X + Y + Z Y y = X + Y + Z Z z = X + Y + Z λ λ λ #!!!" Normalise by the total amount of light energy. Often convenient to work in 2D colour space, so 3D colour space projected onto the plane X+Y+Z=1 to yield the chromaticity diagram. The projection is shown opposite and the diagram appears on the next slide. 23

CIE Chromaticity Diagram C is white and close to x=y=z=1/3 E F D The dominant wavelength of a colour, eg. B, is where the line from C through B meets the spectrum, 580nm for B (tint). i A k C B j A and B can be mixed to produce any colour along the line AB here including white. True for EF (no white this time). True for ijk (includes white) 24

The Colors in the Chromaticity Diagram Spectrally pure colors (monochromatic or prismatic) on the contour Visible spectrum Neutral illuminant white Non-spectral colors (purples and magentas) no dominant wavelength 25

Perceptually Uniform Space: MacAdam In color space CIE-XYZ, the perceived distance between colors is not equal everywhere In perceptually uniform color space, Euclidean distances reflect perceived differences between colors MacAdam ellipses (areas of unperceivable differences) become circles 26 Source: [Wyszecki and Stiles 82]"

Some device colour gamuts C The diagram can be used to compare the gamuts of various devices. Note particularly that a colour printer can t reproduce all the colours of a colour monitor. Note no triangle can cover all of visible space. 27

Colour Cube R,G,B model is additive, i.e we add amounts of 3 primaries to get required colour. Can visualize RGB space as cube, grey values occur on diagonal K to W. 28

Intuitive Colour Spaces Hexagon is a diagonal Cross-Section of the 3D Colour Cube. 29

Espace de couleurs : RGB Gamme de couleur Lieu du spectre visible Diagramme de chromaticité r = R /(R+G+B) g = G /(R+G+B) b = B/(R+G+B)

Espaces de couleurs : RGB RGB et spectrum locus Ensemble des couleurs pures observables

The HSV Colour Space V Green 120 Yellow Cyan 1.0 Red 0 H Hue, or the colour of the pure pigment. Blue 240 Magenta S Saturation of the colour. V Value, or brightness. Black 0.0 H S If V = 0, H is Undefined. 32

The HSL (HSB) Colour Space 1.0 L White H Hue, or the colour of the pure pigment, angle around the axis. Cyan Green 120 0.5 Yellow Red 0 S Saturation of the colour, distance from the axis. a measure of the "purity" of a hue. As saturation is decreased, the hue becomes more gray. A saturation value of zero results in a gray-scale value. Blue 240 Magenta L Lightness, or brightness, distance along the axis. Black 0.0 H S 33 If L = 0,1 H is Undefined. Maximum saturation occurs when L = 0.5

The HSL (HSB) Colour Space H Hue, or the colour of the pure pigment, angle around the axis. S Saturation of the colour, distance from the axis. a measure of the "purity" of a hue. As saturation is decreased, the hue becomes more gray. A saturation value of zero results in a gray-scale value. L Lightness, or brightness, distance along the axis. If L = 0,1 H is Undefined. 34 Maximum saturation occurs when L = 0.5

Color Pickers: HSL Apple s HLS wheel 35

CMYK Subtractive Colour Model R = (1-C) (1-K) W G = (1-M) (1-K) W B = (1-Y) (1-K) W K = G(1-max(R,G,B)) C = 1 - R/(1-K) M = 1 - G/(1-K) Y = 1 - B/(1-K) 36

CIE-LAB 37 Source: [Wyszecki and Stiles 82]"

Gamut Mapping CIE-LAB Color gamut of different processes may be different (e.g. CRT display and 4- color printing process) Need to map one 3D color space into another Perceptually-uniform Color space Typical CRT gamut 4-color printing gamut 38

Gamut Mapping Typical CRT gamut 4-color CMYK printing gamut b* a* 39

Device-Dependent Color 40 http://www.color.org/"

Device-Independent Color 41 http://www.color.org/"

Colour, Physics & Light - Summary Humans have tri-chromatic vision. All visible colours represented in CIE colour diagram. No three selected primaries in CIE colour space can generate all visible colours. Intuitive colour spaces. Subtractive colour models for hard copy. 42