IFT3355: Infographie Couleur. Victor Ostromoukhov, Pierre Poulin Dép. I.R.O. Université de Montréal

Similar documents
COLOR and the human response to light

COLOR. and the human response to light

Raster Graphics. Overview קורס גרפיקה ממוחשבת 2008 סמסטר ב' What is an image? What is an image? Image Acquisition. Image display 5/19/2008.

קורס גרפיקה ממוחשבת 2008 סמסטר ב' Raster Graphics 1 חלק מהשקפים מעובדים משקפים של פרדו דוראנד, טומס פנקהאוסר ודניאל כהן-אור

19. Vision and color

Color & Graphics. Color & Vision. The complete display system is: We'll talk about: Model Frame Buffer Screen Eye Brain

Further reading. 1. Visual perception. Restricting the light. Forming an image. Angel, section 1.4

Reading. Lenses, cont d. Lenses. Vision and color. d d f. Good resources: Glassner, Principles of Digital Image Synthesis, pp

Image and video processing (EBU723U) Colour Images. Dr. Yi-Zhe Song

Colors in Images & Video

Reading. 1. Visual perception. Outline. Forming an image. Optional: Glassner, Principles of Digital Image Synthesis, sections

Vision and Color. Reading. Optics, cont d. Lenses. d d f. Brian Curless CSE 557 Autumn Good resources:

Vision and Color. Brian Curless CSE 557 Autumn 2015

Reading. Foley, Computer graphics, Chapter 13. Optional. Color. Brian Wandell. Foundations of Vision. Sinauer Associates, Sunderland, MA 1995.

Vision and Color. Reading. The lensmaker s formula. Lenses. Brian Curless CSEP 557 Autumn Good resources:

To discuss. Color Science Color Models in image. Computer Graphics 2

Vision and Color. Reading. Optics, cont d. Lenses. d d f. Brian Curless CSEP 557 Fall Good resources:

Vision and Color. Brian Curless CSEP 557 Fall 2016

CS 565 Computer Vision. Nazar Khan PUCIT Lecture 4: Colour

Victor Ostromoukhov Université de Montréal. Victor Ostromoukhov - Université de Montréal

Color and Color Model. Chap. 12 Intro. to Computer Graphics, Spring 2009, Y. G. Shin

Vision and color. University of Texas at Austin CS384G - Computer Graphics Fall 2010 Don Fussell

CIE tri-stimulus experiment. Color Value Functions. CIE 1931 Standard. Color. Diagram. Color light intensity for visual color match

Color. Color. Colorfull world IFT3350. Victor Ostromoukhov Université de Montréal. Victor Ostromoukhov - Université de Montréal

Visual Perception. Overview. The Eye. Information Processing by Human Observer

Color Science. CS 4620 Lecture 15

Colour. Why/How do we perceive colours? Electromagnetic Spectrum (1: visible is very small part 2: not all colours are present in the rainbow!

CMPSCI 670: Computer Vision! Color. University of Massachusetts, Amherst September 15, 2014 Instructor: Subhransu Maji

Color Image Processing

Colour. Electromagnetic Spectrum (1: visible is very small part 2: not all colours are present in the rainbow!) Colour Lecture!

Multimedia Systems Color Space Mahdi Amiri March 2012 Sharif University of Technology

COLOR. Elements of color. Visible spectrum. The Fovea. Lecture 3 October 30, Ingela Nyström 1. There are three types of cones, S, M and L

Color and Perception. CS535 Fall Daniel G. Aliaga Department of Computer Science Purdue University

The Principles of Chromatics

Mahdi Amiri. March Sharif University of Technology

Vision. The eye. Image formation. Eye defects & corrective lenses. Visual acuity. Colour vision. Lecture 3.5

Digital Image Processing Color Models &Processing

Multimedia Systems and Technologies

LECTURE 07 COLORS IN IMAGES & VIDEO

University of British Columbia CPSC 314 Computer Graphics Jan-Apr Tamara Munzner. Color.

Color Image Processing

Colour. Cunliffe & Elliott, Chapter 8 Chapman & Chapman, Digital Multimedia, Chapter 5. Autumn 2016 University of Stirling

Reading for Color. Vision/Color. RGB Color. Vision/Color. University of British Columbia CPSC 314 Computer Graphics Jan-Apr 2013.

Introduction. The Spectral Basis for Color

the eye Light is electromagnetic radiation. The different wavelengths of the (to humans) visible part of the spectra make up the colors.

COLOR. Elements of color. Visible spectrum. The Human Visual System. The Fovea. There are three types of cones, S, M and L. r( λ)

12/02/2017. From light to colour spaces. Electromagnetic spectrum. Colour. Correlated colour temperature. Black body radiation.

The human visual system

Digital Image Processing

Color Science. What light is. Measuring light. CS 4620 Lecture 15. Salient property is the spectral power distribution (SPD)

Image Processing for Mechatronics Engineering For senior undergraduate students Academic Year 2017/2018, Winter Semester

Light. intensity wavelength. Light is electromagnetic waves Laser is light that contains only a narrow spectrum of frequencies

Human Vision, Color and Basic Image Processing

Visual Imaging and the Electronic Age Color Science

Digital Image Processing

University of British Columbia CPSC 414 Computer Graphics

Bettina Selig. Centre for Image Analysis. Swedish University of Agricultural Sciences Uppsala University

Wireless Communication

For a long time I limited myself to one color as a form of discipline. Pablo Picasso. Color Image Processing

Color and Color Models

Color. Computer Graphics CMU /15-662

Visual Perception. human perception display devices. CS Visual Perception

IMAGE PROCESSING >COLOR SPACES UTRECHT UNIVERSITY RONALD POPPE

Lecture 3: Grey and Color Image Processing

Digital Image Processing COSC 6380/4393. Lecture 20 Oct 25 th, 2018 Pranav Mantini

Color Image Processing. Gonzales & Woods: Chapter 6

Color and perception Christian Miller CS Fall 2011

Introduction to Computer Vision and image processing

Human Visual System. Prof. George Wolberg Dept. of Computer Science City College of New York

Computer Graphics Si Lu Fall /27/2016

excite the cones in the same way.

Lecture 8. Color Image Processing

Light and Colour. Light as part of the EM spectrum. Light as part of the EM spectrum

The Science Seeing of process Digital Media. The Science of Digital Media Introduction

Understand brightness, intensity, eye characteristics, and gamma correction, halftone technology, Understand general usage of color

Prof. Feng Liu. Winter /09/2017

Color Perception. Color, What is It Good For? G Perception October 5, 2009 Maloney. perceptual organization. perceptual organization

III: Vision. Objectives:

USE OF COLOR IN REMOTE SENSING

Introduction to Color Science (Cont)

Problems. How do cameras measure light and color? How do humans perceive light and color?

Chapter 3 Part 2 Color image processing

Visual Perception. Readings and References. Forming an image. Pinhole camera. Readings. Other References. CSE 457, Autumn 2004 Computer Graphics

Werner Purgathofer

Color. Bilkent University. CS554 Computer Vision Pinar Duygulu

Lecture Color Image Processing. by Shahid Farid

Color Theory: Defining Brown

Andrea Torsello DAIS Università Ca Foscari via Torino 155, Mestre (VE) Color Vision

Visual Perception. Jeff Avery

Chapter 9: Light, Colour and Radiant Energy. Passed a beam of white light through a prism.

The Human Visual System. Lecture 1. The Human Visual System. The Human Eye. The Human Retina. cones. rods. horizontal. bipolar. amacrine.

Fig Color spectrum seen by passing white light through a prism.

Reading instructions: Chapter 6

Lighting: Basic Concepts

Introduction & Colour

Achim J. Lilienthal Mobile Robotics and Olfaction Lab, AASS, Örebro University

Announcements. Electromagnetic Spectrum. The appearance of colors. Homework 4 is due Tue, Dec 6, 11:59 PM Reading:

Capturing Light in man and machine

Today. Color. Color and light. Color and light. Electromagnetic spectrum 2/7/2011. CS376 Lecture 6: Color 1. What is color?

Chapter 2 Fundamentals of Digital Imaging

Transcription:

IFT3355: Infographie Couleur Victor Ostromoukhov, Pierre Poulin Dép. I.R.O. Université de Montréal

Color Appearance

Visual Range Electromagnetic waves (in nanometres) γ rays X rays ultraviolet violet red infrared radar FM radio 10 3 0 10 2 10 380 780 4 10 6 10 9 10 14 10 Color corresponds to an electromagnetic wave between 380 and 780 nm

Color as a Spectral Distribution of Intensities

Structures of the Human Eye - Cornea Clear coating over the front of the eye Protects the eye and initial focusing 40 D (curvature + refraction) Strongest focusing element in the eye

Structures of the Human Eye - Lens Crystalline lens Ciliary muscles tense to compress (rounder) the lens uncompressed : far focus compressed : near focus Accommodation ability of lens to stretch (elasticity) 10-30 D in children after 45 years, most elasticity is lost

Crystalline

Structures of the Human Eye - Retina

Structures of the Human Eye - Retina

Rods / Cones Rods 10x more sensitive than cones night vision (scotopic) beyond a certain intensity, rods are completely saturated no synaptic chemicals released Cones typical daylight day vision (photopic) when adapted, cones react like rods wrt saturation

Structures of the Human Eye - Fovea Center of visual axis 1-2 degree of visual angle Roughly radially symetric around fovea Contains only cones 147,000 cones/mm

Structures of the Human Eye - Retina Rods increase when moving away from fovea At edge of fovea, more rods than cones Further away, rods form rings around cones Highest rod density at 20 degree from fovea point Photoreceptors diminish when moving away from fovea Visual acuity at fovea, less precision away 120 million rods / 6 million cones

Structures of the Human Eye - Optic Nerve 1 million fibers : eye does some processing before signal reaches the brain Blind spot no photoreceptors completion process

Structures of the Human Eye - Eye Shape Cornea + lens = 60-80 D With 24 mm, only 42 D is needed compensating for the imperfect shape of the eye Corrective lenses Myopic near-sighted, focus in front of retina Hyperopic far-sighted, focus behind retina

Cones 3 types of cones in human eye S 420 nm M 530 nm L 560 nm Bell-shaped curves No S cones in very center of fovea

Color Blindness

Color Blindness Rainbow colors Protanopia No Red Deuteranopia Only 2 Cones Tritanopia No Blue Only 2 Cones

Reaction to Light One photon is enough to produce a chemical reaction Info transmitted by the cone or rod is the stimulation, but not the associated wavelength Spatial vs. spectral density more types of cones takes more space less types of cones requires to reconstruct the spectrum some birds have 5-7 types of cones

Temporal Smoothing Flicker disappears at 60 Hz in best conditions 300 Hz for a bee

Adaptation Eye responds to enormous variations in levels of incoming light moonless overcast night twilight clear day snow in sunlight 0.00003 3 3,000 16,000 candelas / m 2

Luminous Efficiency Curves

Metamerism

Metamerism

Visual Phenomena - Contrast Sensitivity Eye is sensitive to intensity ratios, not absolute values Adaptation plays an important role in contrast sensitivity I ΔI/I I+ΔI I ΔI : just noticeable difference ratio ΔI/I (Weber fraction) is nearly at 0.02 over a range of intensities

Visual Phenomena - Mach Bands Variously emphasizes edges or suggests edges where the signal changes smoothly Regions of high changes and high first derivatives

Visual Phenomena - Lightness Contrast Lightness of a region seems to depend on surrounding intensity Difficulty to pick a color that will appear the same throughout the picture, but the eye is used to that Color constancy : change illumination but keep the same mental image of the scene

Color Appearance, Color Constancy

Color Appearance

Visual Phenomena - CSF (contrast spatial frequency?)

Factors Affecting the Visual System Response Adaptation of eye Psychological processing Frequency and distribution of background illumination Image size Frequency and intensity of recent stimuli Fatigue Age Nutrition etc. Hopeless but it isn t that bad!

Color Perception (Three Properties) Hue determined by the dominant wavelength red, yellow, purple Saturation distance from grey from the same intensity from neutral to vivid Lightness (luminance) quantity of light the color reflects/transmit brightness for emission

Additive vs. Subtractive Models

Cone Response Functions for S, M, L ( ) S = M = L = λ λ Φ( λ) S( λ)dλ λ Φ( λ) M( λ)dλ Φ( λ) L( λ)dλ For a spectral Φ λ signal, the response of each type of cone corresponds to the integral of the product at each wavelength

Color in 3D Space monochromatic color to match sum of the monochromatic lights CIE 1961 R: 700 nm G: 546.1 nm B: 435.8 nm three primary monochromatic lights

CIE RGB - Tristimulus Values standard observer must add color to color to match Distinguisable colors : Δλ = 4 nm (mostly) Δλ = 2 nm (peaks) Δλ = 10 nm (extremities)

The Color Matching System

CIE XYZ Negative portion of CIE RGB is inconvenient Choose three different primaries : X, Y, Z Y is the same as the luminous efficiency curve

Cone of Colors to CIE Chromaticity Diagram Y Q X + Y + Z =1 X y Z x

The Colors in the Chromaticity Diagram Spectrally pure colors (monochromatic) on the contour 520 700 Visible spectrum 400 Neutral illuminant white (sun, D6500, etc.) Non-spectral colors (purples and magentas) no dominant wavelength

Chromaticity Diagram C D A B A: color D: illuminant B: dominant wavelength of A C: complementary color of A (can be mixed with A to give white) AD BD : purity of A

Chromaticity Diagram - White

Color Gamut AB: all colors defined by a mix of colors A and B B D A ABC: all colors defined by a linear combination of A, B, and C C Three visible colors cannot produce all visible colors Gamut is formed by a convex polygon with primaries at the vertices

Color Gamut Each medium has it own color gamut Mapping from one gamut to another (for relative fidelity) is a difficult problem

Gamut Mapping

Gamut Mapping

Gamut Mapping Given two arbitrary gamuts projection over-saturation linear transformations lost of contrasts shift in the colors (e.g., skin) Must maintain color relationships

Many Ancestors to Experimental Color Spaces

Perceptually Uniform Space: Munsell book of colors 1500 color plates separated by strict perception experiments hue, chroma, value : 9R5/8 Hue lightness chroma

Munsell Hue Munsell Color Space Value Chroma munsell.com

CIE Luv In color space CIE XYZ, the perceived distance between colors (points) is not equal everywhere MacAdam ellipses Encode perceived differences 15:1 differences between radii here, exaggerated by factor of 10

Measured Differences by MacAdam

Measured Differences by MacAdam

Measured Differences by MacAdam

CIE Luv CIE Luv is an attempt to better distribute the colors in a more perceptual fashion Transform CIE XYZ to be more perceptual homogeneous Radii closer to 4:1 L u v * * * uʹ = = 116( Y = 13L * = 13L / Y n 1/3 ( uʹ uʹ ) * n 4 X X + 15Y + 3Z vʹ = ) n ( vʹ vʹ ) 16 for ( Y 9Y X + 15Y + 3Z / Y n > 0.01)

CIE Luv

CIE Luv Larson CIE Lab for textiles developed in parallel

CIE Lab

Color Spaces We need a space to manipulate colors Chromaticity diagram does not provide an intuitive tool to manipulate colors Color spaces based on medium cannot reproduce all visible colors Hardware RGB, CMY, YIQ, HSV, HLS Experiments Ostwald, Munsell, CNS

RGB (monitor) Additive blue (0,0,1) black (0,0,0) white (1,1,1) green (0,1,0) red (1,0,0) Depends on the monitor phosphores clipping produces color shifts and saturation transformations

CMY(K) (printer) magenta (1,0,1) black (0,0,0) white (1,1,1) cyan (0,1,1) cyan R G B = 1 C 1 M 1 Y yellow magenta Subtractive yellow (1,1,0) K = min (C,M,Y) : black ink in 4-color printing

YIQ (NTSC transmission) Y : Y from CIE XYZ (2/3 of the signal) luminance used for black-and-white TVs I : in phase (1/4 of the signal) skin colors Q : quadrature (1/12 of the signal) green-purple Y I Q = 0.299 0.596 0.212 0.587 0.275 0.523 0.114 R 0.321 G 0.311 B convert to grays

HSV - HLS Hue-Saturation-Value / Hue-Lightness-Saturation More intuitive, closer to artist perceptions Cylindrical coordinates C G B Y M Horizontal cut : corners of RGB cube S = 0 : gray S = 1 : saturated color R C G white B S V Y M R white G C gray B L Y S M R black H black H