Colors in images. Color spaces, perception, mixing, printing, manipulating...

Similar documents
Color Image Processing. Gonzales & Woods: Chapter 6

Colors in Images & Video

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

The Principles of Chromatics

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

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

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

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

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

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

LECTURE 07 COLORS IN IMAGES & VIDEO

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

Mahdi Amiri. March Sharif University of Technology

COLOR and the human response to light

Digital Image Processing Color Models &Processing

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

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

Images and Colour COSC342. Lecture 2 2 March 2015

COLOR. and the human response to light

Interactive Computer Graphics

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

Introduction. The Spectral Basis for Color

Figure 1: Energy Distributions for light

Digital Image Processing

Lecture Color Image Processing. by Shahid Farid

Color Theory: Defining Brown

6 Color Image Processing

Color images C1 C2 C3

Unit 8: Color Image Processing

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

Chapter 2 Fundamentals of Digital Imaging

Color Image Processing

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

Hello, welcome to the video lecture series on Digital image processing. (Refer Slide Time: 00:30)

Color Image Processing

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

Lecture 8. Color Image Processing

Color Image Processing EEE 6209 Digital Image Processing. Outline

Digital Image Processing (DIP)

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

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

What is Color. Color is a fundamental attribute of human visual perception.

Chapter 3 Part 2 Color image processing

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 image processing

Color Image Processing. Jen-Chang Liu, Spring 2006

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

Digital Image Processing

Observing a colour and a spectrum of light mixed by a digital projector

Introduction to Color Science (Cont)

Colour (1) Graphics 2

Color. Some slides are adopted from William T. Freeman

Color Image Processing

EECS490: Digital Image Processing. Lecture #12

Color Reproduction. Chapter 6

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

Color vision and representation

Multimedia Systems and Technologies

Digital Image Processing. Lecture # 8 Color Processing

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

Computer Graphics Si Lu Fall /27/2016

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

Visual Imaging and the Electronic Age Color Science

Comparing Sound and Light. Light and Color. More complicated light. Seeing colors. Rods and cones

Announcements. The appearance of colors

Lecture 7Colour. Kristína Lidayová Wednesday 23 October

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

INSTITUTIONEN FÖR SYSTEMTEKNIK LULEÅ TEKNISKA UNIVERSITET

Digital Image Processing Chapter 6: Color Image Processing ( )

Color Science. CS 4620 Lecture 15

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

Color images C1 C2 C3

Thursday, May 19, 16. Color Theory

Wireless Communication

Additive Color Synthesis

12 Color Models and Color Applications. Chapter 12. Color Models and Color Applications. Department of Computer Science and Engineering 12-1

Color. Chapter 6. (colour) Digital Multimedia, 2nd edition

Lecture 3: Grey and Color Image Processing

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

Capturing Light in man and machine

IMAGE PROCESSING >COLOR SPACES UTRECHT UNIVERSITY RONALD POPPE

excite the cones in the same way.

VC 16/17 TP4 Colour and Noise

Color Computer Vision Spring 2018, Lecture 15

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

Werner Purgathofer

Introduction to computer vision. Image Color Conversion. CIE Chromaticity Diagram and Color Gamut. Color Models

Technology and digital images

Color , , Computational Photography Fall 2018, Lecture 7

Digital Image Processing

Chapter 6: Color Image Processing. Office room : 841

Color , , Computational Photography Fall 2017, Lecture 11

Capturing Light in man and machine

MATH 5300 Lecture 3- Summary Date: May 12, 2008 By: Violeta Constantin

In a physical sense, there really is no such thing as color, just light waves of different wavelengths.

Introduction & Colour

Reading instructions: Chapter 6

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

Experiment 10. Color. Observe the transmission properties of the three additive primary color filters and the three subtractive primary color filters.

Transcription:

Colors in images Color spaces, perception, mixing, printing, manipulating... Tomáš Svoboda Czech Technical University, Faculty of Electrical Engineering Center for Machine Perception, Prague, Czech Republic svoboda@cmp.felk.cvut.cz http://cmp.felk.cvut.cz/~svoboda

rather an overview lecture Warning 2/30 pictorial, math kept on minimum knowing keywords you may dig deeper Thanks Wikipedia for many images.

Color Spectrum Color is a human interpretation of a mixture of light with different wavelength λ (projected into a retina or camera photoreceptors). 3/30 Isaac Newton s experiment (1666).

Perception of Light Human eye contains three types color receptor cells, or cones. 4/30 Their sensitivity is a function of wavelength. Three peaks may be approximately identified in BLUE, GREEN, RED. Combination of the responses give us our color perception. tristimulus model of color vision. Marking according to wavelengths S short M medium L long

RGB color model A color point is represented by three numbers [R, G, B] 5/30 [R, G, B] have typically range 0... 255 for most common 8-bit images

RGB color model A color point is represented by three numbers [R, G, B] 5/30 [R, G, B] have typically range 0... 255 for most common 8-bit images

RGB color model A color point is represented by three numbers [R, G, B] 5/30 [R, G, B] have typically range 0... 255 for most common 8-bit images

RGB color model A color point is represented by three numbers [R, G, B] 5/30 [R, G, B] have typically range 0... 255 for most common 8-bit images

RGB color model A color point is represented by three numbers [R, G, B] 5/30 [R, G, B] have typically range 0... 255 for most common 8-bit images

RG only, B zero 6/30

RB only, G zero 7/30

GB only, R zero 8/30

Additive mixing computer screens, TV, projectors 9/30 Primary colors: ones used to define other colors, [R,G,B] Secondary colors: pairwise combination of primaries, [C,M,Y] (Cyan, Magenta, Yellow)

Additive mixing computer screens, TV, projectors 9/30 Primary colors: ones used to define other colors, [R,G,B] Secondary colors: pairwise combination of primaries, [C,M,Y] (Cyan, Magenta, Yellow)

Additive mixing computer screens, TV, projectors 9/30 Primary colors: ones used to define other colors, [R,G,B] Secondary colors: pairwise combination of primaries, [C,M,Y] (Cyan, Magenta, Yellow)

Additive mixing computer screens, TV, projectors 9/30 Primary colors: ones used to define other colors, [R,G,B] Secondary colors: pairwise combination of primaries, [C,M,Y] (Cyan, Magenta, Yellow)

Additive mixing computer screens, TV, projectors 9/30 Primary colors: ones used to define other colors, [R,G,B] Secondary colors: pairwise combination of primaries, [C,M,Y] (Cyan, Magenta, Yellow)

RG only, B zero 10/30

RB only, G zero 11/30

GB only, R zero 12/30

Subtractive mixing it works through light absorption the colors that are seen are from the part of light that is not absorbed paintings, printing,... Primary colors: ones used to define other colors [C,M,Y] Secondary colors: pairwise combination of primaries [R,G,B] 13/30

CMYK model color primaries [C.M,Y] should result black when all mixed together 14/30 in practice, such black is not dense enough K = key (black) is added to the model

CMYK model color primaries [C.M,Y] should result black when all mixed together in practice, such black is not dense enough K = key (black) is added to the model 14/30 CMYK printing

Capturing RGB values We know how to display, print color... 15/30 How to capture? CCD generates output proportionally to amount of energy

Capturing RGB values We know how to display, print color... 15/30 How to capture? CCD generates output proportionally to amount of energy 3CCD camera with separating dichroic beam splitter 3CCD chip camera dichroic prism

Capturing RGB values We know how to display, print color... 15/30 How to capture? CCD generates output proportionally to amount of energy 3CCD camera with separating dichroic beam splitter 3CCD chip camera dichroic prism Good: Color quality, Problem: price...

use one chip 1CCD camera with Bayer filter 16/30 place a selective filter in front of it 2:1:1, 2 to green, human eye is most sensitive to it combine values to make RGB image Demosaicking cheap but the image quality suffers this is, among other things, what makes difference between digital photo cameras

Demosaicking in images 17/30

Demosaicking in images 18/30

Demosaicking result 19/30 Many demosaicking method exist. 1CCD with a filter is still prevailing solution. Few expensive DV cameras in consumer level. A company Foveon found yet another way...

Color from depths 20/30

Capturing color revisited Many demosaicking method exist. 21/30 1CCD with a filter is still prevailing solution. Few expensive DV cameras in consumer level. A company called Foveon found yet another way...

HSV color space Problem in RGB space: How would you create a color according to your design? 22/30 RGB values do not correspond to human thinking about colors We are saying: pure red, deep purple, sky blue...

HSV color space Problem in RGB space: How would you create a color according to your design? 22/30 RGB values do not correspond to human thinking about colors We are saying: pure red, deep purple, sky blue... HSV Hue, Saturation, Value color space Hue is the color type (red, yellow,... ) Saturation refers to color purity or vibrancy Value is the brightness of the color

HSV cone 23/30

Playing with saturation 24/30 original image what a nice autumn!

Playing with saturation 25/30 original image what a sad gray autumn!

Additive mixing revisited Can we, assuming properly chosen [R,G,B], mix any color? 26/30

Additive mixing revisited Can we, assuming properly chosen [R,G,B], mix any color? 26/30 Well, almost any. What is wrong?

Additive mixing revisited Can we, assuming properly chosen [R,G,B], mix any color? 26/30 Well, almost any. What is wrong? Blue and Green makes Cyan. But how to make monochromatic Cyan? blue + green - (little red) = monochromatic cyan but how to make negative values on screens?

What do you need to match any color? 27/30 Color spectrum S(λ) 1 0.8 0.6 0.4 0.2 0 350 400 450 500 550 600 650 700 750 800 wavelength [nm] 1 Table of S(λ) in predefined λ S(λ) = P1 f1(λ)s(λ)dλ + P2 f2(λ)s(λ)dλ + P3 f3(λ)s(λ)dλ which gives us [P 1, P 2, P 3 ] representation. 1 Data tables can downloaded from http://www.cvrl.org

What RGB do you need to match any color? 28/30 3.5 3 color matching functions for the RGB primaries r g b 2.5 2 1.5 1 0.5 0 S(λ) = R 0.5 350 400 450 500 550 600 650 700 750 800 wavelength [nm] r(λ)s(λ)dλ + G g(λ)s(λ)dλ + B 2 b(λ)s(λ)dλ Problem: How to realize devices with negative matching functions? 2 Data tables can downloaded from http://www.cvrl.org

A way out new primary colors CIE XY Z 29/30 2.5 2 color matching functions for the CIE XYZ primaries x y z 1.5 1 0.5 0 S(λ) = X 0.5 350 400 450 500 550 600 650 700 750 800 wavelength [nm] x(λ)s(λ)dλ + Y y(λ)s(λ)dλ + Z 3 z(λ)s(λ)dλ 3 Data tables can downloaded from http://www.cvrl.org

CIE chromaticity diagram 30/30 [x, y] = [ X X + Y + Z, ] Y X + Y + Z

Do we see all colors on the screen? 31/30

No! Do we see all colors on the screen? 31/30 Typical gamut of a CRT monitor

Color spectrum S(λ) 1 0.8 0.6 0.4 0.2 0 350 400 450 500 550 600 650 700 750 800 wavelength [nm]

3.5 3 color matching functions for the RGB primaries r g b 2.5 2 1.5 1 0.5 0 0.5 350 400 450 500 550 600 650 700 750 800 wavelength [nm]

2.5 2 color matching functions for the CIE XYZ primaries x y z 1.5 1 0.5 0 0.5 350 400 450 500 550 600 650 700 750 800 wavelength [nm]