CS 551 / 645: Introductory Computer Graphics

Color

Administrivia

Changes to assignment 2 Today’s reading material: FvD, Chapter 13 Final Exam

– Monday, December 11th, 2000– 7:00 - 10:00 p.m.– MEC 339– Check your schedule for collisions ASAP!– You will collide if you are taking any of the following:

APMA 109, 111; ITAL 101, 102; LATI 103, 201, 202 SPAN 101, 102, 201, 202

Assignment 2 For use on Windows box

– change .C extension to .cpp extension– remove unistd.h inclusion– remove GL.h and GLU.h inclusion. glut.h includes

these– No memory deallocation eats through memory. If you

care, add deallocation to the ESCAPE key handler. sgi-10 is screwed up. You can compile on another

SGI and run on sgi-10, though Don’t worry about the cat or horse Do zooming with up/down. Ignore left/right.

Assignment 2

Euler angle rotations are bad– Rotate about x, followed by rotate about y,

followed by rotate about z– Example:

Rotate 180 degrees about x A rotation about y will turn in the opposite direction you

expect

You can leave the code the way it is now. We will fix it in future assignments

Color

Next topic: Color

To understand how to make realistic images, we need a basic understanding of the physics and physiology of vision. Here we step away from the code and math for a bit to talk about basic principles.

Basics Of Color

Elements of color:

Basics of Color

Physics: – Illumination

Electromagnetic spectra

– Reflection Material properties Surface geometry and microgeometry (i.e., polished

versus matte versus brushed)

Perception– Physiology and neurophysiology– Perceptual psychology

Physiology of Vision

The eye: The retina

– Rods– Cones

Color!

Physiology of Vision

The center of the retina is a densely packed region called the fovea. – Cones much denser here than the periphery

Physiology of Vision: Cones

Three types of cones:– L or R, most sensitive to red light (610 nm) – M or G, most sensitive to green light (560 nm)– S or B, most sensitive to blue light (430 nm)

– Color blindness results from missing cone type(s)

Physiology of Vision: The Retina

Strangely, rods and cones are at the back of the retina, behind a mostly-transparent neural structure that collects their response.

Perception: Metamers

A given perceptual sensation of color derives from the stimulus of all three cone types

Identical perceptions of color can thus be caused by very different spectra

Perception: Other Gotchas

Color perception is also difficult because:– It varies from person to person– It is affected by adaptation (stare at a light bulb… don’t)– It is affected by surrounding color:

Perception: Relative Intensity

We are not good at judging absolute intensity Let’s illuminate pixels with white light on

scale of 0 - 1.0 Intensity difference of neighboring colored

rectangles with intensities:– 0.10 -> 0.11– 0.50 -> 0.55

will look the same We perceive relative intensities, not absolute

Representing Intensities

Remaining in the world of black and white… Use photometer to obtain min and max

brightness of monitor This is the dynamic range Intensity ranges from min, I0, to max, 1.0 How do we represent 256 shades of gray?

Representing Intensities

Equal distribution between min and max fails– relative change near max is much smaller than near

I0

I0 = I0, I1 = rI0, I2 = rI1= r2I0,…, I255 = rI254 = r255I0

Ex: 4 intensities– 1/8, 1/4, 1/2, 1

Dynamic Ranges

Dynamic Range Max Perceived Display (max / min illum) Intensities, r=1.01

CRT: 50-200 400-530 Photo (print) 100 465 Photo (slide) 1000 700 B/W printout 100 465 Color printout 50 400 Newspaper10 234

Gamma Correction

But most display devices are inherently nonlinear: Intensity = k(voltage)

– I.e., brightness(voltage) != 2*brightness(voltage/2) is between 2.2 and 2.5 on most monitors

Common solution: gamma correction– Post-transformation on intensities to map them to

linear range on display device:– Can have separate for R, G, B

1

xy

Gamma Correction

Some monitors perform the gamma correction in hardware (SGI’s)

Others do not (most PCs) Tough to generate images that look good on

both platforms (i.e. images from web pages)

Halftoning

A technique used in newspaper printing Only two intensities are possible, blob of ink

and no blob of ink But, the size of the blob can be varied Also, the dither patterns of small dots can be

used

Back to color

Color is defined many ways Computer scientists frequently use:

– Hue - The color we see (red, green, purple)– Saturation - How far is the color from gray (pink is

less saturated than red, sky blue is less saturated than royal blue)

– Brightness - How bright is the color

How well do we see color?

What color do we see the best?– Yellow-green at 550 nm

What color do we see the worst?– Blue at 440 nm

Flashback: Colortables (colormaps) for color storage

Can perceive color differences of 10 nm at extremes (violet and red) and 2 nm between blue and yellow

How well do we see color?

128 fully saturated hues can be distinguished Cannot perceive hue differences with less

saturated light. Sensitivity to changes in saturation for a fixed

hue and brightness ranges from 23 to 16 depending on hue.

Color Spaces

Three types of cones suggests color is a 3D quantity. How to define 3D color space?

Idea: shine given wavelength () on a screen, and mix three other wavelengths (R,G,B) on same screen. Have user adjust intensity of RGB until colors are identical:

CIE Color Space

The CIE (Commission Internationale d’Eclairage) came up with three hypothetical lights X, Y, and Z with these spectra:

Idea: any wavelength can be matched perceptually by positive combinations of X,Y,Z

Note that:X ~ R

Y ~ G

Z ~ B

CIE Color Space

The gamut of all colors perceivable is thus a three-dimensional shape in X,Y,Z:

For simplicity, we often project to the 2D plane X+Y+Z=1X = X / (X+Y+Z)

Y = Y / (X+Y+Z)

Z = 1 - X - Y

CIE Chromaticity Diagram (1931)

Device Color Gamuts

Since X, Y, and Z are hypothetical light sources, no real device can produce the entire gamut of perceivable color

Example: CRT monitor

Device Color Gamuts

The RGB color cube sits within CIE color space something like this:

Device Color Gamuts

We can use the CIE chromaticity diagram to compare the gamuts of various devices:

Note, for example, that a color printercannot reproduceall shades availableon a color monitor

Converting Color Spaces

Simple matrix operation:

The transformation C2 = M-12 M1 C1 yields

RGB on monitor 2 that is equivalent to a given RGB on monitor 1

B

G

R

ZZZ

YYY

XXX

B

G

R

BGR

BGR

BGR

'

'

'

Converting Color Spaces Converting between color models can also be

expressed as such a matrix transform:

Note the relative unimportance of blue in computing the Y

YIQ is the color model used for color TV in America. Y is luminance, I & Q are color– Note: Y is the same as CIE’s Y

– Result: backwards compatibility with B/W TV!

B

G

R

Q

I

Y

31.052.021.0

32.028.060.0

11.059.030.0

HSV Color Space

A more intuitive color space– H = Hue– S = Saturation– V = Value (or brightness)