CSE 332/564: Visualization

Fundamentals of Color

Kl M llKlaus Mueller

Computer Science Department

Stony Brook University

Perception of Light Intensity

How Many Intensity Levels Do We Need? Dynamic Intensity Range Issues

D i f th t l ldDynamic range of the natural world:

100 000 000:1

Dynamic range the eye can accommodate in a single view:

10 000:1

Dynamic range a typical monitor can display:

100:1100:1

D i t i l tDynamic range a typical camera can capture:

100:1

Long Camera Exposure

captured the interior well, but the outside is too bright…

Short Camera Exposure

captured the outside well, but now the interior is dark…

Medium Camera Exposure

everything is somewhat present, but not very detailed

What Now…

OK h th i th t h t d ll thOK.. now we have three images that have captured all the detail of the scene• but we want to visualize it all in one picture, not three• we need some way to merge these three pictures• this is the domain of High Dynamic Range Imaging (HDR)

How does HDR work?How does HDR work?

Two methods:• somehow compress the large range into a small displayable rangesomehow compress the large range into a small, displayable range• look at small neighborhoods and try to maximize contrast in each• the first is a global method, the second is a local method

This is also often called tone mapping

Another application of HDR:• computational datasets are often computed in floating point precision• HDR can be used to compress the floating point images into 8-bit

Methods

Gl b l th dGlobal methods: • scale each pixel according to a fixed curve• the key issue is here: the shape of the curve

Local methods: • group small neighborhoods by their average value• scale these averages down• add detail back in

Comparison: Global Method

Comparison: Local Method Result With Earlier Example

References

HDR h b l t h iHDR has become a popular technique

Some of the key HDR researchers are:• P Debevec E Reinhard G Ward M Ashikhmin J Tumblin and• P. Debevec, E. Reinhard, G. Ward, M. Ashikhmin, J. Tumblin, and

others• for use of HDR in scientific visualization, see X. Yuan, M. Nguyen, B.

Chen and D Porter “High Dynamic Range Volume Visualization ”Chen and D. Porter, High Dynamic Range Volume Visualization, IEEE Transaction on Visualization and Computer Graphics, vol. 12, no. 4, 2006.

Image examples were taken from http://www hdrsoft comImage examples were taken from http://www.hdrsoft.com

Back to The Optical Illusion Example

Explanation

Whil th ti i hi h f i t iti itWhile the retina can perceive a high range of intensities, it cannot handle all simultaneously• at any given time, each region adapts to a small intensity range

determined by the local intensity• that is why you have to wait a while when you step from a bright into

a dark room (say, a dark movie theater from a brightly lit lobby)

after moving the eye:eventually adapted

eventually the bright area intensity is unsaturated, matches neighborhood

current adapted ft i th

eventually adapted range

g(which was already adapted

here before)

current adapted range

after moving the eye:new bright area saturates

intensity perception

current dark area in picture falls here

Spectrum of Wavelengths

Perception Curves

color generation with primarieshuman color sensitivity curves

g p

Perceptional Color Spaces

Use Of The CIE Chromaticity Diagram The Munsell Perceptional Color Space

Th (i l l h d) M ll t h 3The (irregularly shaped) Munsell tree has 3 axes:• chroma (saturation): distance from the core (values 0-30, with

fluorescent colors having the maximum 30)• value (brightness): vertical axis (0– 10 (white))• hue: 10 principal hues (R, YR, Y, GY, G, BG,

B, PB, P, RP)

Non-Perceptional Color Spaces

bluemagenta

cyan

green

white

red

yellowRGB

HSV

y

compare to: CIE LAB in 3D

Application: Colorization of Grey-Level Images

Application: Colorization of Grey-Level Images

imovie:

Application: Colorization of Grey-Level Images

movie:

References

M i f tiMore information:• T. Welsh, M. Ashikhmin, and K. Mueller, "Transferring color to

greyscale images," ACM Transactions on Graphics (Proc. of SIGGRAPH'02) vol 21 no 3 pp 277 280 2002SIGGRAPH'02), vol. 21, no. 3, pp. 277-280, 2002.

More on Color

More on Color More on Color

Use of Color Luminance Contrast

Luminance Contrast Color Contrast and Harmony

Color Constancy

A h h i l hA psychophysical phenomenon:• accounts for the ability of humans to accurately perceive the "color" of

an object under different lighting conditions • lighting, or illumination, may vary both over a viewed scene and over

time yet the perceived color is constant• in fact, constant illumination over a scene is almost never

encountered in real lifeencountered in real life

Given an object, the colors we perceive (within limits) remain the same, even though… • the spectral content ("color") of sunlight varies greatly through the day

and with weather conditions• artificial light sources also vary greatly from g y g y

one to another

Color Constancy: Example

illuminant A illuminant B illuminant C

Chromatic Aberration

from: J. Döllner, U Potsdam

Why Color? … Color Adds More Dimensions

from: M. Stone

Color Adds Aesthetics

from: M. Stone

But… Mapping to Color Can Cause Problems

from: M. Stone

Color Maps

from: Rogowitz/Treinish

Color Map: Segmentation Tasks

from: Rogowitz/Treinish

Color Map: Rainbow

from: Rogowitz/Treinish

Color Map: Linear Hue

from: Rogowitz/Treinish

Color Maps: Spatial Frequency Issues

from: Rogowitz/Treinish

Color Maps: Low vs. High Frequency

weather modellow frequency

radar scanhigh frequency

from: Rogowitz/Treinish

Color Maps: Highlighting

from: Rogowitz/Treinish

Brewer Scale

N i l lNominal scales• distinct hues, but similar emphasis

Sequential scalesSequential scales• vary in lightness and saturation• vary slightly in hue

Diverging scale• complementary sequential scales• neutral at “zero”neutral at zero

from: M. Stone (see also colorbrewer.org)

Brewer Scales

from: M. Stone (see also colorbrewer.org)

Example for Proper Use of Color

References

M St A Fi ld G id t Di it l C l AK P tMaureen Stone, A Field Guide to Digital Color, AK Peters 2003• color perception and design with color

Colin Ware, Perception and Information Visualization: 2nd

Edition, Morgan Kaufman, 2004b k ifi ll d t d i f ti i li ti• book specifically geared towards information visualization

Bernice Rogowitz and Lloyd Treinish, “An architecture for perceptual rule-based visualization,” Proc. IEEE p p ,Visualization 1993, pp. 236-243, 1993• see also

http://www research ibm com/dx/proceedings/pravda/index htmhttp://www.research.ibm.com/dx/proceedings/pravda/index.htmhttp://www.research.ibm.com/dx/proceedings/pravda/truevis.htm

Color brewer: http://www.colorbrewer.org