Color Theory

ST Nandasara/ADMTC

2

Contents

Color Theory2D Bitmap Image Theory2D Bitmap Image Processing2D Vector Image Theory

Color Theory

How to manipulate color digitally?

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What is color?

Color = Mixture of various frequency of light Perceptive colors for human eyes

= around 400nm ~ 700nm (wavelength) The number of colors in real world =

Infinite But human eyes cannot distinguish every color

A color =

400 500 600 700

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Visible spectrum

Progressive Rainbow

"visible" light can be broken down into a spectrum that ranges from blue to red in a progressive rainbow

The visible spectrum of lightContinuous optical spectrum (designed for monitors with gamma 1.5).

6Wheel of Color – Visible spectrum

Progressive Rainbow

The visible spectrum of lightBeam of sunlight

A Prism separates the beam of lightInfra red Ultra violet

Red Orange Yellow Green Blue Indigo Violet

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Visible spectrum Progressive Rainbow

nm is the most common unit to describe the wavelength of light, with visible light falling in the region of 400–700 nm. The data in compact discs is stored as indentations (known as pits) that are approximately 100 nm deep by 500 nm wide. Reading an optical disk requires a laser with a wavelength 4 times the pit depth -- a CD requires a 780 nm wavelength (near infrared) laser, while the shallower pits of a DVD requires a shorter 650 nm wavelength (red) laser, and the even shallower pits of a Blu-ray Disc require a shorter 405 nm wavelength (blue) laser.

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Color in the eye Progressive Rainbow

The ability of the human eye to distinguish colors is based upon the varying sensitivity of different cells in the retina to light of different wavelengths. The retina contains three types of color receptor cells, or cones. One type, relatively distinct from the other two, is most responsive to light that we perceive as violet, with wavelengths around 420 nm. (Cones of this type are sometimes called short-wavelength cones, S cones, blue cones.) The other two types are closely related genetically and chemically. One of them (sometimes called long-wavelength cones, L cones, red cones) is most sensitive to light we perceive as yellowish-green, with wavelengths around 564 nm; the other type (sometimes called middle-wavelength cones, M cones, green cones) is most sensitive to light perceived as green, with wavelengths around 534 nm.

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Visible spectrumThis image contains 1 million pixels, each of a different color. The human eye can distinguishabout 10 million different colors.

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Color Model

Math model for color information RGB

Red, Green, Blue CMY / CMYK

Cyan, Magenta, Yellow, blacK (or Key) HSL / HSB / HSV / HVC

Hue , Saturation , Lightness (Brightness/Value) YUV / YCbCr (YCC)

Luminance + 2 Chrominance (Color differences)

Other color models

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The Color Wheel

A color wheel usually include 12 distinct colors. The color wheel is essentially the linear progression of color as seen in the color spectrum, connecting the two ends together.

Wheel of Color

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The Primary Colors (Additive colors)

Most of us now use color display, for which the primary colors will be Red, Green and Blue.

Wheel of Color (RGB Color Model)

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The Primary Colors (Additive colors)

Most of us now use color display, for which the primary colors will be Red, Green and Blue.

Wheel of Color (RGB Color Model)

Red

Green Blue

WY

C

M

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Cubic coordinate based on primary additive colors Start from Black (darkness) Sum of all = White (light)

Widely used in PC hardware CRT, LCD / Image Scanner Easy to implement

Not efficient/intuitive for processing Difficult to achieve / adjust to

desired color for human

RGB Color Model

Additive Color(= mixing light)

Red Blue Green

R

B

GBlack

White

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The Secondary Colors (Subtractive Colors)

Secondary color wheel: the three colors that are obtained by combining any two adjacent primary colors. These will be the secondary colors: cyan, magenta, and yellow.

Wheel of Color (CMY Color Model)

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The Secondary Colors (Subtractive Colors)

Secondary color wheel: the three colors that are obtained by combining any two adjacent primary colors. These will be the secondary colors: cyan, magenta, and yellow.

Wheel of Color (CMY Color Model)

Magenta

Yellow Cyan

R B

G

B

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CMY / CMYK Color ModelCyan

Magenta

Yellow

Subtractive Color(= mixing ink)

WhiteBlack

CM

Y

Subtractive version of RGB Start from White (paper) Sum of all = Black (ink)

Widely used in Publishing Industry Printer / Color publishing

uses 4 inks (CMYK) Why K (Black) ?

For pure black / black letter

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The Tertiary Colors

Tertiary colors are the same for both the additive and subtractive worlds.

Wheel of Color

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Analogous Colors

Analogous colors directly beside a given color. If you start with Orange and you want its two analogous colors, select Red and Yellow.

Wheel of Color

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The Complementary Colors

Complementary colors are directly opposite each other on the color wheel. Selecting contrasting colors is useful when you want to make the colors stand out more vibrantly.

Wheel of Color

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Split Complementary Colors

Split complementary colors can be made up of two or three colors. You select a color, find its complementary color or colors on the either side of the color wheel.

Wheel of Color

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Warm Colors

Warm colors are made up of the Red hues, such as Red, Orange and Yellow. They lend a sense of warmth, comfort, and energy to the color selection. They also produce visual result.

Wheel of Color

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Cool Colors

Cool colors come from the Blue hues, such as Blue, Cyan, and Green. These colors will stabilize and cool the color scheme. These are good to use for page background.

Wheel of Color

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Hue = Color name (red, blue, green, etc.)

Saturation = Density (purity) of the color

Value = Lightness & Darkness

Dimension of Color (HSL/HSV/HVC)

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HSL / HSV / HVC Color Model

Black

White

Cylindrical coordinates based on logical aspect of color Hue = Color name (red, blue, green, etc.) Saturation = Density (purity) of the color Lightness

Used in image editingsoftware Very easy to achieve /

adjust to desired colorfor human

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Color Matching

Color Gamut The range of color that can be reproduced on

any imaging device

Color Matching Adjustment / Compensation of the difference of

color gamut among multiple image devices

Eye CRT Scanner Printer Offset

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Color Depth

How many colors are needed? Black & White

= 1 bit

1 0

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How many colors are needed?Gray Scale

= 8 bit (256 shadows)

Color Depth

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Indexed Color (Palette)

F1 C3 4A 01 83 9B FC45 1D 3E 47 20 1D 80 565B 40 FA E4 5A 33 0F D07A 00 12 E2 C4 79 ED1C

0001020304

FEFF

03 F1 C3 4A 01 83 9B 2C45 1D 3E 47 20 1D 80 5379 40 FA E4 5A 33 0F D85A 00 12 E2 C4 79 ED 32

Image Data Palette Picture

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256-color image

Palette and Dithering

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How many colors are needed?Full Color = 8 bits for each R, G and B

= 24 bits (16.7 million colors)

Color Depth

Red

Green

Blue

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Color Depth

How many colors are needed? Black & White

= 1 bit Gray Scale

= 8 bit (256 shadows)

Indexed Color= 8 bit (217~256 color pallet)

Full Color = 8 bit each for RGB

= 24 bit (16.7 million colors)

Medical / Professional photography= 30~48 bit (10~16 bit/RGB)(Preserve detail / accuracy in editing)

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Color Depth

Graphic/Image Data Structure Pixels: picture elements in digital

images Image resolution: number of pixels in

a digital image Bit-map: a representation of the

graphic/image data in the same manner as they are stored in video memory

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Color Depth

Graphic/Image Data Structure Black & White

= 1 bitMono-chrome image

Each pixel is stored as a single bit (0 or 1)A 640 X 480 monochrome image requires 37.5 Kbytes

Gray-scale imageEach pixel is usually stored as a byte (0 to 255 levels)A 640 X 480 gray-scale image requires over 300 Kbytes

Gray Scale= 8 bit (256 shadows)

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Color Depth

Graphic/Image Data Structure Indexed Color

= 8 bit (217~256 color pallet)

One byte for each pixelSupport 256 colorsA 640 X 480 8-bit color image requires 307.2 KBytes

Three byte for each pixelSupport 256X256X256 colorsA 640 X 480 24-bit color image requires 921.6 KBytes

Full Color = 8 bit each for RGB

= 24 bit (16.7 million colors)

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Video Systems

Transm

itte

r

Rece

iver

Goals:1. Efficient use of bandwidth2. High viewer perception of

quality

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Camera Operation

Note:1. Camera has 1, 2, or 3 tubes for

sampling2. More tubes (CCD’s) and better lens

produce better pictures

Color Filters

En

cod

er

Camera Tubes

Zoom Lens

G

R

B

BeamSplitter

Com

pone

nt

YR-YB-Y

YC

RGB

S-Video

R

G

B

Composite

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Color Perception

Color is perceived lightwave 400nm to 700nm received at retina

Retina (on the back wall of the eye) composed of approximately 125 million rods and 7 million cones Cones respond to different frequencies (three

types, RGB) Rods measure brightness at low light levels (i.e.,

night vision)

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Color Perception (Cont…) Spectral-response functions of

each of the three types of cones on the human retina

G > R >> B Humans more sensitive to

brightness than color The processing and perception

of the image takes place in the brain.

Need to understand that there are also physiological and psychological aspects to the perception of color. Colors are often associated with various emotions, such as "feeling blue."

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YIQ color model: used in NTSC color TV Y is luminance containing brightness and the detail

(monochrome TV) To create the Y signal, the red, green and blue

inputs to the Y signal must be balanced to compensate for the color perception misbalance of the eye. Y = 0.3R + 0.59G + 0.11B

Chrominance I = 0.6R – 0.28G - 0.32B (cyan-orange axis) Q = 0.21R – 0.52G + 0.31B (purple-green axis)

Human eyes are most sensitive to Y, next to I, next to Q. In a channel (6 MHz) of NTSC TV, 4 MHz is allocated to

Y, 1.5 MHz to I, and 0.5 MHz to Q.

Color Models in Video

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YUV color model: for PAL TV and CCIR 601 standard for digital video

Same definition for Y as in YIQ model Chrominance is defined by U and V – the

color differences U = B – Y V = R – Y

YCbCr color model: used in JPEG and MPEG

Closely related to YUV: scaled and shifted YUV

Cb = ((B – Y)/2) + 0.5 Cr = ((R – Y)/1.6) + 0.5

Chrominance value in YCbCr are always in the range of 0 to 1

Color Models in Video (Cont…)

R

G

B

Y

U V

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Color Models in Video (Cont…)

R

G

B

Y

U V

Color models based on linear transformation from RGB color space

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Types of Color Video Signals Component video -- each primary is sent as a separate

video signal. The primaries can either be RGB or a luminance-chrominance

transformation of them (e.g., YIQ, YUV). Best color reproduction Requires more bandwidth and good synchronization of the three

components Composite video -- color (chrominance) and luminance

signals are mixed into a single carrier wave. Some interference between the two signals is inevitable.

S-Video (Separated video, e.g., in S-VHS) -- a compromise between component analog video and the composite video. It uses two lines, one for luminance and another for composite chrominance signal.

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NTSC Video: 525 scan lines per frame, 30 frames per second (or be exact, 29.97 fps, 33.37 msec/frame)

Interlaced, each frame is divided into 2 fields, 262.5 lines/field

20 lines reserved for control information at the beginning of each field So a maximum of 485 lines of visible data Laserdisc and S-VHS have actual resolution of ~420

lines Ordinary TV -- ~320 lines

Each line takes 63.5 microseconds to scan. Horizontal retrace takes 10 microseconds (with 5 microseconds horizontal synch pulse embedded), so the active line time is 53.5 microseconds.

Analog Video

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Chroma subsampling: human visual system is more sensitive to luminance than chrominance We can sub-sample chrominance

4:4:4 – No subsampling 4:2:2 – horizontally subsample 4:1:1 – horizontally subsample 4:2:0 – horizontally and vertically

Scanning Video

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Scanning Video

4:4:4 – No subsampling Y

CR CB

YCR CB

Line 1

Line 2

Line 3

Line 4

Y CR CB

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Scanning Video

4:2:2 – horizontally subsample YCR CB

YOnly

Line 1

Line 2

Line 3

Line 4

Y CR CB YCR CB

YOnly

YCR CB

YOnly

YCR CB

YOnly

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Scanning Video

4:1:1 – horizontally subsample YCR CB

YOnly

Line 1

Line 2

Line 3

Line 4

Y CR CB YOnly

YCR CB

YOnly

YOnly

YOnly

YOnly

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Scanning Video

4:2:0 – horizontally and vertically Y CR

Y CB

Y Only

Y Only

Line 1

Line 2

Line 3

Line 4

Y CR CB Y CR

Y CB

Y Only

Y Only

Y CR

Y CB

Y Only

Y Only

Y CR

Y CB

Y Only

Y Only

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Typical data assignment to YUV Y:U:V = 4:2:2 (TV)

Y:U:V = 4:1:1 (JPEG)

Y:U:V = 4:2:0 (JPEG)

Color space compression

Y U V

Y U V

Y U V

JPEG (1:50) Y U V

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Standards for Video

HDTVCCIR 601

NTSCCCIR 601

PALCIF QCIF

Luminance Resolution 1920 x 1080 720 x 486 720 x 576 352 x 288 176 x 144

Chrominance Resolution 960 x 540 360 x 486 360 x 576 176 x 144 88 x 72

Color Subsampling 4:2:2 4:2:2 4:2:2 4:2:0 4:2:0

Fields/sec 60 60 50 30 30

Aspect Ratio 16:9 4:3 4:3 4:3 4:3

Interlacing Yes Yes Yes No No

CCIR – Consultative Committee for International RadioCIF – Common Intermediate Format (approximately VHS quality)

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Sampling

1 Frame is stored 720x480 pixels for NTSC 1 Frame is stored 720x576 pixels for PAL Each Pixel is processed for Y (Luminance (B&W) 4:2:2 Samples 2 of every 4 pixels for color 4:1:1 Samples 1 of every 4 pixels for color 4:2:2 has twice the color detail for 4:1:1 (shaper

color edges) 4:4:4 is not necessary as humans are more

sensitive to change in luminance than color

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Sampling

The first number refers to the 13.5 MHz sampling rate of the luminance

The other two numbers refer to the sampling rates of the color difference signals R-Y and B-Y (or,more properly in the digital domain, Cr and Cb)

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Sampling

4:2:2 systems (D-1, D-5, DigiBeta, BetaSX, Digital-S,DVCPRO50) color sampled at half the rate of luminance,

Y is 13.5 MHz R-Y and B-Y is each 6.75 MHz 360 color samples (in each of Cr and Cb) per

scanline. 4:1:1 systems (NTSC DV & DVCAM, DVCPRO

Color data are sampled half as frequently as in 4:2:2

Y is 13.5 MHz R-Y and B-Y is each 3.375 MHz . 180 color samples per scanline.

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Sampling

4:2:2 Better for Computer Graphics Special Effects Chroma Keying Compositing Matting

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Uncompressed Sizes (NTSC)

For the 525 line TV standard the line data is: 720(Y) + 360(Cr) + 360(Cb) = 1,440

pixels/line 487 active lines/picture there are 1,440 x

487 = 701,280 pixels/picture (sampling at 8-bits, a picture takes 701.3

kbytes) 1 sec takes 701.3 x 30 = 21,039 kbytes, or

21 Mbytes 1 min takes 21,039 x 60 = 1,262,340 kbytes,

or 1.26 gigs

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Uncompressed Sizes (NTSC)

BOTTOM LINE 1 Gbyte will hold ~47 seconds 1 hour takes ~76 Gbytes Of Active Picture (Does not include sync

Blanking etc as these can be regenerated)

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Uncompressed Sizes (NTSC)

1 hour takes ~ Uncompressed 76 Gbytes 2:1 Compression 38 Gbytes 5:1 Compression 15 Gbytes

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Indexed Color (Palette)

Palette Optimization

F1 C3 4A 01 83 9B FC45 1D 3E 47 20 1D 80 565B 40 FA E4 5A 33 0F D07A 00 12 E2 C4 79 ED1C

0001020304

FEFF

03 F1 C3 4A 01 83 9B 2C45 1D 3E 47 20 1D 80 5379 40 FA E4 5A 33 0F D85A 00 12 E2 C4 79 ED 32

Image Data Palette Picture

03

DitheringBetter perception

256-color image

Optimized PaletteDithered

Optimized Palette& Dithered

Banding Effect

Palette and Dithering

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Gamma = Non-linearity of lightness in any imaging device

output value input value

= 1 : Linear

2.0 < < 3.0 : Typical CRT

Any imaging device has its gamma value Importance of Gamma correction

It is very important to adjust gamma values if you use same image in different imaging device

Especially in publishing industry

input

outp

ut

= 1.0

> 1.0

Gamma Correction

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Alpha Channel

Transparency information of image Important for image editing, animation

OriginalImage

TransparencyImage (GIF)

AlphaChannel(1-bit)

Grayscale Alpha Channel (8-bit)

Photo Collage

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Aliased image

Anti-Aliased ImageSimple Blur

Anti-aliasing

Aliasing problem Jagged edge of digital image

Not a problem of image data itself

Problem of PC's pixel-baseddisplay screen

Anti-aliasing technology Make edge smoother

Not a simple blur Over sampling or

other advancedalgorithms required

2D Bitmap Image Theory

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Bitmap image

Pixel based Group of colored dots

Best for real-world image Photography, Painted picture

Large data size Needs compression for transfer

Resolution Dependent Not suitable for resizing/zooming

RGB =(FF,B6,98)

A pixel

Full Color Windows BMP / 44KB

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Bitmap image compression

Loss-less Compression Can reproduce mathematically identical original

image without any data loss Not high compression ratio (~2.0)

Lossy Compression Reduce non-sensitive information to human eyes

(not mathematical, but physiological method) Cannot reproduce original image Can specify the amount of information loss

High compression ratio (~100)

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Algorithm Basic Concept Comp. Ratio

FileFormat

Loss-Less

RLE(Run-Length Encoding)

Pack repetitive data~1.2 BMP

LZW(Lempel-Zif-Welsh)

Build treed dictionary

~2.0 TIFF, GIF

Lossy

Color-space compression

Cut non-sensitivecolor information ~2.0 JPEG, (TV)

DCT(Discrete Cosine Transformation)

Transform to seriesof Cosine functions

~100 JPEG, MPEG1/2

Wavelet compression

Transform to seriesof Wavelet functions

~100 JPEG2000, MPEG4

Compression algorithms

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Color space compression (1)

Uses human eye characteristics Less sensitive to color than lightness Less sensitive to red than green Color information can be sparse

YUV color compression Y is the most sensitive light to human eyes

We should reserve information on this component U/V is much less sensitive

We can reduce information from these 2 components Typical ratio of data assignment to YUV

component Y:U:V = 4:4:4 / 4:2:2 / 4:1:1 / 4:2:0

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Typical data assignment to YUV Y:U:V = 4:2:2 (TV)

Y:U:V = 4:1:1 (JPEG)

Y:U:V = 4:2:0 (JPEG)

Color space compression (2)

Y U V

Y U V

Y U V

JPEG (1:50) Y U V

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Convert image to mathematical functions DCT (Discrete Cosine Transformation)

Uses series of cosine functions to encode image

Used in JPEG, MPEG, MPEG2, etc. Wavelet Transformation

Uses series of wavelet functions to encode image

Used in JPEG2000, MPEG4, DivX, XviD, etc.

Transformation Algorithm

= a0 · + a1 · + …+ a2 ·

= a0 · + a1 · + …+ a2 ·

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Fractal DCT Wavelet

Original Image (154KB)

Compress to 3 KB (1:50)

Algorithm Comparison

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Bitmap image file formats

Industry standard TIFF - Adobe/Silicon Graphics

Platform Standard BMP - Windows PICT - Macintosh GIF - CompuServe

International Standard JPEG - ISO 10918 PNG - MIT/W3C JPEG2000 - ISO 15444

http://www.dcs.ed.ac.uk/home/mxr/gfx/

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TIFF (Tagged Image File Format)

Highly flexible Ability to handle various kinds of specialized

image formats by using internal Tag over-24bit images (32, 36, up to 64-bits) Alpha-channel (Transparency) can be stored Multiple Layers LZW, JPEG or other compression

For Professional Used in professional imaging industry

Medical, Publishing, Digital photographers

Photoshop

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GIF (Graphics Interchange Format)

Designed for amateur use on network Many useful features for hobbyist

Transparency (1 bit only) Interlace (for fast perception over net) Animation (Cell Animation)

Suitable for small pictures / icons Flexible choice of bit-per-pixel (1~8) Indexed color only (no full color support) LZW compression (*patented)

Widely used in WWW Mostly for small animations or icons

Many

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High compression for full-color image Based on characteristics of human eyes

Less sensitive to color than lightness (YUV) Good for photography or artistic image NG for scientific image (uneven information loss)

The only international standard (up to now) Block noise

Widely used in consumer market, WWW

1:10 1:100

Square noise inhigh compression

JPEG (Joint Photographic Experts Group)

Many

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Designed to be the alternative of GIF No patent problem by free loss-less compression

algorithm (gnu zip) Many advanced features

Up to 48bpp color depth, 16 bit Alpha channel 2 dimensional interlace (Progressive image) File corruption checking

Slowly getting popularitys No “ground-breaking” features (Others can do) Limited support in Web browsers

PNG (Portable Network Graphics)

Macromedia Fireworks

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JPEG2000

New international standard (2001) ~20% better compression than JPEG

Less noise in high compression ratio Many advanced features

True progressive transfer Option for Loss-less compression Support for video Codec (Motion JPEG2000) Error resistance (good for the Internet) ROI (Region of interest) support

Slow acceptance No native support in Web browsers

IrfanView32

2D Bitmap Image Processing

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Basic Image Processing

How can you enhance your photograph taken by digital cameras / image scanners? Before doing any “creative” operation in

Photoshop, you should do basic (but important) image adjustment

Necessary basic image adjustment

1. Color correction / White balance correction

2. Dynamic range correction

3. Gamma correction

4. Retouching

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White Balance Correction

Especially useful for photos taken in house Incandescent lamp Photo shifts to Red Fluorescent lamp Photo shifts to Green Shadow in sunny day Photo shifts to Blue

Use Auto Levels or Variations command

79Dynamic range correction – Don’ts

Black White

Black White

Black White

Brightness change Simple shift of lightness

Contrast change Simple scaling of lightness

Do not use them without caution Information will be lost Better to use dynamic range

correction and / or gamma correction

Histograms

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Dynamic Range Correction

Especially useful for scanned image Black is not truly black, White is not truly white

Use Levels or Auto Contrast Tool

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Only Brightness

Useful for too under/over exposed image Also used for detailed tone normalization Use Levels or Curves command

Highlight and shadow are the same. Only middle tone changes

Gamma Correction as a Tool

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Dodge & Burn

Adjustment of dynamic range (lightness) of selected area in an image Traditionally the most sensitive task for

professional photographer in darkroom Use masking and histogram manipulation

Automatic local dynamic range correction The latest software (like Photoshop CS) has

function to automatically perform typical Dodge & Burn Surprisingly useful for photographer

But it still needs manual operation for real “content-based” correction

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Dodge & Burn (Example)

Gamma Correction

Shadow/Highlight (Photoshop) Manual Dodge & Burn

Original

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Correct the defect in photograph Especially useful for scanned image (because it

always has many dust orscratch on the image)

Use Clone Stamp Tool

Photo Retouching

2D Vector Image Theory

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Vector imageFilled polygon

Vector Based Group of mathematical shape data

Best for Illustration /Technical Drawing Fully editable, structured data

Small data size ~1/100 of comparable bitmap image Suitable for slow network (Internet)

Resolution Independent Suitable for resizing/zooming/printing

Can be applied to 3D modeling

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Line

Fill - for closed path only

Basic elements of vector image

Curve

Open Path Closed Path Open Path Closed Path

Simple Gradient Pattern

Polygon

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1 filled polygon

Group of 3 objects

Group of 54 polygons

Group of 97 polygons

Group of 18 polygons

Group of 2 objects

Group of 21 polygons Total of 191 polygons Group of 2 objects

Z-order and Grouping

Z-order Which object comes in front?

Grouping Treed structure of objects

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Mathematical Curves

Anchor Point 1

AnchorPoint 2

ControlPoint

Anchor Point 1

AnchorPoint 2

ControlPoint 2

Control Point 1

B-Spline curve Simple and fast calculation Easy to modify curve locally Used in TrueType Font, etc.

Bézier curve The most popular 2D

curve standard Easy to control the shape Widely used in almost

all vector based graphics programs

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Vector image file format

Industry Standard EPS - Adobe Artistic drawing AI - Adobe Artistic drawing DXF - Autodesk 2D/3D CAD

Platform Standard WMF, EMF - Windows

International Standard CGM (Computer Graphics Metafile) - ANSI/ISO SVG - (W3C recommendation)

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EPS (Encapsulated Post Script)

PostScript based PostScript = Bézier-curve based page definition

language developed by Adobe For printing complex page layout

Highly expressive Color separation, Layers, etc.

For Professional Artist Used in publishing / illustration industry Not used in mechanical drawing DXF

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AI (Adobe Illustrator)

Proprietary format for Adobe Illustrator Based primarily on PostScript Adds all special functionality of Illustrator

Somewhat industry standard More capability than EPS Many applications support this format

Inconsistency in versions Each new version of Adobe Illustrator has newer

version of file format Incompatible

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WMF & EMF

WMF (Windows Meta File) Straight line-based (No curve!) Designed for Microsoft Windows 3.1 Limited feature, but widely used in office market

EMF (Enhanced Meta File) Bézier curve-based Designed for Microsoft Windows 95 Used for exchange of vector data internally

between Windows applications

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