© 1999 Rochester Institute of Technology Introduction to Digital Imaging

© 1999 Rochester Institute of Technology

Introduction to Digital Introduction to Digital ImagingImaging

Imaging Science Workshop for Teachers ©Chester F. Carlson Center for Imaging Science at RIT

What is a Digital Image?What is a Digital Image?

Just an array of numbers!

50 44 23 31 38 52 75 5229 09 15 08 38 98 53 5208 07 12 15 24 30 51 5210 31 14 38 32 36 53 6714 33 38 45 53 70 69 4036 44 58 63 47 53 35 2668 76 74 76 55 47 38 3569 68 63 74 50 42 35 32


PixelPixel

Each picture element in the array is called a pixel. Each pixel is represented by a number.

50 44 23 31 38 52 75 5229 09 15 08 38 98 53 5208 07 12 15 24 30 51 5210 31 14 38 32 36 53 6714 33 38 45 53 70 69 4036 44 58 63 47 53 35 2668 76 74 76 55 47 38 3569 68 63 74 50 42 35 32

3232The “32” could represent a color, or a gray level


Capturing ImagesCapturing Images

How do we capture images digitally?

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01


Traditional Traditional vs.vs. Digital Photography Digital Photography

Chemical processing

Detector: Photographic film

Digitalprocessing

Detector: Electronic sensor (CCD)


Goal of Charge Coupled Device (CCD)Goal of Charge Coupled Device (CCD)

Capture electrons formed by interaction of photons with the silicon Measure the electrons from each picture element as a voltage

CCDPhotons Electronic Signal


Charge Coupled Device (CCD)Charge Coupled Device (CCD)

CCD chip replaces silver halide film

No wet chemistry processing

Image available for immediate feedback


Magnified View of a CCD ArrayMagnified View of a CCD Array

Individual pixel element

Close-up of a CCD Imaging ArrayClose-up of a CCD Imaging Array

CCD


Charge Coupled Device (CCD)Charge Coupled Device (CCD)

Lens projects image onto the CCD

CCD ‘samples’ the image, creating different voltages

based on the amount of light at each pixel

Voltages are converted to digital signals and stored


Spatial SamplingSpatial Sampling

When a scene is imaged onto the CCD by the lens, the continuous image is ‘sampled’ and divided into discrete picture elements, or ‘pixels’

Scene Grid over scene Spatially sampled scene


QuantizationQuantization

The spatially sampled image is then converted into an ordered set of integers (0, 1, 2, 3, …) according to how much light fell on each element

Spatially sampled scene

0

0

0

0

0

0

0

0

0

0

0

0

0

0

25

40

0

0

25

40

40

25 25

2540 40

40 40 40

25 2540 40 40

40 40 25

40

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40

64

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64 64 64

64 64 64

97

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97

0 0 0 0 0 0

0 0 0 0 0 0

0

0

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0 0

0

0

Numerical representation


Basic structure of CCDBasic structure of CCD

Divided into small elements called pixels (picture elements).

preamplifier

Image Image Capture Capture AreaArea

Shift Register

Voltageout

Columns

Rows


Fundamentals: Digital ImagesFundamentals: Digital Images

A digital image is an ordered collection of numbers

To be useful, the collection of numbers must be in a known, pre-defined format.

The rules of English let us ‘parse’ letters into words

1 0 0 0 1 1 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 1 1 0 1 1 1 0 0 0 0 1 0 1 0 1 1 1 0 1 1 0 1 0 1 0 0 0 1 1 0

Introductiontodigitalimagingforgearupstudentsfromnewyork



There is no ‘universal rule’ to decode the string of 0s and 1s in a digital file into an image

1 0 0 0 1 1 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 1 1 0 1 1 1 0 0 0 0 1 0 1 0 1 1 1 0 1 1 0 1 0 1 0 0 0 1 1 0

Image Formats provide the definitions that allow a string of numbers to be understood as an image



Once we know the format, each number can be read and used to describe the lightness or color of a specific picture element (“pixel”)

1 1 1 0 0 0 0 1 0 1 0 1 1 1 0 1 1 1 0 0 0 1 1 0


Image quality factorsImage quality factors

Two major factors which determine image quality are: Bit depth -- controlled by number of colors or grey

levels allocated for each pixel Spatial resolution -- controlled by spatial sampling.

Increasing either of these factors results in a larger image file size, which requires more storage space and more processing/display time.



The simplest kind of digital image is known as a “binary image” because the image contains only two ‘colors’ - white and black


Binary ImagesBinary Images

Because binary images contain only two colors, we can encode the image using just two numbers, for example:

0 = black 1 = white

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1 1 1 1 1 1 1 0 0 0 0 0 0 0 0

1 1 1 1 1 1 1 1 1 0 0 0 0 0 0

1 1 1 1 1 1 1 1 1 1 1 0 0 0 0

1 1 1 1 1 1 1 1 1 1 1 0 0 0 0

Imaging Science Workshop for Teachers ©Chester F. Carlson Center for Imaging Science at RIT2 shades of gray







Bit depth: bits per pixelBit depth: bits per pixel

The number of possible gray levels is controlled by the number of bits/pixel, or the ‘bit depth’ of the image

gray levelsgray levels

22

44

88

1616

3232

6464

128128

256256

Bit depth; bits/pixel

1

2

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8


Digital images: FundamentalsDigital images: Fundamentals

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228 178 106 193

183 143 84 162

A digital image is an ‘ordered array of numbers’

Each pixel (picture element) in a grayscale digital image is a number that describe the pixel’s lightness

(e.g., 0 = black 255 = white)




Color ImagesColor Images

In most cases, we also want to capture color information

The way that we capture, store, view, and print color digital images is based on the way that humans perceive color


Color PerceptionColor Perception

The eyes have three different kinds of color receptors (‘cones’); one type each for blue, green, and red light.

Color perception is based on how much light is detected by each of the three ‘primary’ cone types (red, green, and blue)


Color PerceptionColor Perception

Because we have three kinds of cones, every color that we can see can be made up by combining red, green, and blue light - the three “additive primaries”


Additive Color Mixing:Additive Color Mixing:

Mixing the three additive primaries together is known as “additive mixing” to distinguish it from mixing paints or dyes (“subtractive mixing”)



Remember that we are discussing “additive color mixing.” The mixing happens in the visual system, not on the screen.

You can verify this by examining a TV or computer screen at high magnification. Color monitors and LCD displays only make red, green, and blue light. All other colors are synthesized in the visual system.



By recording and playing back the amount of Red, Green, and Blue at each pixel, a digital camera can capture the colors in a scene.



RGB Color ImagesRGB Color Images

Each one of the color images (‘planes’) is like a grayscale image, but is displayed in R, G, or B

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The most straightforward way to capture a color image is to capture three images; one to record how much red is at each point, another for the green, and a third for the blue.


RGB Color ImagesRGB Color Images

To capture a color image we record how much red, green, and blue light there is at each pixel.

To view the image, we use a display (monitor or print) to reproduce the color mixture we captured.

Q) How many different colors can a display produce? A) It depends on how many bits per pixel we’ve got.

For a system with 8 bits/pixel in each of the red, green, and blue (a ‘24-bit image’):


RGB Color Images: 24-bit colorRGB Color Images: 24-bit color

Every pixel in each of the three 8-bit color planes can have 256 different values (0-255)

If we start with just the blue image plane, we can make 256 different “colors of blue”

0

255





If we add red (which alone gives us 256 different reds): 0 255

0

255





If we add red (which alone gives us 256 different reds):

We can make 256 x 256 = 65,536 combination colors because for every one of the 256 reds, we can have 256 blues.

0 255

0

255



When we have all three colors together, there are 256 possible values of green for each onefor each one of the 65,536 combinations of red and blue:

256 x 256 x 256 = 16,777,216 (“> 16.7 million colors”)



The numbers stored for each pixel in a color image contain the color of that pixel


Color Image = Red + Green + BlueColor Image = Red + Green + Blue

=

In a 24-bit image, each pixel has R, G, & B values When viewed on a color display, the three images are

combined to make the color image.

212100139196

16375113149

37446372

95118155170

189

162

38

41608278

182

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43576863





Bit Depth: ReviewBit Depth: Review

The color, or value of each pixel in an image is specified by a string of binary digits, or bits

The more bits available for each pixel, the greater the number of possible values each pixel can show:

bits/pixel values 1 2 8 256 24 16,777,216


Image quality factorsImage quality factors

Two major factors which determine image quality are: Bit depth -- controlled by number of colors or grey levels

allocated for each pixel Spatial resolution -- controlled by spatial sampling.

Increasing either of these factors results in a larger image file size, which requires more storage space and more processing/display time.



25


49


64


100


169


400


841


1600


2500


10,000


1,000,000



File Size CalculationFile Size Calculation

100 pixels

100 pixels

Bit depth = 8 bits per pixel (256 gray levels)

File size (in bits) = Height x Width x Bit Depth

100 x 100 x 8 bits/pixel = 80,000 bits/image80,000 bits or 10,000 bytes

How much memory is necessary to store an image that is 100 x 100 pixels with 8 bits/pixel?


File Size CalculationFile Size Calculation

1280 pixels

960 pixels

Bit depth = 24 bits per pixel (RGB color)

File size (in bits) = Height x Width x Bit Depth

960 x 1280 x 8 bits/pixel = 29,491,200 bits/image29,491,200 bits = 3,686,400 bytes = 3.5 MB

How much memory is necessary to store an image that is 1280 x 960 pixels with 24 bits/pixel?


Computer Memory & StorageComputer Memory & Storage

Unlike analog instruments (and people) that work with continuously variable signals, computers are inherently binary systems

Instead of ten distinct values (a decimal system), computers use only two values, e.g.,

RAM memory: 0 or +5 volts Disk drives: N or S magnetization CD/DVD-ROM: ‘land’ or ‘pit’

By convention, binary digits (bits) are labeled ‘0’ & ‘1’


Binary ArithmeticBinary Arithmetic

In binary arithmetic, we can only count from 0 to 1 with a single bit, giving two different values.

0

1

0

1

binary decimal

1 bit



In binary arithmetic, we can only count from 0 to 1 with a single bit, giving two different values.

To get more than two values, we have to increase the number of bits. With two bits it is possible to count from 0 through 3 (decimal), giving four different values.

0

1

0

1

binary decimal

00

01

10

11

0

1

2

3

1 bit

2 bits



Each added bit allows us to double the number of values we can represent with a binary number.

The number of values that can be represented is given by 2Nbits

e.g., 4 bits provides 24 = 16 different values

A bit is a value, a position, and an amount of information

0

1

10

11

100

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111

1000

1001

1010

1011

1100

1101

1110

1111

10000...

binary

0

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16...

decimal

1 bit

2 bits

3 bits

4 bits



Because of the internal design of early computers, 8 bits were grouped together and called a ‘byte’

8 bits 1 byte

One byte can represent any one of (28 = 256) different values;

00000000 11111111 (binary) 0 255 (decimal)



1 bit (‘binary digit’)

1 byte = 8 bits

1 kilobyte (KB) = 1,024 bytes (210 = 1024) (1,000 bytes)

1 megabyte (MB) = 1,048,576 bytes ( 220)

(1,000,000 bytes)

1 gigabyte (GB) = 1,073,741,824 bytes ( 230)

(1,000,000,000 bytes)

Documents

© 1999 Rochester Institute of Technology Introduction to Digital Imaging