Digital Imaging - RIT Center for Imaging ScienceImaging Science Workshop for Teachers ©Chester F. Carlson Center for Imaging Science at RIT Response of CCD υThe response of CCD is

© 1999 Rochester Institute of Technology

Digital ImagingDigital Imaging

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

So Far . . .So Far . . .

υ AgX photographic film captures image formed by theoptical elements (lens).

υ Unfortunately, the processing for film is slow (among otherdisadvantages).

processing

image

cameraAgX film

υ Can we use something else to capture the image?

image

camera


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

υ 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

υ Each picture element in thearray is called a pixel.

υ Each pixel is representedby 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


Binary ArithmeticBinary Arithmetic

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

01

01

binary decimal

1 bit



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

υ To get more than two values, wehave to increase the number of bits.With two bits it is possible to countfrom 0 through 3 (decimal), givingfour different values.

01

01

binary decimal

00011011

0123

1 bit

2 bits



υ Each added bit allows us to doublethe number of values we canrepresent with a binary number.

υ The number of values that can berepresented is given by 2Nbits

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

υ A bit is a value, a position, and anamount of information

01

1011

100101110111

10001001101010111100110111101111

10000...

binary

0123456789

10111213141516

...

decimal

1 bit

2 bits

3 bits

4 bits


8s 4s 2s 1s01

1 01 1

1 0 01 0 11 1 01 1 1

1 0 0 0

Decimal & Binary ArithmeticDecimal & Binary Arithmetic

υ The value of a symbol is given by its ‘place’

υ When any place gets beyond ‘1’ we carry into the next higher place

100s 10s 1s012..

91 01 11 2

.

.9 9

1 0 0


Computer Memory & StorageComputer Memory & Storage

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

8 bits ≡ 1 byte

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

00000000 → 11111111 (binary) 0 → 255 (decimal)



υ 1 bit (‘binary digit’)

υ 1 byte = 8 bits

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

(≈1,000 bytes)

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

(≈1,000,000 bytes)

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

(≈1,000,000,000 bytes)



υ Page of Text: 3 KB

υ Floppy disk 1.44 MB

υ ZIP disk: 100 - 250 MB

υ Laptop Disk Drive: 2.1 GB

υ DC-120 *.kdc raw image: 1 MB

υ DC-120 Hi-Res Image: 3.6 MB

υ DCS-460 Image: 18 MB


υ Digital imaging relies on many of the sameprinciples as traditional film-based photography

υ Light source

υ Object

υ Lens

υ Aperture

υ Shutter

υ “Detector”

υ “Processing”

Digital Digital vsvs.Traditional Photography.Traditional Photography


Traditional Traditional vsvs.. Digital Photography Digital Photography

Chemical processing

Detector: Photographic film

Digitalprocessing

Detector: Electronic sensor (CCD)


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

υ CCD chip replaces silver halide film

υ No wet chemistry processing

υ Image available for immediate feedback


Response of CCDResponse of CCD

υ The response of CCD is linear (i.e., if 10,000 captured photonscorresponds to a digital count of 4, then 20,000 photons capturedyields a digital count of 8)

υ Linearity is critical for scientific uses of CCD

Log H

Den

sity

Response of photographicnegative

Exposure

Dig

ital C

ount

Response of CCD


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


CCDsCCDs as Semiconductors as Semiconductors

υ Conductors allow electricity to pass through. (Metals likecopper and gold are conductors.)

υ Insulators do not allow electricity to pass through. (Plastic,wood, and paper are insulators.)

υ Some materials are halfway in between, called semiconductors.

ConductorInsulator


Basic structure of a pixel in a CCDBasic structure of a pixel in a CCD

υ Silicon is a semiconductor.

υ Oxide layer is an insulator.

υ Metal gates are conductors.

υ Made with microlithographic process.

υ One pixel may be made up of two or more metal gates.

Silicon baseSilicon base

Metal gate

Oxide Layer

One pixel


Photon/Silicon InteractionPhoton/Silicon Interaction

υ Photon knocks off one of the electrons from the silicon matrix.

Silicone-e-

υ Electron “wanders around” randomly through the matrix.

υ Electron gets absorbed into the silicon matrix after some period.


Spectral Response (sensitivity)Spectral Response (sensitivity)of a typical CCDof a typical CCD

υ Response is large in visible region, falls off for ultraviolet(UV) and infrared (IR)

300 400 500 600 700 800 900 1000

Incident Wavelength [nm]

RelativeResponse

Visible Light IRUV


Goal of CCDGoal of CCD

υ Capture electrons formed by interaction ofphotons with the silicon

υ Measure the electrons from each picture elementas a voltage

CCDPhotons Electronic Signal


Collection stageCollection stage

υ Electron formed in the silicon matrix by a photon.

e-

υ Electron wanders around the matrix.

υ If the electron wanders into the depletion region, the electron iscaptured, never recombining with the silicon matrix.

e-e-

Voltage


CollectionCollection

υ The number of electrons accumulated is proportional to theamount of light that hit the pixel.

υ There is a maximum number of electron that these “wells”can hold.

e-e-e- e-

e- e-e-e- e-e- e-

Light


ReadoutReadout

υ Now that the electrons are collected in theindividual pixels, how do we get theinformation out?

Alright! How do weget the electrons out?!


Bucket BrigadeBucket Brigade

υ By alternating the voltage applied to the metalgates, collected electrons may be moved across thecolumns.

e-e-e- e-

e- e-e-e- e-e- e-e-

e-e- e-e-e-e- e-

e- e- e-e-e-e- e-

e-e- e-e- e-e- e-e- e-e-e-

e-e- e-e- e-e- e-e- e- e-e-e-e-e-e- e-e- e-e- e- e-e-e-e-e-e-

e-e- e-


Bucket BrigadeBucket Brigade

υ Charge is marched across the columns into theshift register, then read out 1 pixel at a time.

100 pixels

100 pixels

1 transfer100 transfers

100 transfers200 transfers

Shift Register


Converting Analog Voltages to DigitalConverting Analog Voltages to Digital

υ Analog voltage is converted to a digital count using anAnalog-to-Digital Converter (ADC)υ Also called a digitizer

υ The input voltage is quantized:υ Assigned to one of a set of discrete steps

υ Steps are labeled by integers

υ Number of steps determined by the number of available bits

υ Decimal Integer is converted to a binary number forcomputation

ADC6.18 volts 01100101 (117)


Bits and BytesBits and Bytes

υ In the digital domain, there are only two possible numbersin a digit: 0 or 1.

υ This numbering system is called a binary system.

υ Each digit is called a bit (Binary digIT).

υ Byte is 8 bits

Decimal012345

Binary011011100101


BitsBits

υ Bits dictate how fine the quantization levelsare.

υ An n bit system can represent 2n numbers.

1 bit system = 21 = 2 levels (“Black” or “White”)

8 bit system = 28 = 256 levels

12 bit system = 212 = 4096 levels


QuantizationQuantization

υ Let’s say our 8 bit ADC acceptsinput voltage range of 0 to 10v.

ADC

6.8 volts

υ Since there are 256 discretelevels in an 8 bit system, eachlevel will be 10v/256 or0.0390625 volts per analog-to-digital unit (ADU).

υ So, if the input voltage was 6.8volts . . .

6.8v 174.08

Volts DC

υ Since ADU are stored as binaryintegers, the decimal must betruncated (to 174).

172

173

174

175

176

255

00v

6.8 volts/0.0390625 volts per DC = 174.08

10v

υ Binary equivalent of 174 is10101110.



υ Spatially sampled image can now be turned into numbersaccording to the brightness of each pixel.

Spatially sampled scene

0

0

00

0

0

0

0

0

0

0

0

0

0

2540

0

0

25

40

40

25 25

2540 40

40 40 40

25 2540 40 40

40 40 25

40

40

40

64

64

6464

64

64

64 64 64

64 64 64

97

97

97

97

97

150

97

97

97

0 0 0 0 0 0

0 0 0 0 0 0

0

00

00 0

0

0

Numerical representation


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

υ Lens projects image onto the CCD

υ CCD ‘samples’ the image, creating different voltages

based on the amount of light at each pixel

υ Voltages are converted to digital signals and stored


Spatial SamplingSpatial Sampling

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

Scene Grid over scene Spatially sampled scene



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

Spatially sampled scene

0

0

00

0

0

0

0

0

0

0

0

0

0

2540

0

0

25

40

40

25 25

2540 40

40 40 40

25 2540 40 40

40 40 25

40

40

40

64

64

6464

64

64

64 64 64

64 64 64

97

97

97

97

97

150

97

97

97

0 0 0 0 0 0

0 0 0 0 0 0

0

0

0

00 0

0

0

Numerical representation


Fundamentals: Digital ImagesFundamentals: Digital Images

υ A digital image is an ordered collection of numbers

υ To be useful, the collection of numbers must be in aknown, pre-defined format.

υ 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

introductiontodigitalimagingforlawenforcementandpublicsafety



υ There is no ‘universal rule’ to decode the string of0s 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

υ Image Formats provide the definitions that allow astring of numbers to be understood as an image



υ Once we know the format, each number can beread and used to describe the lightness or colorof 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



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


Binary ImagesBinary Images

υ Because binary images contain only two colors, wecan encode the image using just two numbers, forexample:

υ 0 = black

υ 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



υ Regardless of the particular method, they areall binary - only two different values can bestored

υ Computers only work with binary numbers.Before any calculations are done, decimalnumbers are converted internally to theirbinary equivalents.


Digital Image FormatsDigital Image Formats

υ The smallest unit of measurement in a computer isthe bit (binary digit) - 0 or 1

υ 1 bit is the amount of storage needed to store 1 pixelof a binary image because each pixel can only beblack or white.


υ If we want an image that has more than two gray levels,we have to increase the number of ‘bits per pixel’

binary: just white or black grayscale: many shades of gray



0 0

0 1

1 0

1 1

2x2 = 4 gray levels

2 gray levels

0

11 bit/pixel 2 bits/pixel



2x2x2 = 8 gray levels

“false contours”0 0 0

0 0 1

0 1 0

0 1 1

1 0 0

1 0 1

1 1 0

1 1 1

3 bits/pixel



0 0 0 = 0

0 0 1 = 1

0 1 0 = 2

0 1 1 = 3

1 0 0 = 4

1 0 1 = 5

1 1 0 = 6

1 1 1 = 7

. . . = .

υ We started to look at the bits astokens to represent differentvalues, but we ended up with abinary counting system.

υ The largest number we cancount to (and the number ofdifferent gray levels we canhave) depends on how manybits we use.



3 bits/pixel: 8 gray levels

000 → 111

(0 → 7)


0000 → 1111

(0 → 15)




00000 → 11111

(0 → 31)


00000000 → 11111111

(0 → 255)

...



Bit depth: bits per pixelBit depth: bits per pixel

υ The number of possible gray levels is controlled by thenumber 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

3

4

5

6

7

8


Memory requirements: Bit depthMemory requirements: Bit depth

υ Adding more gray levels is ‘cheap’ in terms of memoryrequirements. Every added bit doubles the number ofgray levels

Grayscale Values vs. Bit Depth

0

64

128

192

256

1 2 3 4 5 6 7 8bits per pixel

gray levels


Digital images: FundamentalsDigital images: Fundamentals

39

56

45

75

62

99

64

101

228 178 106 193

183 143 84 162

υ A digital image is an ‘ordered array of numbers’

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

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


υ A digital camera converts each pixel into a number

υ The output display (computer screen or printer) interprets the arrayof numbers as an image

113 143 200 98 87 34 12 56 121 124 . . .

128 150 221 107 98 56 21 87 133 143 . . .

134 155 191 97 88 73 30 101 127 131 . . .

113 143 200 98 87 34 12 56 121 124 . . .

128 150 221 107 98 56 21 87 133 143 . . .

134 155 191 97 88 73 30 101 127 131 . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

113 143 200 98 87 34 12 56 121 124 . . .

128 150 221 107 98 56 21 87 133 143 . . .

134 155 191 97 88 73 30 101 127 131 . . .

113 143 200 98 87 34 12 56 121 124 . . .

128 150 221 107 98 56 21 87 133 143 . . .

134 155 191 97 88 73 30 101 127 131 . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .



υ A digital camera converts each pixel into a number

υ The output display (computer screen or printer) interprets the arrayof numbers as an image

113 143 200 98 87 34 12 56 121 124 . . .

128 150 221 107 98 56 21 87 133 143 . . .

134 155 191 97 88 73 30 101 127 131 . . .

113 143 200 98 87 34 12 56 121 124 . . .

128 150 221 107 98 56 21 87 133 143 . . .

134 155 191 97 88 73 30 101 127 131 . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

113 143 200 98 87 34 12 56 121 124 . . .

128 150 221 107 98 56 21 87 133 143 . . .

134 155 191 97 88 73 30 101 127 131 . . .

113 143 200 98 87 34 12 56 121 124 . . .

128 150 221 107 98 56 21 87 133 143 . . .

134 155 191 97 88 73 30 101 127 131 . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .



Grayscale ImagesGrayscale Images

υ Grayscale images commonly have 256 different grayvalues, numbered 0 - 255. Each pixel can then be storedin 8 bits, or 1 byte. [00000000 ∏ 11111111]

0 = black 255 = white

υ Grayscale pixels are sometimes stored with as many as1024 gray values (10 bits) or 4096 gray values (12 bits)Because of limitations of the visual system, this doesn’tmake the images ‘look better’ but it increases the amountof information, and the range of tones that can be captured


Image quality factorsImage quality factors

υ Two major factors which determine image qualityare:υ Spatial resolution -- controlled by spatial sampling.

υ Color depth -- controlled by number of colors or greylevels allocated for each pixel

υ Increasing either of these factors results in a largerimage file size, which requires more storage spaceand more processing/display time.


Image Resolution: Image Resolution: 4 x 3 Pixels4 x 3 Pixels


















Image Resolution: Image Resolution: 1280 x 960 Pixels*1280 x 960 Pixels*


Image resolution: Pixels per imageImage resolution: Pixels per image


Bit Depth: ReviewBit Depth: Review

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

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

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


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

υ How much memory isnecessary to store an imagethat is 100 x 100 pixels with8 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

υ How much memory isnecessary to store an imagethat is 1280 x 960 pixelswith 24 bits/pixel?


Spatial SamplingSpatial Sampling

υ When a continuous scene is imaged on the array (grid)formed by a CCD , the continuous image is divided intodiscrete elements.

υ The picture elements (pixels) thus captured represent aspatially sampled version of the image.

Scene Grid over scene Spatially sampled scene

Documents

Digital Imaging - RIT Center for Imaging ScienceImaging Science Workshop for Teachers ©Chester F. Carlson Center for Imaging Science at RIT Response of CCD υThe response of CCD is