Digital Imaging - Computed Tomography - Lecture Slides, Slides of Computed Tomography

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Digital Imaging

Analog vs. Digital Information

 Analog  continuous information  Can have any of an infinite number of values  Digital  discrete information  Can have a finite number of values limited by  # of digits on display  # of bits used to represent value

Digitizing a Picture

 Commercial scanner  Renders a photograph into numbers

311, 255, 309, 78, 43, 99, 124,…

Analog vs. Digital Images

 Analog

 continuous gray shade information

 Digital

 Discrete gray shade information

Digital Image Formation:

Sampling

 Place mesh over image

 Assign each square

(pixel) a value based on density

 Pixel values form the digital image

Digital Image Formation:

Sampling

 Each pixel assigned a value

 Value averages entire pixel  Any spatial variation within a pixel is lost

 The larger the pixel, the more variation

What is this?

12 X 9 Matrix docsity.com

Same object, smaller squares

24 X 18 Matrix

Same object, smaller squares

96 X 72 Matrix docsity.com

Same object, smaller squares

192 X 144 Matrix

Popular Bit Groupings

 Bit (binary digit)  Smallest binary unit; has value 0 or 1 only  Byte  8 bits  28 = 256 unique values  Word  16 bits  216 = 65536 unique values  Double Word  32 binary bits (1110 0100 0000 1011 0101 0101 1110 0101)

of values which can be

represented by 1 bit

2 unique combinations / values

1

2

of values which can be

represented by 3 bits

8 unique combinations / values

2

1

3

4

6

5

7

8

Digital Image Bit Depth

 bit depth controls # of possible values a pixel can have

 increasing bit depth results in

 more possible values for a pixel  better contrast resolution

Bits Values^ # Values