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Chapter 2: Digital Image Fundamentals

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Chapter 2: Digital Image Fundamentals. 2.1 Elements of visual perception. 2.2 Light and electromagnetic spectrum. 2.3 Image sensing and acquisition – PowerPoint PPT presentation

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Title: Chapter 2: Digital Image Fundamentals


1
Chapter 2 Digital Image Fundamentals
2.1 Elements of visual perception 2.2 Light and
electromagnetic spectrum 2.3 Image sensing and
acquisition 2.4 Image sampling and
quantization 2.5 Some basic relationships
between pixels
2
2.1 Elements of Visual Perception
3
2.1.1 Structure of the Human Eye
  • Cones highly sensitive to color, 67 million
  • Rods sensitive to low levels of illumination,
    75150 million
  • dim-light vision

4
2.1.2 Image Formation in the Eye
5
2.2 Light and Electromagnetic Spectrum
6
2.2 Light and Electromagnetic Spectrum
7
2.3 Image Sensing and Acquisition
8
2.3.4 A Simple Image Formation Model
2-D digital image
illumination
shift, scale
9
2.4 Image Sampling and Quantization
  • Image acquisition generate digital images from
    sensed data
  • Two processes sampling, quantization
  • Sampling digitizing coordinate values
  • Quantization digitizing amplitude values

10
2.4.1 Basic Concepts in Sampling and Quantization
11
2.4.1 Basic Concepts in Sampling and Quantization
12
2.4.2 Representing Digital Images
Spatial domain
Spatial coordinate (x,y) discrete quantities
(integers)
13
2.4.2 Representing Digital Images
14
2.4.2 Representing Digital Images
  • MxN digital image in compact matrix form
  • Each element in the matrix array
  • Image element, picture element, pixel, pel
  • MxN digital image in more traditional matrix
    notation

ai,j f(i,j)
15
2.4.2 Representing Digital Images
0, L-1 dynamic range
L quantization level
  • b number of bits to store digital image

if MN
16
2.4.2 Representing Digital Images
17
2.4.3 Spatial and Intensity Resolution
Spatial resolution change down-sampling
(subsampling)
18
2.4.3 Spatial and Intensity Resolution
Spatial resolution change up-sampling from
down-sampled images
19
2.4.3 Spatial and Intensity Resolution
20
2.4.3 Spatial and Intensity Resolution
Gray-level resolution change
256 levels (k 8)
128 levels (k 5)
false contouring
64 levels (k 6)
32 levels (k 5)
21
2.4.3 Spatial and Intensity Resolution
Gray-level resolution change
false contouring
8 levels (k 3)
16 levels (k 4)
2 levels (k 1)
4 levels (k 2)
22
2.4.4 Image Interpolation
128?1024
64?1024
32?1024
Zooming by pixel replication
Zooming by bilinear interpolation using four
neighbors
23
2.4.4 Image Interpolation
24
2.5 Some Basic Relationships Between Pixels
2.5.1 Neighbors of a Pixel
  • N4(p) 4-neighbors of p, p(x,y)
  • (x1, y), (x-1, y), (x,y1), (x,y-1)
  • ND(p) diagonal neighbors of p, p(x,y)
  • (x1, y1), (x1, y-1), (x-1,y1), (x-1,y-1)
  • N8(p) union of N4(p) and ND(p)

25
2.5.2 Adjacency, Connectivity, Regions, and
Boundaries
  • 4-adjacency Two pixels p and q are 4-adjacent
  • if q is in N4(p)
  • 8-adjacency Two pixels p and q are 8-adjacent
  • if q is in N8(p)

26
2.5.3 Distance Measures
  • p(x,y), q(s,t), z(v,w) pixels

Requirements for distance function (metric)
  • Euclidean distance

27
2.5.3 Distance Measures
  • D4 distance (city-block distance)
  • D8 distance (chessboard distance)
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