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 2.4 Image sampling and
quantization 2.5 Some basic relationships
between pixels
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2.1 Elements of Visual Perception
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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

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2.1.2 Image Formation in the Eye
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2.2 Light and Electromagnetic Spectrum
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2.2 Light and Electromagnetic Spectrum
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2.3 Image Sensing and Acquisition
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2.3.4 A Simple Image Formation Model
2-D digital image
illumination
shift, scale
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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

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2.4.1 Basic Concepts in Sampling and Quantization
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2.4.1 Basic Concepts in Sampling and Quantization
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2.4.2 Representing Digital Images
Spatial domain
Spatial coordinate (x,y) discrete quantities
(integers)
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2.4.2 Representing Digital Images
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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)
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2.4.2 Representing Digital Images
0, L-1 dynamic range
L quantization level

• b number of bits to store digital image

if MN
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2.4.2 Representing Digital Images
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2.4.3 Spatial and Intensity Resolution
Spatial resolution change down-sampling
(subsampling)
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2.4.3 Spatial and Intensity Resolution
Spatial resolution change up-sampling from
down-sampled images
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2.4.3 Spatial and Intensity Resolution
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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)
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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)
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2.4.4 Image Interpolation
128?1024
64?1024
32?1024
Zooming by pixel replication
Zooming by bilinear interpolation using four
neighbors
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2.4.4 Image Interpolation
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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)

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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)

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2.5.3 Distance Measures

• p(x,y), q(s,t), z(v,w) pixels

Requirements for distance function (metric)

• Euclidean distance

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2.5.3 Distance Measures

• D4 distance (city-block distance)

• D8 distance (chessboard distance)