DIGITAL IMAGE PROCESSING INTRODUCTION Dr. Hatem Elaydi Electrical Engineering Department Islamic University of Gaza Fall 2015 Sep. 9, 2015
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DIGITAL IMAGE PROCESSING
INTRODUCTION Dr. Hatem Elaydi
Electrical Engineering Department
Islamic University of Gaza
Fall 2015
Sep. 9, 2015
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Electromagnetic spectrum
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Sensor Array: CCD Imaging
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Image Formation Model
f(x,y)=i(x,y)r(x,y)+n(x,y)
0<f(x,y)<∞
0<i(x,y)<∞
0<r(x,y)<1 reflectance
illumination
Intensity – proportional to energy
radiated by a physical source
(“intrinsic images”)
n(x,y) noise
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Sampling and Quantization: 1D Case
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2D Sampling and Quantization
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Introduction to Grayscale Images
Image representation
Spatial resolution
Bit-depth resolution
Local neighborhood
Block decomposition
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Image Represented by a Matrix
Spatial resolution
Bit-depth resolution
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Spatial Domain vs. Transform Domain
• Spatial domain
image plane itself, directly process the intensity values of
the image plane
• Transform domain
process the transform coefficients, not directly process
the intensity values of the image plane
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Spatial Domain Process
( , ) [ ( , )])
( , ) : input image
( , ) : output image
: an operator on defined over
a neighborhood of point ( , )
g x y T f x y
f x y
g x y
T f
x y
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Image Resampling
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Spatial Domain Process
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Spatial Resolution
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Commonly–used Terminology
Neighbors of a pixel p=(i,j)
N4(p)={(i-1,j),(i+1,j),(i,j-1),(i,j+1)} N8(p)={(i-1,j),(i+1,j),(i,j-1),(i,j+1),
(i-1,j-1),(i-1,j+1),(i+1,j-1),(i+1,j+1)}
Adjacency
4-adjacency: p,q are 4-adjacent if p is in the set N4(q)
8-adjacency: p,q are 8-adjacent if p is in the set N8(q)
Note that if p is in N4/8(q), then q must be also in N4/8(p)
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Euclidean distance
(2-norm)
D4 distance
(city-block distance)
D8 distance
(checkboard distance)
0 1 1
1
1
0 1 1
1
1
0 1 1
1
1 1 1
1 1
2 2 2 2 2
2
2
2
2 2 2 2
2
2
2
2
2
2
2
2
2
2
2
2 3
3
3
3 3
3
3
3 4
4 4
4 2
2 2
2
2 2
22
22
22 22
22
5
5
55
5
5
5 5
Common Distance Definitions
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