cis 601 image fundamentals longin jan latecki
DESCRIPTION
CIS 601 Image Fundamentals Longin Jan Latecki. Slides by Dr. Rolf Lakaemper. Fundamentals. Parts of these slides base on the textbook Digital Image Processing by Gonzales/Woods Chapters 1 / 2. Fundamentals. Today we will - PowerPoint PPT PresentationTRANSCRIPT
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CIS 601Image Fundamentals
Longin Jan Latecki
Slides by Dr. Rolf Lakaemper
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Fundamentals
Parts of these slides base on the textbook
Digital Image Processingby Gonzales/Woods
Chapters 1 / 2
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Fundamentals
Today we will
• Learn some basic concepts about digital images (Textbook chapters 1 / 2)
• Show how MATLAB can help in understanding these concepts
• Build a simple video – surveillance system using MATLAB !
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Fundamentals
In the beginning…
we’ll have a look at the human eye
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Fundamentals
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Fundamentals
We are mostly interested in the retina:
• consists of cones and rods• Cones• color receptors• About 7 million, primarily in the retina’s
central portion • for image details
• Rods• Sensitive to illumination, not involved in
color vision• About 130 million, all over the retina• General, overall view
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Fundamentals
Distribution of cones and rods:
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Fundamentals
The human eye is sensible to electromagnetic waves in the ‘visible spectrum’ :
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Fundamentals
The human eye is sensible to electromagnetic waves in the ‘visible
spectrum’ , which is around a wavelength of
0.000001 m = 0.001 mm
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Fundamentals
The human eye
• Is able to perceive electromagnetic waves in a certain spectrum
• Is able to distinguish between wavelengths in this spectrum (colors)
• Has a higher density of receptors in the center
• Maps our 3D reality to a 2 dimensional image !
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Fundamentals
…or more precise:
maps our continous (?) reality to a (spatially) DISCRETE 2D image
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Fundamentals
Some topics we have to deal with:
• Sharpness• Brightness
• Processing of perceived visual information
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Fundamentals
Sharpness
The eye is able to deal with sharpness in different distances
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Fundamentals
Brightness
The eye is able to adapt to different ranges of brightness
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Fundamentals
Processing of perceived information: optical illusions
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Fundamentals
optical illusions:
Digital Image Processing does NOT (primarily) deal with cognitive
aspects of the perceived image !
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Fundamentals
What is an image ?
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Fundamentals
The retinal model is mathematically hard to handle (e.g. neighborhood ?)
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Fundamentals
Easier: 2D array of cells, modelling the cones/rods
Each cell contains a numerical value (e.g. between 0-255)
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Fundamentals
• The position of each cell defines the position of the receptor
• The numerical value of the cell represents the illumination received by the receptor
5 7 1 0 12 4 ………
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Fundamentals
• With this model, we can create GRAYVALUE images
• Value = 0: BLACK (no illumination / energy)
• Value = 255: White (max. illumination / energy)
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Fundamentals
A 2D grayvalue - image is a 2D -> 1D function,
v = f(x,y)
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Fundamentals
As we have a function, we can apply operators to this function, e.g.
H(f(x,y)) = f(x,y) / 2
Operator Image (= function !)
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Fundamentals
H(f(x,y)) = f(x,y) / 2
6 8 2 0
12 200 20 10
3 4 1 0
6 100 10 5
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Fundamentals
Remember: the value of the cells is the illumination (or brightness)
6 8 2 0
12 200 20 10
3 4 1 0
6 100 10 5
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Fundamentals
As we have a function, we can apply operators to this function…
…but why should we ?
some motivation for (digital) image processing
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Fundamentals
• Transmission of images
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Fundamentals
• Image Enhancement
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Fundamentals
• Image Analysis / Recognition
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Fundamentals
The mandatory steps:
Image Acquisition and Representation
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Fundamentals
Acquisition
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Fundamentals
Acquisition
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Fundamentals
Typical sensor for images:
CCD Array (Charge Couple Devices)
• Use in digital cameras• Typical resolution 1024 x 768
(webcam)
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Fundamentals
CCD
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Fundamentals
CCD
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Fundamentals
CCD: 3.2 million pixels !
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Fundamentals
Representation
The Braun Tube
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Fundamentals
Representation
Black/White and Color
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Fundamentals
Color Representation: Red / Green / Blue
Model forColor-tube
Note: RGB is not the ONLY color-model, in fact its use is quiet restricted. More about that later.
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Fundamentals
Color images can be represented by3D Arrays (e.g. 320 x 240 x 3)
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Fundamentals
But for the time being we’ll handle
2D grayvalue images
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Fundamentals
Digital vs. Analogue Images
Analogue:Function v = f(x,y): v,x,y are REAL
Digital:Function v = f(x,y): v,x,y are INTEGER
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Fundamentals
Stepping down from REALity to INTEGER coordinates x,y: Sampling
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Fundamentals
Stepping down from REALity to INTEGER grayvalues v : Quantization
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Fundamentals
Samplingand
Quantization
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Fundamentals
MATLAB demonstrations of sampling and quantization effects in sampling.m