Download - Imaging Fundamentals
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Course Website: http://www.comp.dit.ie/bmacnamee
Digital Image Processing:Digital Imaging Fundamentals
Brian Mac [email protected]
mailto:[email protected]:[email protected] -
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Contents
This lecture will cover:
Human visual system
Light and the electromagnetic spectrum
Image representation
Image sensing and acquisition
Sampling, quantisation and resolution
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Human Visual System
The best vision model we have!
Knowledge of how images form in the eyecan help us with processing digital images
We will take just a whirlwind tour of thehuman visual system
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Structure of the Human Eye
The lens focuses light from objects onto theretina
The retina is covered withlight receptors called
cones(6-7 million) androds(75-150 million)
Cones are concentrated
around the fovea and arevery sensitive to colour
Rods are more spread outand are sensitive to low levels of illumination
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Blind-Spot Experiment
Draw an image similar to that below on apiece of paper (the dot and cross are about6 inches apart)
Close your right eye and focus on the cross
with your left eyeHold the image about 20 inches away from
your face and move it slowly towards youThe dot should disappear!
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Image Formation in the Eye
Muscles within the eye can be used tochange the shape of the lens allowing usfocus on objects that are near or far away
An image is focused onto the retina causing
rods and cones to become excited whichultimately send signals to the brain
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Brightness Adaptation & Discrimination
The human visual system can perceiveapproximately 1010 different light intensitylevels
However, at any one time we can only
discriminate between a much smallernumber brightness adaptation
Similarly, the perceived intensityof a regionis related to the light intensities of theregions surrounding it
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Brightness Adaptation & Discrimination(cont)
An example of simultaneous contrast
An example of Mach bands
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Optical Illusions
Our visualsystems play lotsof interestingtricks on us
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Light and the Electromagnetic Spectrum
Light is just a particular part of theelectromagnetic spectrum that can besensed by the human eye
The electromagnetic spectrum is split up
according to the wavelengths of differentforms of energy
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Reflected Light
The colours that we perceive are determinedby the nature of the light reflected from anobject
For example, if white
light is shone onto agreen object most
wavelengths areabsorbed, while greenlight is reflected from
the object
WhiteLight
ColoursAbsorbed
GreenLight
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Sampling, Quantisation and Resolution
In the following slides we will consider whatis involved in capturing a digital image of areal-world scene
Image sensing and representation
Sampling and quantisation Resolution
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Image Representation
col
row
f (row, col)
Before we discuss image acquisition recallthat a digital image is composed of M rows
and Ncolumns of pixelseach storing a value
Pixel values are mostoften grey levels in therange 0-255(black-white)
We will see later onthat images can easilybe represented asmatrices
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Image Acquisition
Images are typically generated byilluminatinga sceneand absorbing the
energy reflected by the objects in that scene Typical notions of
illumination andscene can be way off:
X-rays of a skeleton
Ultrasound of anunborn baby
Electro-microscopic
images of molecules
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Image Sensing
Incoming energy lands on a sensor materialresponsive to that type of energy and this
generates a voltage
Collections of sensors are arranged to
capture images
Imaging Sensor
Line of Image SensorsArray of Image Sensors
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Image Sampling and Quantisation
A digital sensor can only measure a limitednumber of samples at a discrete set of
energy levels
Quantisationis the process of converting a
continuous analogue signal into a digitalrepresentation of this signal
17 Image Sampling and Quantisation
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Image Sampling and Quantisation(cont)
Remember that a digital image is alwaysonly an approximation of a real world
scene
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Spatial Resolution
The spatial resolutionof an image isdetermined by how sampling was carried out
Spatial resolution simply refers to thesmallest discernable detail in an image
Vision specialists willoften talk about pixelsize
Graphic designers willtalk about dots per
inch(DPI)
5.1
Megapixe
ls
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Spatial Resolution (cont)
1024 * 1024 512 * 512 256 * 256
128 * 128 64 * 64 32 * 32
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Intensity Level Resolution
Intensity level resolutionrefers to thenumber of intensity levels used to represent
the image The more intensity levels used, the finer the level of
detail discernable in an image
Intensity level resolution is usually given in terms ofthe number of bits used to store each intensity level
Number of BitsNumber of Intensity
Levels Examples
1 2 0, 1
2 4 00, 01, 10, 11
4 16 0000, 0101, 11118 256 00110011, 01010101
16 65,536 1010101010101010
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Intensity Level Resolution (cont)
128 grey levels (7 bpp) 64 grey levels (6 bpp) 32 grey levels (5 bpp)
16 grey levels (4 bpp) 8 grey levels (3 bpp) 4 grey levels (2 bpp) 2 grey levels (1 bpp)
256 grey levels (8 bits per pixel)
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Resolution: How Much Is Enough?
The big question with resolution is alwayshow much is enough?
This all depends on what is in the image andwhat you would like to do with it
Key questions include Does the image look aesthetically pleasing?
Can you see what you need to see within the
image?
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Summary
We have looked at:
Human visual system
Light and the electromagnetic spectrum
Image representation
Image sensing and acquisition Sampling, quantisation and resolution
Next time we start to look at techniques forimage enhancement