Digital Image Processing: Digital Imaging Fundamentals
DIGITAL IMAGE PROSESSING Pertemuan-06 Dosen :Kundang K Juman Prodi Teknik Informatika , Fakultas Imu Komputer Digital Image Processing: Digital Imaging Fundamentals Brian Mac Namee
of Contents42 This lecture will cover:
- – The human visual system
- – Light and the electromagnetic spectrum
- – Image representation
- – Image sensing and acquisition
- – Sampling, quantisation and resolution
42 The best vision model we have!
Knowledge of how images form in the eye can help us with processing digital images We will take just a whirlwind tour of the human visual system of Structure Of The Human Eye
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The lens focuses light from objects onto the
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retina
g in ss ce
The retina is covered with
ro P e g
light receptors called
a m l I
cones (6-7 million) and
ita ig D s,
rods (75-150 million)
d o o W &
Cones are concentrated
z le za
around the fovea and are
n o G of Blind-Spot Experiment
42 Draw an image similar to that below on a
piece of paper (the dot and cross are about 6 inches apart) Close your right eye and focus on the cross with your left eye
of
42 of Image Formation In The Eye
42 Muscles within the eye can be used to
change the shape of the lens allowing us focus on objects that are near or far away An image is focused onto the retina causing rods and cones to become excited which ultimately send signals to the brain of Brightness Adaptation & Discrimination
42 The human visual system can perceive
10 approximately 10 different light intensity levels However, at any one time we can only discriminate between a much smaller number – brightness adaptation Similarly, the perceived intensity of a region Brightness Adaptation & Discrimination of
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Brightness Adaptation & Discrimination of
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Brightness Adaptation & Discrimination of
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An example of simultaneous contrast Brightness Adaptation & Discrimination of
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42 of Optical Illusions
42 Our visual
systems play lots of interesting tricks on us of Optical Illusions (cont…)
42 of Optical Illusions (cont…)
42 Stare at the cross
in the middle of the image and think circles Mind Map Exercise: Mind Mapping of
42 For Note Taking
Light And The Electromagnetic of
42 Spectrum
Light is just a particular part of the electromagnetic spectrum that can be sensed by the human eye The electromagnetic spectrum is split up according to the wavelengths of different forms of energy of Reflected Light
42 The colours that we perceive are determined
by the nature of the light reflected from an object For example, if white light is shone onto a
White L ight green object most
Colours Absorbed wavelengths are
Light Green absorbed, while green of Sampling, Quantisation And Resolution
42 In the following slides we will consider what
is involved in capturing a digital image of a real-world scene
- – Image sensing and representation
- – Sampling and quantisation
- – Resolution
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Before we discuss image acquisition recall
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that a digital image is composed of M rows
g in ss
and N columns of pixels
ce ro
col
P e
each storing a value
g a m l I
Pixel values are most
ita ig D s,
often grey levels in the
d o o W
range 0-255(black-white)
& z le za
We will see later on
n o G of Image Acquisition
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Images are typically generated by
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illuminating a scene and absorbing the
in ss ce
energy reflected by the objects in that scene
ro P e g a
- – Typical notions of
m l I ita
illumination and
ig D s,
scene can be way off:
d o o W
- X-rays of a skeleton
& z le za
- Ultrasound of an
n o G
unborn baby of Image Sensing
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Incoming energy lands on a sensor material
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responsive to that type of energy and this
in ss ce
generates a voltage
ro P e g a m
Collections of sensors are arranged to
l I ita ig
capture images
D s, d o o W & z le za n o G of Image Sensing
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A digital sensor can only measure a limited
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number of samples at a discrete set of
in ss ce
energy levels
ro P e g a m
Quantisation is the process of converting a
l I ita ig
continuous analogue signal into a digital
D s, d o o
representation of this signal
W & z le za n o G of Image Sampling And Quantisation
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Image Sampling And Quantisation of
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Remember that a digital image is always
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only an approximation of a real world
in ss ce
scene
ro P e g a m l I ita ig D s, d o o W & z le za n o G of Image Representation
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The spatial resolution of an image is determined by how sampling was carried out Spatial resolution simply refers to the smallest discernable detail in an image
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42 Spatial Resolution
- – Vision specialists will often talk about pixel size
- – Graphic designers will
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42 Intensity level resolution refers to the
number 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 of the number of bits used to store each intensity level
Number of Intensity
Number of Bits Examples
Levels
1 2 0, 1 of Intensity Level Resolution (cont…)
42 64 grey levels (6 bpp) 32 grey levels (5 bpp) 256 grey levels (8 bits per pixel) 128 grey levels (7 bpp)
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42 Resolution: How Much Is Enough?
The big question with resolution is always how much is enough?
- – This all depends on what is in the image and what 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?
Resolution: How Much Is Enough? of
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The picture on the right is fine for counting of Intensity Level Resolution (cont…)
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42 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 for