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SGN-3016 Digital Image Processing (5 cr)Lecturer: Moncef Gabbouj

Lectures: Period I, Room TB 110, Mondays 14.00-16.00

Periods II, Room TB 219, Mondays 14:00 – 16.00

Exercises and Assistants:

Dr. Esin Guldogan (Office TC 413)

Group 1: Thursdays 14.00-16.00, room TC 415

Group 2: Fridays 14.00-16.00, room TC 415

Course webpage: http://www.cs.tut.fi/~moncef/SGN-3016-DIP/SGN-3016-DIP.htm

First Lecture: Monday 7 September 2009

First Exercise: Thursday 17th September 2009 (Group 1), and Friday 18th September 2009 (Group 2)

Description: Basic principles and concepts of image processing will be covered in the course.

Textbook:

Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Third Edition, Prentice Hall, 2007, Chapters 1-6.

Other references:

The Image Processing Handbook, John C. Russ, Editor, CRC Press, 1999.

Introduction to Digital Image Processing with Matlab, A. McAndrew, Thomson, 2004.

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Course Outline

Chapter 1: Introduction to Digital Image Processing

Chapter 2: Digital Image Fundamentals

Chapter 3: Intensity Transformations and Spatial Filtering

Chapter 4: Filtering in the Frequency Domain

Chapter 5: Image Restoration and Reconstruction

Chapter 6: Color Image Processing

Chapter 8: Image Compression

Chapter 10: Image Segmentation

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Chapter 1: IntroductionEarly stages of digital photography

over

85-year old!

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Chapter 1: Introduction

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Chapter 1: Introduction

FIGURE 1.4 The first picture of the moon by a US spacecraft.

Ranger 7 took this image on July 31, 1964, about 17 minutes

before impacting the lunar surface (Courtesy of NASA)

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Chapter 1: IntroductionRadiation-based images

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Images based on radiation from ElectroMagnetic spectrum are most familiar,

e.g. X-ray images and visible spectrum images.

EM waves can be thought of as propagating sinusoidal waves of varying

wavelengths or as a stream of massless particles, each traveling in a wavelike

pattern and moving at the speed of light.

Each massless particle contains a certain amount (or bundle) of energy. Each

bundle of energy is called a photon.

If spectral bands are grouped according to energy per photon, we obtain the

spectrum below.

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Chapter 1: IntroductionRadiation-based images

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Each massless particle contains a certain amount (or bundle) of energy. Each

bundle of energy is called a photon.

If spectral bands are grouped according to energy per photon, we obtain the

spectrum below.

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Chapter 1: Introduction

Bone Scan PET Scan

Cygnus loop is a gas cloud

generated by a start in the

constellation of Cygnus

Gamma radiation from

a valve in a nuclear

reactor

notice the tumor

in the brain and

in the lung

notice the area of

strong radiation

Examples of

Gamma-ray

imaging

Center for Gamma-Ray Imaging, Univ of Arizona: http://www.radiology.arizona.edu/CGRI/research.html

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Chapter 1: IntroductionExamples of X-ray imaging

Chest X-ray

Image of blood

vessels

(angiogram)

X-ray of circuit board

Computerised

axial tomography

(CT) of the head

Cygnus loop in the

X-ray band

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Chapter 1: Introduction

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Chapter 1: IntroductionExamples of X-ray imaging

CT scan vs MRI imaging:

http://www.cancerhelp.org.uk/help/default.asp?page=149

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Chapter 1: IntroductionExamples of ultraviolet imaging

UV imaging is used in

lithography, industrial

inspection, microscopy, biological

imaging and astronomical

observations

UV is used in

fluorescence

microscopy, a

method to study

material which can

be made to

fluoresce.

Normal cornInfected corn

(by smut)

Cygnus loop in the

UV band

Smut corn disease

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Chapter 1: IntroductionImaging in the visible and IR bands

Examples of

light

microscopy

images

Applications

range from

enhancement to

measurements. 1.16

Chapter 1: Introduction

NASA’s Landsat satellite captures and transmits images of

Earth from space for the purpose of monitoring

environmental conditions on the planet. It uses both visible

and infrared regions of the spectrum.

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Chapter 1: Introduction

The Potomac river is clearly seen in all bands1.18

Chapter 1: Introduction

More hurricane pictures from

Plymouth State University

Weather Center

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Chapter 1: IntroductionHuman settlements in the Americas

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Chapter 1: Introduction

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Chapter 1: Introduction

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Chapter 1: Introduction

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Chapter 1: Introduction

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Chapter 1: Introduction

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Chapter 1: Introduction

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Chapter 1: Introduction

Examples of Scanning Electron Microscope (SEM) images

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Chapter 1: Introduction

Examples of computer generated images

Photographs from Sharjah

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Photographs from Tampere

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Chapter 1: Introduction

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Chapter 1: Introduction

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On an area array CCD, a

matrix of hundreds of

thousands of microscopic

photocells creates pixels

by sensing the light

intensity of small

portions of the film

image.

With digital photography,

the detector is a solid state

image sensor called a

charge coupled device,

(CCD) for short.

How are pictures made?

A basic image capture

system contains a lens

and a detector. Film

detects far more visual

information than is

possible with a digital

system.

Ref.: www.kodak.com/US/en/digital/dlc/book3/chapter1/digFundCapture1.shtml

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Types of Image Degradations (1/2)

lack of contrast

motion blur

image

enhancement

image

restoration1.34

Types of Image Degradations (2/2)

BLURRING

NOISE

image

enhancement

image

restoration

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Chapter 1: Introduction

Analog versus digital image processing

Analog image Digital image

+ imitates light intensity - records only samples of the

information rather than all of it

+ compactness + copy quality

+ scalability + freedom from noise

+ seamlessness + computer compatibility

http://www.videomaker.com/article/3250/ 1.36

Chapter 1: Introduction

Recall that an analog signal copies by imitating:

Light from the camcorder lens slams into a sensor on the imaging

chip, creating an electrical charge.

The stronger the light, the stronger the charge, which is to say

that the electrical signal is imitating the intensity of the light that

produced it.

Multiply this stimulus/response by several hundred thousand sensors

covering all three primary colors and you have the entire optical

image imitated by an electrical signal of rapidly and continuously

varying voltage.

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Chapter 1: Introduction

In a digital system, by contrast, the first thing that happens to the original

continuous signal is that it's fed through an analog/digital converter chip.

That chip looks at the signal hundreds of thousands of separate times per second

and assigns each discrete sampling a numerical value that corresponds to the

strength of the signal at that precise moment in time.

These numbers, rather than the signal itself, represent the digital image.

This means that digital recording differs from analog in two crucial ways:

It numerically encodes the information rather than electrically mimicking it

It records only samples of the information rather than all of it.

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Chapter 1: Introduction

Compactness

Information in analog image or video can be stored very efficiently and cheaply

(up to two and a half hours of video on one $1 VHS tape at SP speed).

High-quality digital video demands a huge amounts of storage space. For

example, DVDs (Digital Versatile Disks), must squeeze 4.7 gigabytes of data onto

a single side of the disk just to fit a feature-length movie and that's with a hefty

dose of compression.

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Chapter 1: Introduction

Scalability

All video, analog and digital, tends to look sharper and clearer on a smaller

screen; it's the natural result of squeezing the same amount of visual information

into a smaller space. All but the highest quality digital video, however, suffers

greatly from enlargement. When you blow up your digitized image onto a huge

home-theater TV screen, for example, all of those invisible digital compression

artifacts become quite noticeable--straight lines become jaggy, curves look

blocky, etc. Analog video, on the other hand, is much better at filling larger

screens with sharp-looking images.

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Chapter 1: Introduction

Seamlessness

In the audio world, some purists have returned to analog (vinyl LP) recordings

because they hear the fact that digital recordings only sample the signal at

intervals instead of copying the whole thing. To them, CDs sound hollow and

brittle as a consequence.

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Chapter 1: Introduction

Copy Quality

We talk about "copying" a digital image or a digital video file, but we are not

actually making a copy at all. Instead, we're making a transcription: rewriting the

information rather than duplicating it.

Instead of copying the video signal, digital duplication transcribes the numerical

code that describes that signal. If you transcribe it accurately, you can decode the

result into a daughter signal that is essentially indistinguishable from the parent.

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Chapter 1: Introduction

Freedom from NoiseNoise is any disturbance in an electrical current that is not part of the signal, and every

current carries a certain amount of this electrical garbage.

Since an analog dupe is an imitation, it happily copies the noise along with the parent

signal, while adding new noise in the process. That means that in each generation, the

noise level relative to the signal (signal-to-noise ratio) increases and the quality decreases

proportionately.

In digital recording, noise is not a problem because the signal consists entirely of current

pulses carrying information e.g. Morse code: power on = 1; power off = 0. If the voltage

level of the "power on" part of the signal is well above the noise level, then the

transcribing system can be set to respond only to current at that level and ignore the noise

entirely. So even if the process adds a small amount of its own noise, it never copies the

parental noise--nor does it pass on its own noise to the “copy”.

The result is that digital video can be copied through many generations without

appreciable quality loss. This is a massive improvement over analog video.

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Chapter 1: Introduction

Computer Compatibility

By far the biggest advantage of digital video is that a computer can process and store it.

For many years, professionals have digitized video, not only to take advantage of loss-free

duplicating, but also to perform image editing. Image editing means superimposing titles,

compositing multiple images, and adding effects like dissolves and wipes.

But as hard drives got bigger and faster, and as image compression techniques improved, it

became possible to digitize the signal and then keep it in that form indefinitely by storing

it in the computer.

Digital storage also saw the birth of nonlinear editing, with almost instant access to any

footage anywhere in the computer. This advantage is so great that digital video would

probably prevail over analog due to random (nonlinear) access alone.

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