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Digital Image Processing
Lecture 1(Introduction)
Bu-Ali Sina UniversityComputer Engineering Dep.
Fall 2009
Introduction
“One picture is worth more than ten thousandwords”
Outline
� Syllabus� References� Course Plane� Grading and policies� Introduction to image processing
Introduction
Syllabus
MSRT References
References
“Digital Image Processing”, Rafael C.Gonzalez & Richard E. Woods,Addison-Wesley, 2002
Digital Image Processing Using matlabmuya
Recommended journals and conferences
•IEEE tran. On Image processing•Journal of Graphics, Vision and Image Processing(GVIP)•Image and Vision Computing•Computer Vision and Image Understanding•Journal of Visual Communication and ImageRepresentation•International Journal of Computer Vision•Machine Vision and Applications•Journal of Mathematical Imaging and Vision•Graphical Models and Image Processing
Course plan•Image fundamental•Image enhancement (Spatial domain)•Image transform (Fourier, DCT)•Image enhancement (Frequency domain)•Image restoration•Color image processing•Image compression•Morphological image processing•Image segmentation
Grading and PoliciesExams 50%
– Midterm 50% (25% of total) about 15/8/88– Final 50% (25% of total)
Final Project (25%)– One project (deadline is about 31/4/89)
Seminar (15%)– Every body present a seminar (select a subject until
15/8/88)Home works (10%)
– 5 home works
Hours: 10-12 Sat. and Mon (every two week)
Site: http://Profs.basu.ac.ir/khotanlou
Email:[email protected]
Contact: 8257410, 11 (324 )
ContentsThis lecture will cover:
– What is a digital image?– What is digital image processing?– History of digital image processing– State of the art examples of digital image
processing
What is a Digital Image?A digital image is a representation of a two-dimensional image as a finite set of digitalvalues, called picture elements or pixels
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What is a Digital Image? (contH)Pixel values typically represent gray levels,colours, heights, etcRemember digitization implies that a digitalimage is an approximation of a real scene
1 pixel
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What is digital image?An image: 2-d function
– I=f(x,y)– I: intensity(or color)– (x,y): coordinate– When (x,y) and I are finite and discrete quantities
-> digital image– pixels, picture elements, image elements, pels
Representing digital images
Pixels
Side story of Lena
1972 playboy: Miss Nov. 1997 Lena
Representing digital imagesMatrix form
f(0,0) f(0,1) … f(0,N-1)f(1,0) f(0,1) … f(1,N-1)
……
f(M-1,0) f(M-1,1) … f(M-1,N-1)MxN
bits to store the image = M x N x kgray level = 2k
Sources of digital images
Electromagnetic(EM) energyAcoustic imagingSynthetic (computer-generated) imaging
EM images (cont.)The same objects in different EM spectrum
Ultrasound images
Synthetic images
What is a Digital Image? (contH)Common image formats include:
– 1 sample per point (B&W or Grayscale)– 3 samples per point (Red, Green, and Blue)– 4 samples per point (Red, Green, Blue, and
“Alpha”, Opacity)
For most of this course we will focus on grey-scale images
What is Digital Image Processing?Digital image processing focuses on two majortasks
– Improvement of pictorial information for humaninterpretation
– Processing of image data for storage,transmission and representation for autonomousmachine perception
Some argument about where image processingends and fields such as image analysis andcomputer vision start
What is DIP? (contH)The continuum from image processing tocomputer vision can be broken up into low-,mid- and high-level processes
Low Level ProcessInput: ImageOutput: Image
Examples: Noiseremoval, imagesharpening
Mid Level ProcessInput: ImageOutput: Attributes
Examples: Objectrecognition,segmentation
High Level ProcessInput: AttributesOutput: Understanding
Examples: Sceneunderstanding,autonomous navigation
In this course we willstop here
Research fields
Low-level processing
Mid-level processing
High-level processing
Imageprocessing
Computervision
Early vision
Brain processing
Related fields
Image processing– Inputs and outputs are images– Extract attributes from images
Image analysisComputer vision
– Use computers to emulate human vision– Related to artificial intelligence (AI)
Pattern Recognition
History of Digital Image ProcessingEarly 1920s: One of the first applications ofdigital imaging was in the news-paper industry
– The Bartlane cable picturetransmission service
– Images were transferred by submarine cablebetween London and New York
– Pictures were coded for cable transfer andreconstructed at the receiving end on atelegraph printer
Early digital image
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History of DIP (contH)Mid to late 1920s: Improvements to theBartlane system resulted in higher qualityimages
– New reproductionprocesses basedon photographictechniques
– Increased numberof tones inreproduced images Improved
digital image Early 15 tone digitalimage
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History of DIP (contH)1960s: Improvements in computing technologyand the onset of the space race led to a surgeof work in digital image processing
– 1964: Computers used toimprove the quality ofimages of the moon takenby the Ranger 7 probe
– Such techniques were usedin other space missionsincluding the Apollo landings
A picture of the moon takenby the Ranger 7 probeminutes before landing
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History of DIP (contH)1970s: Digital image processing begins to beused in medical applications
– 1979: Sir Godfrey N.Hounsfield & Prof. Allan M.Cormack share the NobelPrize in medicine for theinvention of tomography,the technology behindComputerised AxialTomography (CAT) scans Typical head slice CAT
image
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History of DIP (contH)1980s - Today: The use of digital imageprocessing techniques has exploded and theyare now used for all kinds of tasks in all kindsof areas
– Image enhancement/restoration– Artistic effects– Medical visualisation– Industrial inspection– Law enforcement– Human computer interfaces
Examples: Image EnhancementOne of the most common uses of DIPtechniques: improve quality, remove noise etc
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Examples: The Hubble TelescopeLaunched in 1990 the Hubbletelescope can take images ofvery distant objectsHowever, an incorrect mirrormade many of Hubble’simages uselessImage processingtechniques wereused to fix this
Examples: Artistic EffectsArtistic effects areused to makeimages more visuallyappealing, to addspecial effects and tomake compositeimages
Examples: MedicineTake slice from MRI scan of canine heart, andfind boundaries between types of tissue
– Image with gray levels representing tissuedensity
– Use a suitable filter to highlight edges
Original MRI Image of a Dog Heart Edge Detection ImageImag
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Examples: GISGeographic Information Systems
– Digital image processing techniques are usedextensively to manipulate satellite imagery
– Terrain classification– Meteorology
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Examples: GIS (contH)Night-Time Lights of theWorld data set
– Global inventory ofhuman settlement
– Not hard to imaginethe kind of analysisthat might be doneusing this data
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Examples: Industrial InspectionHuman operators areexpensive, slow andunreliableMake machines do thejob insteadIndustrial vision systemsare used in all kinds ofindustriesCan we trust them?
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Examples: PCB InspectionPrinted Circuit Board (PCB) inspection
– Machine inspection is used to determine that allcomponents are present and that all solder jointsare acceptable
– Both conventional imaging and x-ray imagingare used
Examples: Law EnforcementImage processingtechniques are usedextensively by lawenforcers
– Number platerecognition for speedcameras/automated tollsystems
– Fingerprint recognition– Enhancement of CCTV
images
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Examples: HCI
Try to make human computerinterfaces more natural
– Face recognition– Gesture recognition
Does anyone remember theuser interface from “MinorityReport”?These tasks can beextremely difficult
Key Stages in Digital Image Processing
ImageAcquisition
ImageRestoration
MorphologicalProcessing
Segmentation
Representation& Description
ImageEnhancement
ObjectRecognition
Problem Domain
Colour ImageProcessing
ImageCompression
Key Stages in Digital Image Processing:Image Aquisition
ImageAcquisition
ImageRestoration
MorphologicalProcessing
Segmentation
Representation& Description
ImageEnhancement
ObjectRecognition
Problem Domain
Colour ImageProcessing
ImageCompression
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Key Stages in Digital Image Processing:Image Enhancement
ImageAcquisition
ImageRestoration
MorphologicalProcessing
Segmentation
Representation& Description
ImageEnhancement
ObjectRecognition
Problem Domain
Colour ImageProcessing
ImageCompression
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Key Stages in Digital Image Processing:Image Restoration
ImageAcquisition
ImageRestoration
MorphologicalProcessing
Segmentation
Representation& Description
ImageEnhancement
ObjectRecognition
Problem Domain
Colour ImageProcessing
ImageCompression
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Key Stages in Digital Image Processing:Morphological Processing
ImageAcquisition
ImageRestoration
MorphologicalProcessing
Segmentation
Representation& Description
ImageEnhancement
ObjectRecognition
Problem Domain
Colour ImageProcessing
ImageCompression
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Key Stages in Digital Image Processing:Segmentation
ImageAcquisition
ImageRestoration
MorphologicalProcessing
Segmentation
Representation& Description
ImageEnhancement
ObjectRecognition
Problem Domain
Colour ImageProcessing
ImageCompression
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Key Stages in Digital Image Processing:Object Recognition
ImageAcquisition
ImageRestoration
MorphologicalProcessing
Segmentation
Representation& Description
ImageEnhancement
ObjectRecognition
Problem Domain
Colour ImageProcessing
ImageCompression
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Key Stages in Digital Image Processing:Representation & Description
ImageAcquisition
ImageRestoration
MorphologicalProcessing
Segmentation
Representation& Description
ImageEnhancement
ObjectRecognition
Problem Domain
Colour ImageProcessing
ImageCompression
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Key Stages in Digital Image Processing:Image Compression
ImageAcquisition
ImageRestoration
MorphologicalProcessing
Segmentation
Representation& Description
ImageEnhancement
ObjectRecognition
Problem Domain
Colour ImageProcessing
ImageCompression
Key Stages in Digital Image Processing:Colour Image Processing
ImageAcquisition
ImageRestoration
MorphologicalProcessing
Segmentation
Representation& Description
ImageEnhancement
ObjectRecognition
Problem Domain
Colour ImageProcessing
ImageCompression
Fundamental steps in DIP
SummaryWe have looked at:
– What is a digital image?– What is digital image processing?– History of digital image processing– State of the art examples of digital image
processing– Key stages in digital image processing
