Digital Image Processing ECE.09.452/ECE.09.552 Fall 2009
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Transcript of Digital Image Processing ECE.09.452/ECE.09.552 Fall 2009
S. Mandayam/ DIP/ECE Dept./Rowan University
Digital Image ProcessingDigital Image Processing
ECE.09.452/ECE.09.552ECE.09.452/ECE.09.552 Fall 2009Fall 2009
Shreekanth MandayamECE Department
Rowan University
http://engineering.rowan.edu/~shreek/fall09/dip/
Lecture 1Lecture 1September 14, 2009September 14, 2009
S. Mandayam/ DIP/ECE Dept./Rowan University
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http://hubblesite.org/
“Pillars of Creation” Eagle Nebula (M16)
Supernova remnant: Crab Nebula Jupiter
Galaxies from Ultra-Deep-Field
S. Mandayam/ DIP/ECE Dept./Rowan University
S. Mandayam/ DIP/ECE Dept./Rowan University
ABA E-13B FontABA E-13B Font
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S. Mandayam/ DIP/ECE Dept./Rowan University
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S. Mandayam/ DIP/ECE Dept./Rowan University
BiometricsBiometrics
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PlanPlan• What is an image?
• Mathematical representation of monochromatic images• What is a digital image?
• Digital image processing• Fundamental steps• Why do we need this?
• Course logistics• Self-Assessment Test
• Sampling & Quantization• Image Preprocessing• Pre-Lab 1
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ImagesImages
xy
f(x, y)row
column
Sample
Quantize
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Digital ImageDigital Image
.....
.....
....120
....255
..1127128x
y
GrayLevel
f(x,y)
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Color ImagesColor Images
R B
G
W
M
CY
Mixtures of Light: Additive Primaries
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R+G+BRG
B
R+G+BRG
B
R+G+BRG
B
R+G+BRG
B
R+G+BRG
B
R+G+BRG
B
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RGB Color SpaceRGB Color Space
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Fundamental StepsFundamental Steps
ImageAcquisition
ImageAcquisition
Preprocessing Preprocessing SegmentationSegmentation Representation &Description
Representation &Description
Recognition &Interpretation
Recognition &Interpretation
ProblemDomain
KnowledgeBase
KnowledgeBase
Result
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The Human EyeThe Human Eye
http://webvision.med.utah.edu/anatomy.html
Section of human retinaSagittal section of adult human eye
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Perceived BrightnessPerceived Brightness
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Perceived ContrastPerceived Contrast
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Optical IllusionsOptical Illusions
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DIP: DetailsDIP: Details
Gray-level Histogram
Spatial
DFT DC T
Spectral
Digital Image Characteristics
Point Processing M asking Filtering
Enhancem ent
Degradation M odels Inverse Filtering W iener Filtering
Restoration
Pre-Processing
Inform ation Theory
LZW (gif)
Lossless
Transform -based (jpeg)
Lossy
Com pression
Edge Detection
Segm entation
Shape Descriptors Texture M orphology
Description
Digital Im age Processing
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DIP: Course LogisticsDIP: Course Logistics
http://engineering.rowan.edu/~shreek/fall09/dip/
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Sampling & QuantizationSampling & Quantization
• Samplingdemos/demo1sampling_and_quantization/demo_sampling.m
• Quantizationdemos/demo1sampling_and_quantization/demo_quant.m
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Image PreprocessingImage Preprocessing
Enhancement Restoration
SpatialDomain
SpectralDomain
Point Processing• >>imadjust• >>histeq
Spatial filtering• >>filter2
Filtering• >>fft2/ifft2• >>fftshift
• Inverse filtering• Wiener filtering
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Point ProcessingPoint Processing(Intensity Transformation)(Intensity Transformation)
s(x,y) = T{ r(x,y)}
TransformedGray Level
OriginalGray Level
TransformationFunction
>>imadjust
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Pre-Lab 1: Intro to Matlab IP Pre-Lab 1: Intro to Matlab IP ToolboxToolbox
http://engineering.rowan.edu/~shreek/fall09/dip/ipintro.html
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SummarySummary