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Digital Image Processing 0909.452.01/0909.552.01 Fall 2003. Lecture 6 October 13, 2003. Shreekanth Mandayam ECE Department Rowan University http://engineering.rowan.edu/~shreek/fall03/dip/. Plan. Digital Image Restoration Recall: Environmental Models Image Degradation Model - PowerPoint PPT Presentation
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S. Mandayam/ DIP/ECE Dept./Rowan University
Digital Image ProcessingDigital Image Processing0909.452.01/0909.552.010909.452.01/0909.552.01
Fall 2003Fall 2003
Shreekanth MandayamECE DepartmentRowan University
http://engineering.rowan.edu/~shreek/fall03/dip/
Lecture 6Lecture 6October 13, 2003October 13, 2003
S. Mandayam/ DIP/ECE Dept./Rowan University
PlanPlan• Digital Image Restoration
• Recall: Environmental Models• Image Degradation Model• Image Restoration Model• Point Spread Function (PSF) Models
• Linear Algebraic Restoration• Unconstrained (Inverse Filter, Pseudoinverse Filter)• Constrained (Wiener Filter, Kalman Filter)
• Lab 3: Digital Image Restoration
S. Mandayam/ DIP/ECE Dept./Rowan University
DIP: DetailsDIP: Details
Gray-level Histogram
Spatial
DF T 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)
Loss less
Transform -based (jpeg)
Lossy
Com pression
Edge Detection
Segm entation
Shape Descriptors Texture M orphology
Description
Digital Im age Process ing
S. Mandayam/ DIP/ECE Dept./Rowan University
Image PreprocessingImage Preprocessing
Enhancement Restoration
SpatialDomain
SpectralDomain
Point Processing• >>imadjust• >>histeq
Spatial filtering• >>filter2
Filtering• >>fft2/ifft2• >>fftshift
• Inverse filtering• Wiener filtering
S. Mandayam/ DIP/ECE Dept./Rowan University
Degradation ModelDegradation Model
f(x,y) h(x,y) g(x,y)
n(x,y)
Degradation Model: g = h*f + n
demos/demo5blur_invfilter/demos/demo5blur_invfilter/degrade.m
S. Mandayam/ DIP/ECE Dept./Rowan University
Restoration ModelRestoration Model
f(x,y) DegradationModel f(x,y)Restoration
Filter
Unconstrained Constrained• Inverse Filter• Pseudo-inverse Filter
• Wiener Filter
demos/demo5blur_invfilter/
S. Mandayam/ DIP/ECE Dept./Rowan University
ApproachApproach
demos/demo5blur_invfilter/
f(x,y)
Builddegradation model
Formulate restoration algorithms
f(x,y)
Analyze usingalgebraic techniques
Implement usingFourier transforms
g = h*f + n
g = Hf + nW -1 g = DW -1 f + W -1 n
f = H -1 g
F(u,v) = G(u,v)/H(u,v)
S. Mandayam/ DIP/ECE Dept./Rowan University
Degradation & Restoration Examples: Gonzalez & WoodsDegradation & Restoration Examples: Gonzalez & WoodsAtmospheric Turbulence Model
S. Mandayam/ DIP/ECE Dept./Rowan University
Degradation & Restoration Examples: Gonzalez & WoodsDegradation & Restoration Examples: Gonzalez & WoodsExample 5.11: Inverse Filtering
S. Mandayam/ DIP/ECE Dept./Rowan University
Degradation & Restoration Examples: Gonzalez & WoodsDegradation & Restoration Examples: Gonzalez & WoodsExample 5.12: Wiener Filtering
S. Mandayam/ DIP/ECE Dept./Rowan University
Degradation & Restoration Examples: Gonzalez & WoodsDegradation & Restoration Examples: Gonzalez & WoodsExample 5.10: Planar Motion Model
S. Mandayam/ DIP/ECE Dept./Rowan University
Degradation & Restoration Examples: Gonzalez & WoodsDegradation & Restoration Examples: Gonzalez & WoodsExample 5.13: Inverse and Wiener Filtering
S. Mandayam/ DIP/ECE Dept./Rowan University
Lab 3: Digital Image Lab 3: Digital Image RestorationRestoration
http://engineering.rowan.edu/~shreek/fall03/dip/lab3.html
S. Mandayam/ DIP/ECE Dept./Rowan University
SummarySummary