Lecture Notes

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Imaging Optics and Computational Imaging
Intern. Centre for Theoretical PHysics Winter College on Optics in Imaging Science, Trieste, Italy,
Jan. 30-Febr.12, 2011

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Advanced Image Processing Lab

Getting started
Lab. 1. Image Digitization: Discretization
Lab. 2. Image Digitization: Quantization
Lab. 3. Image Coding: Predictive Methods
Lab. 4. Image Coding: Transform Methods
Lab. 5. Image Global and Local Statistics
Lab. 6.
Statistical Image and Noise Models and Noise Diagnostics
Lab. 7.
Image Resampling and Geometrical Transformations
Lab. 8.
Target Location and Object Detection: Localization Accuracy and Reliability


Lab. 9. Target Location and Object Detection in Clutter Images
Lab. 10. Linear Filters for Image Restoration and Enhancement
Lab. 11.
Rank Filters for Image Restoration, Enhancement and Segmentation


Lab. 12. Image Perfecting and Enhancement

M-Files

Image Files

Advanced Demo Lab

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Advanced Digital Imaging Laboratory

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12 Lectures on Selected Topics in Image Processing

Synopsis

1

4.11.2008  @TB216

Lect. 1. Convolution integral and digital filters

2

7.11.2008 @TC163

Lect. 2. Fourier integral and Discrete Fourier Transforms

3

11.11.2008 @TB216

Lect. 3. Perfect resampling filter

4

14.11.2008 @TC163

Lect. 4. Implementations and applications of the Perfect Discrete Resampling Filters

5

18.11.2008 @TB216

Lect. 5. Precise numerical integration and differentiation

6

21.11.2008 @TC163

Lect. 6. Discrete sampling theorem

7

25.11.2008 @TB216

Lect. 7. Algorithms for reconstruction of signals from sparse samples and applications

8

28.11.2008 @TC163

Lect. 8. Target location as a parameter estimation task

9

2.12.2008 @TB216

Lect. 9. Accuracy and reliability of target location

10

5.12.2008 @TC163

Lect. 10. Target location in clutter

11

9.12.2008 @TB216

Lect. 11. Local adaptive transform domain scalar filters

12

12.12.2008 @TC163

Lect. 12. Local adaptive nonlinear filters

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Introduction to Digital Holography

Synopsis

 

Lecture plan: Spring 2009

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Date

Subject

1

Febr. 10

Lect. 1. Holography and Imaging Methods.

2

Febr. 17

Lect. 2. Holographic Transforms in Digital Computers

3

Febr. 24

Lect. 3 Digital Recording and Numerical Reconstruction of Holograms

4

March 3

Lect. 4. Computer Generated Holograms (CGH): principles

5

March 10

Lect. 5. Methods for Encoding CGH for Recording on Physical Media

6

March 17

Lect. 6. Optical Reconstruction of CGHs

7

March 24

Lect. 7. CHGs and Optical Information Processing

8

March 31

Lect. 8. CGHs and 3D Visual Communication

9

Apr. 7

Lect. 9.  Lect. 9.  Stochastic Noise Models in Imaging and Digital Holography

10

Apr. 14

Lect. 10.  Image Processing Methods in Digital Holography

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Computer-Generated Holograms and 3-D Visual Communication: a Tutorial

3DTV-CONFERENCE 2008
28-30 MAY 2008, ISTANBUL, TURKEY 

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Tutorial, EUSIPCO2000, Tampere, Finland, Sept. 2000
Advanced Image Processing Lab.:

Lecture 1. Signal Fast Sinc-interpolation
Lecture 2. Statistical Noise models and Diagnostics 
Lecture 3. Image Restoration, Enhancement and Segmentation: Linear Filters 
Lecture 4. Image Restoration, Enhancement and Segmentation: Nonlinear Filters 
Lecture 5. Image Parameter Estimation
Lecture 6.

 Target Location in Clutter 

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From Photography to *-Graphies: Unconventional Imaging Techniques

Tampere University of Technology, Finland, Sept.3 - 14, 2001

Lecture 1. Evolution of Imaging: Direct Image Plane Imaging  
Lecture 2. Evolution of Imaging: Transform Imaging 
Lecture 3. Principles of Fourier Optics
Lecture 4. Principles of Reconstructive Tomography 
Lecture 5. Discrete Representation of Imaging Transforms  
Lecture 6. Sinc-interpolation in Digital Imaging
Lecture 7. Speckle Noise in Coherent Imaging Systems 
Lecture 8. Methods and Means for Recording Computer Generated Holograms

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Holography and Microscopy
Tampere University of Technology, Finland, Sept. 19, 2002

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Selected Topics in Advanced Digital Signal and Image Processing

Tampere University of Technology, Finland, Aug. 15-19, 2005

 

Lect. 1. Optical transforms in digital holography

Lect. 2. FFT methods for digital image re-sampling: optimality, fast algorithms and application examples

Lect. 3. Numerical integration and differentiation of sampled data
Lect. 4. Spatial, temporal and inter-channel data fusion for image restoration and enhancement in long distance observation systems

Lect. 5. Redundancy of stereoscopic vision and new methods for 3-D stereoscopic image display

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Archive-TAU 1995-2008

Selected Topics in Image Processing

Synopsis               

 

 

 

Lecture 1. Imaging transforms                                                                                         

(2 hours)

Lecture 2. Imaging transforms in digital computers

(6 hours)

Lecture 3. Fast transform methods for image resampling

(6 hours)

Lecture 4. Efficient computational algorithms for digital image processing

(2 hours)

Lecture 5. Image data fusion

(4 hours)

Lecture 6. Digital holographic imaging

(6 hours)

Lecture 7. 3-D imaging and vision

(2 hours)

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Digital Image Processing: Applications

Lecture plan-2008
Introduction
Lecture 1. Principles of Image Digitization 
Lecture 2. Image Discretization 
Lecture 3. Image Quantization in Image and Transform Domains  
Lecture 4. Image Coding Methods
Lecture 5. Statistical Image and Noise Models 
Lecture 6. Imaging  Transforms  
Lecture 7. Discrete Representation of Imaging Transforms  
Lecture 8. Methods of Image Filtering and Resampling in Signal and Transform Domains   
Lecture 9. Image Quantification: Localization, Registration, Recognition 
Lecture 10. Target Location in Clutter 
Lecture 11. Image Restoration and Enhancement: Linear Filters
Lecture 12. Image Restoration, Enhancement and Segmentation: Nonlinear Filters  
Lecture 13. Methods of Image Perfecting and Enhancement  

Exercises
ForExperiments

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Biomedical Signal and Image Processing

Lecture 1. Signals and mathematical models 
Lecture 2 Digital representation of signals 
Lecture 3 Signal discretization by sampling 
Lecture 4 Element-wise quantization 
Lecture 5 Principles of signal and image coding 
Lecture 6 Signal transformations and their discrete representation. Digital filters 
Lecture 7 Discrete representations of Fourier Transform 
Lecture 8 Applications of DFT and SDFTs    
Lecture 9 Principles of signal parameter estimation  
Lecture 10 Signal reconstruction and enhancement: linear filters
Lecture 11Signal/image restoration: nonlinear filters
Lecture 12 Correlational averaging as a method for signal restoration
Lecture 13 Ultrasound image processing for quantitative analysis of fetal movement

Test signals and images for exercises

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Fundamentals of Image Processing

Introduction
Lecture 1. Imaging devices
Lecture 2. Elements of the theory of 2D signal processing
Lecture 3. Signal transformations and mathematical models of imaging systems
Lecture 4. Principles of signal digitization. Signal sampling  
Lecture 5. Image quantization
Lecture 6. Principles of image coding
Lecture 7. Digital representation of signal transformations
                                                                Properties of DFT
Lecture 8. Orthogonal Transforms in Digital Image Processing
Lecture 9. Statistical Image and Noise Models
Lecture 10. Principles of Image Restoration Lecture 11. Image enhancement
Exercise 1. Introduction to Matlab.  
Exercise 2.  Signal sampling
Exercise 3.  Image quantization  
Exercise 4.  Image coding  
Exercise 5.  Digital convolution ; Digital convolution demo  
Exercise 6.  Discrete Fourier Transforms 

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