ECE 468/568: Digital Image Processing



Instructor:
   Prof. Sinisa Todorovic
   sinisa at eecs oregonstate edu
   2107 Kelley Engineering Center

Classes:
   MWF 2-2:50pm, BAT 144

Office hours:
   T 2:30-3pm, or by appointment

HOME
 ASSIGNMENTS
eye



LECTURE NOTES:


Weeks
 Topics and Recommended Literature Notes
09/20
 Introduction: Administrative stuff and course overview;
Overview of fundamental problems and popular applications (Textbook: 1);

Matlab tutorial;
Image Processing Toolbox for Matlab;
 Lecture 1
09/25-09/29 Review of probability and statistics (by R. Gonzalez and R. Woods);

Image acquisition and representation (Textbook: 2.3, 2.4.2);
Image sampling and quantization (Textbook: 2.4);
Image interpolation (Textbook: 2.4.4);
Intensity transformations (Textbook: 3.2);
Histogram equalization (Textbook: 3.3.1);
Histogram specification (Textbook: 3.3.2);
Spatial convolution and correlation (Textbook: 3.4.2);
Smoothing spatial filters (Textbook: 3.5);
Sharpening spatial filters (Textbook: 3.5);

Detection of interest points;
MATLAB code for computing SIFT;

Homework 1
Lecture 2

Lecture 3

Lecture 4

Lecture 5

Lecture 6

Lecture 7

Lecture 8
10/02-10/06

 Discrete Fourier Transform of functions of one continuous variable (Textbook: 4.2-4.4); 2D Continuous Fourier Transform (Textbook: 4.5);

Homework 2
10/09-10/13
 2D Discrete Fourier Transform (Textbook: 4.6);
Frequency-domain image filtering (Textbook: 4.7);


10/16-10/20 Frequency-domain image filtering (Textbook: 4.7);
Smoothing, sharpening, unsharp masking in the frequency domain (Textbook: 4.8, 4.9);
Image restoration (Textbook: 5.1);
Noise models (Textbook: 5.2);
Lecture 10

Lecture 11

Lecture 12
10/23-10/27
 Restoration by spatial filtering (Textbook: 5.3);
Degradation models (Textbook: 5.6);
Noise reduction by frequency-domain filtering (Textbook: 5.4);
Computed Tomography (Textbook: 5.11.2),
Radon transform (Textbook: 5.11.3);
Fourier-slice theorem (Textbook: 5.11.4);

Homework 3
 Lecture 13

Lecture 14

Lecture 15
10/30-11/03
 Haar Series Expansion (Textbook: 7.2);
Preparation for the midterm exam
 Lecture 18
11/06-11/10 Midterm exam
Color (Textbook: 6);

No class on November 8

Homework 4
 Lecture 16

Lecture 17
11/20-11/22
1D Discrete Wavelet Transform (Textbook: 7.3);
1D Fast Wavelet Transform (Textbook: 7.4);
2D Wavelet Transform (Textbook: 7.5);
  

Lecture 22

Lecture 23

Lecture 24
11/27-12/01 Neural Networks (Textbook: 12.2.3); 
Exam 2: preparation; examination; solutions
 Lecture 25