Math 155, Lecture 1, Winter 2017
Mathematical Imaging
Lecture Meeting Time: MWF 1.00PM - 1:50PM.
Lecture Location: MS 5118.
Discussion Section: Tuesday 1.00PM - 1:50PM, MS 5118.
Instructor: Luminita A. Vese
Office: MS 7620D
Office hours: Thursday 1-2pm.
E-mail: lvese[at]math.ucla.edu
Teaching Assistant: Baichuan Yuan. E-mail: byuan[at]math.ucla.edu.
Office: MS 6147.
Office hours: Tuesday 2-3pm and Wednesday 4-5pm.
Textbooks:
R.C. Gonzalez and R.E. Woods, Digital Image
Processing, 3rd edition, Prentice-Hall, 2008.
Pre-requisites: courses Maths 32B and Maths 33B, Maths 115A and PIC 10A.
Math 155 is an introductory course on mathematical models for image processing and analysis. The students will become familiar with basic concepts (such as image formation, image representation, image quantization, change of contrast, image enhancement, noise, blur, image degradation), as well as with mathematical models for edge and contour detection (such as the Canny edge detector), filtering, denoising, morphology, image transforms, image restoration, image segmentation, and applications. All theoretical concepts will be accompanied by computer exercises.
Useful Links:
PIC Lab: 2000 Math Sciences Building
http://www.pic.ucla.edu/piclab/
Textbook website
MATLAB documentation
More about Matlab
Quick Matlab Documentation (thanks to Prof. Chris Anderson, UCLA)
Class Web Page: http://www.math.ucla.edu/~lvese/155.1.17w/
Tutorial: Image Processing with Matlab (Pascal Getreuer)
Sections studied in the lecture (3rd Edition):
Introduction
1.4 Fundamental Steps in Digital Image Processing
2.3.4. A Simple Image Formation Model
2.4 Image Sampling and Quantization: 2.4.1, 2.4.2, 2.4.3, 2.4.4.
Chapter 3: Sections 3.1,
3.2 (3.2.1-3.2.4 except Bit-plane slicing), 3.3, 3.4, 3.5, 3.6.
Chapter 4: Sections 4.2, 4.4, 4.5,
4.6, 4.7, 4.8, 4.9, 4.10, 4.11.
Chapter 5: Sections
5.1, 5.2, 5.3, 5.4, 5.5, 5.6, 5.7, 5.8, 5.9, 5.10.
Chapter 10: Sections 10.2.5, 10.2.6.
...
Assignment Policy:
There will be weekly homework assignments on theoretical questions and
computer projects. Homework will be assigned every week and collected every Friday in class. The lowest homework score will be dropped.
Examinations:
One Midterm Exam: Monday, February 13 (in class).
One Final Exam: 03/21/2017, Tuesday, 3pm-6pm.
Sample questions for the final
These are closed note and closed book written exams.
Grading Policy:
HW 30%, Midterm 25%, Final 45%
Class materials:
SampleMatlabCode.m
Illustration of shifting the center of the FT in 1D
Matlab code for the example above of computing the DFT in 1D and shifting the center
Matlab code reproducing the result in Fig. 4.3, using the DFT and IDFT
Fig4.03(a).jpg
The following material is obtained from the book web page (including review material for students, solutions (student version), projects):
http://www.imageprocessingplace.com/
Errata to the textbook
Review material offered by the book authors
Homework Assignments, Projects & Practice Problems:
HW #1 Due on: Friday, January 20.
HW1.pdf
Image to download Fig3.08(a).jpg
HW #2 Due on: Friday, January 27.
HW2.pdf
HW #3 Due on: Friday, February 3.
HW3.pdf
HW3.tex
Image to download Fig3.37(a).jpg
HW #4 Due on: Friday, February 10.
HW4.pdf
HW4.tex
Image to download Fig3.37(a).jpg
Image to download Fig3.40(a).jpg
Image to download Fig5.26a.jpg
HW #5 Due on: Friday, February 17, or on Tuesday the following week.
HW5.pdf
HW5.tex
Image to download Fig5.26a.jpg
HW #6 Due on: Friday, February 24.
HW6.pdf
HW6.tex
Image to download Fig4.11(a).jpg
HW #7 Due on: Friday, March 3 or the following Monday.
HW7.pdf
HW7.tex
Image to download Fig5.26(a).jpg
HW #8 Due on: Friday, March 10.
HW8.pdf
HW8.tex
Image to download Fig5.07(a).jpg (original circuit board X-ray)
Image to download Fig5.07(b).jpg
Image to download Fig5.08(a).jpg
Image to download Fig5.08(b).jpg
HW #9 Due on: Friday, March 17.
HW9.pdf
HW9.tex
Image to download Fig5.26(a).jpg
Image to download Fig10.15a.jpg