Math 155, Lecture 1, Fall 2024

Mathematical Imaging

Lecture: MWF 3.00PM - 3:50PM (remote lectures over Zoom).

Discussion Section: Thursday 3.00PM - 3:50PM (MS 5117)

Instructor: Luminita A. VESE
Office: MS 7620D
Office hours (Instructor): Mon, Wed, Fri after lectures, or by appointment.
E-mail: lvese[at]math.ucla.edu

Teaching Assistant: Yunuo Chen. E-mail: yunuoch[at]math.ucla.edu
Office: MS 3957.
Office hours (T.A.): Thursday 12:30PM - 2:00PM.

Textbooks:
  • R.C. Gonzalez and R.E. Woods, Digital Image Processing, Prentice-Hall, 2018 (4th Ed.) (2nd and 3rd editions are very good; I will be using these).

    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/155.1.19w/
  • Tutorial: Image Processing with Matlab (Pascal Getreuer)

  • Undergraduate Summer School 2010 - An Introduction to Mathematical Image Processing (with lecture notes)

    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 with theoretical questions and computer projects.
    Matlab is the recommended programming language for the computational questions. However, you can use a different programming language of your choice.
    Homework assignments will be assigned every week and turned in, via upload, by Friday night, through Gradescope.
    The lowest homework score will be dropped.

    Examinations:
  • One Midterm Exam: Thursday, November 7, 3:00PM - 4:00PM (MS 5117).
  • One Final Exam: December 12, 2024, Thursday, 11:30am-2:30pm (location to be determined).
    These are closed note and closed book written exams.
    Sample questions for the final

    Grading Policy: HW 30%, Midterm 30%, Final 40%

    Class materials:
  • SampleMatlabCode.m
  • Sample code in Python (thanks to Jacob Moorman) samplePython.py
  • 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

    Additional images for optional projects
  • Fig. 5.13(a): Circuit image corrupted by additive Gaussian noise of zero mean and variance 1000
  • Fig. 5.14(a): Circuit image corrupted by salt-and-pepper noise
  • Fig. 5.19(a): Florida image
  • Fig. 5.20(a) Mars image

    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 (TO BE UPDATED):

    HW #1 Due on: Fri October 11, 2024.
    HW1-Fall2024.pdf HW1-Fall2024.tex
    Image to download Fig2.21(a).jpg

    HW #2 Due on: Fri Oct 18, 2024, or Mon Oct 21, 2024.
    HW2-Fall2024.pdf HW2-Fall2024.tex
    Image to download Fig3.08(a).jpg

    HW #3 Due on: Friday, October 25
    HW3-Fall2024.pdf HW3-Fall2024.tex
    Image to download Fig3.37(a).jpg

    HW #4 Due on: Friday, Nov 1st or on Monday, Nov 4th
    HW4-Fall2024.pdf HW4-Fall2024.tex
    Image to download Fig3.40(a).jpg
    Image to download Fig5.26a.jpg

    HW #5 Due on: Monday, Nov 11
    HW5-Fall2024.pdf HW5-Fall2024.tex
    Image to download Fig5.26a.jpg

    HW #6 Due on: Sunday, Nov 24
    HW6-Fall2024.pdf HW6-Fall2024.tex
    Image to download Fig4.11(a).jpg

    HW #7 Due on: Monday, December 2nd
    HW7-Fall2024.pdf HW7-Fall2024.tex
    Image to download Fig4.11(a).jpg

    HW #8 Due on: Wednesday, December 11
    HW8-Fall2024.pdf HW8-Fall2024.tex

    Image to download Fig5.26a.jpg
    Image to download Fig5.07(a).jpg (original circuit board X-ray)
    Image to download Fig5.07(b).jpg

    HW #9 Due on:

    Image to download Fig5.08(a).jpg
    Image to download Fig5.08(b).jpg Image to download Fig5.26(a).jpg
    Image to download Fig10.15a.jpg