Image Processing

Academic year 2019-2020, term 2



Instructor: Xiaolin Wu, ITB-A315

Extension: 24190

Email: xwu@ece.mcmaster.ca

Office hours: Tuesdays 2pm~4pm


Teaching Assistants:

Xiaohong Liu, ITB-A203, office hours: Tuesday 2~5pm.

Mehdi Ayyoubzadeh, ITB-A103, office hours: Wednesday 11:00~2:00pm.


Lectures: 3 hours/week

Tutorial:  1 hour/week                


Lecture Notes: week1.pdf; lecture3_enhancement_spatial.pdf; lecture4_enhancement_frequency.pdf; lecture5_restoration.pdf; Interpolation;segmentation; lecture8_registration.pdf; Visualization.pdf; morphology.pdf; color.pdf; lecture6_wavelet.pdf.



Course Objectives:


Outline of Topics:

·         Introduction

o   Applications of image processing

o   Elements of image processing system

·         Digital Image Fundamentals

o   Image perception

o   Sampling and quantization

o   Basic relationships between pixels

·         Image Enhancement

o   Point processing

o   Spatial filtering

o   Frequency domain method

·         Image Restoration

o   Degradation models

o   Inverse filtering

o   Minimum mean square error (Wiener) filtering

o   Constrained least squares filtering

·         Wavelets and multiresolution processing

o   Multiresolution expansion

o   Wavelet transforms in one dimension

o   Wavelet transforms in two dimensions

·         Image Compression

o   Elements of information theory

o   Lossless compression

o   Lossy compression

o   Image compression standards

·         Image Segmentation

o   Detection of discontinuities

o   Segmentation by thresholding

o   Region based segmentation

·         Image representation and description

o   Chain codes

o   Fourier descriptors

o   Moments

·         Color image processing

o   Color models

o   Pseudocolor image processing

o   Color transformation

·         Morphological image processing

o   Dilation and erosion

o   Opening and closing

o   Hit or miss transformation


Format: The course consists of class lecture sessions, tutorial session and a laboratory component. The lab component of the course consists of programming assignments and a small project.



Assignments: 5%

Quizzes: 20%

Final: 40%

Projects: 35%


Accreditation measurements: As part of the accreditation process for our undergraduate degrees, the Department is engaging in a “continuous improvement” process, part of which involves the assessment of  the development of desirable attributes amongst a student cohort as a whole. This process is independent of the grading of individual students. In this course, indicators related to the development of the following attributes will be measured: Problem Analysis, Design, Individual and Team Work, and Professionalism.



“Digital Image Processing, 3rd edition”, by R. Gonzalez and R. Woods, Prentice Hall, 2002.



************************ OLD MATERIALS **************************************


Reading material for contrast enhancement: ContrastTIP-xwu.pdf; octmslides.pdf

Image formation model paper ImageFormation.pdf


Sample questions of midterm quizzes: makeup.pdf


2010 Project, part 1 http://grads.ece.mcmaster.ca/~shux/4tn4/ass_1.html




Midterm sample questions: midterm15_1.pdf; midterm15_2.pdf