EN CH

Digital Image Processing

(Spring 2016)

Course name:Digital Image Processing

Course code: EE346

Credit/class hours: 3/54

Time: 10:00~11:40 am on Mon. and 8:00~9:40 am on Thur. (odd-numbered weeks)

Classroom: 1-102, Dongzhong buildings

 

Textbook and References

(1)R.C. Gonzalez and R.E Woods, Digital Image Processing Third Edition , Publishing House of Electronic Industry, 2010 
(2)R.C. Gonzalez and R.E Woods, 阮秋琦、阮智宇等译 数字图像处理第三版中文版 , 电子工业出版社, 2011 
(3)R.C. Gonzalez, R.E Woods, and S.L. Eddins, 阮秋琦译 数字图像处理(MATLAB版)第二版 , 电子工业出版社, 2014
(4)熊红凯、孙军等, 数字电视信源编码技术与应用 , 电子工业出版社, 2012 
 

Course Details

This is an introductory course to the fundamentals of digital image processing, which is essential and necessary for further study and research in computer vision, computational photography, etc. We expect to cover topics such as image acquisition, intenstity transformation, image filtering in spatial and frequency domain, image restoration, morphological image processing, multiresolution image processing, image segmentation, image compression, some basic feature extraction and recognition tasks. Students will be required to complete several projects that are designed to substantially enhance their practical experience.

 

Requirements and Grading

Homework and attendance: 20%

Projects (2+1): 20%+20%

Final Exam: 40%

More information

 

Syllabus

Class Date Topic Lecture Note Assignments

Week 1-2

2/22,2/25,2,29

Introduction Lecture01_1
Lecture01_2
 
Week 3 
3/07
Digital Image Fundamentals Lecture02  

Week 3-5

3/10,3/14,3/21

Spatial Filtering Lecture03

Problem 3.7,

3.11, 3.23

Week 5-6

3/24,3/28

Frequency Filtering Lecture04

Problem 4.8(b),

4.22, 4.28, 4.33, 4.35 
Project 1

Week 7-8

4/07,4/11

Image Restoration Lecture05 Project 2 
restoration 
pocs
Week 9 
4/18,4/21

Multiresolution Processing

and Wavelets

Lecture07  

Week 10-11

4/25,5/02

Image Compression Lecture08  

Week 11-13

5/05,5/09,5/16

Image Segmentation Lecture09_1
Lecture09_2
 
Week 13 
5/19
Morphlogical Image Processing Lecture10  
Week 14 
5/23
Representation Lecture11  
Week 15 
5/30
Object Recognition    
Week 15 
6/02
Review    

 

Projects

You totally need to finish 3 projects, which consists of project 1, project 2, and one of project 3_1, project 3_2, and project 3_3. Your work is evaluated by both your code and report, and academic integrity is another major evaluation criterion. Please submit your work on time, otherwise you will get at most half of the score.

Project 1

Project 2

Project 3

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