Digital Image Processing

University of Oulu

Digital Image Processing

Lecturer:

Janne Heikkilä

NOTICE: Lectures are held in Finnish, but the lecture slides are also available in English.

Assistant:

Matteo Pedone

Schedule:

Spring 2019 (period 4)

Lectures:

First lecture on 11th March.

Exercises:

First exercise on 18th March.

Assignments:

Several homework assignments with Python that must be completed within one week after they have been published. 

Notice! Matlab is no longer used in this course.

Requirements:

Homework assignments and a written exam.

Final exam: 6.5.2019

Summer exam: 17.6.2019

Grading:

Exam (2/3) and homework assignments (1/3)

Literature:

Lecture slides and exercise material.

Text book: 

Gonzalez R.C., Woods R.E.: Digital image processing, Third edition, Addison-Wesley, 2008. More information from here.
Notice! It is also possible to use the 2nd edition (2002) or the 4th edition (2017) of the book. Most of the content is the same.

Prerequisites:

Basic studies of mathematics (Matrix Algebra and Signal Analysis)

Basic Python programming skills

Registration:

Weboodi

 Learning outcomes:

 

Upon completion of the course the student:

- understands the basic theory of digital image processing and knows its main applications,

- is able to apply spatial and frequency domain and wavelet based methods in image enhancement, restoration, compression and segmentation.

 Contents:

 1. Fundamentals of digital images, 2. Image enhancement in spatial and frequency domains, 3.Image restoration, 4. Color image processing, 5. Wavelets, 6. Image compression, 7. Morphological image processing and 8. Image segmentation.

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