Schedule: 08.01.2019 - 19.02.2019
Teacher in charge (valid 01.08.2018-31.07.2020):
Contact information for the course (applies in this implementation):
Responsible Teacher: Petri Rönnholm (email@example.com)
Contact persons for assignments are announced in assignment instructions.
Teaching Period (valid 01.08.2018-31.07.2020):
III (spring term)
Learning Outcomes (valid 01.08.2018-31.07.2020):
To understand principles of sampling and reconstruction of a signal. To understand and apply Fourier transformation of images. To understand and apply linear space-invariant systems with images. To understand and apply basic digital image processing tasks, such as image restoration, image enhancement, image compression, and image correlation. To understand and apply how edges and interesting points can be extracted from images. To understand segmentation of digital images.
Content (valid 01.08.2018-31.07.2020):
The course gives fundamentals of signal processing focusing on digital images. Mathematical principles of image enhancing and restoration are given. The course also illustrates how areas, breaklines and interesting points, such as corners and centers of circles, can be extracted automatically from images.
Assessment Methods and Criteria (valid 01.08.2018-31.07.2020):
Examination and assignments
Elaboration of the evaluation criteria and methods, and acquainting students with the evaluation (applies in this implementation):
To pass the course, you need to have all
assignments accepted, seminar presentation given and examination passed. The final grade is a combination of
assignment, seminar points and examination grade. The maximum points
from assignments is á 30 points, i.e., total of 150 points. This is scaled (no
rounding) to range [0,5]. If the assignment report is returned after the
deadline, the maximum point from that assignment is 12 points (equals to grade
2). Seminar is a group work and it is graded from 0 to 3 points.
grade to pass the examination is 15/30 points. If the examination is passed,
seminar points are added to results (valid for one year).
grade is the rounded average of the assignment and examination grades
examination = 2, assignments = 4.5, grade = 3.25 -> 3
= 5, assignments = 3, grade = 4
Workload (valid 01.08.2018-31.07.2020):
Lectures (20 h), assignments (50 h), self-study (38 h), preparation for examination + examination (27 h)
Details on calculating the workload (applies in this implementation):
Lectures: 20 h
Self-study of lecture contents:
Assignments and seminar: 78 h
Preparation to examination: 27
Total workload: 135 h
Study Material (valid 01.08.2018-31.07.2020):
Lecture notes and additional literature
Substitutes for Courses (valid 01.08.2018-31.07.2020):
Maa-57.3130 Digitaalinen fotogrammetria I (4 op)
Course Homepage (valid 01.08.2018-31.07.2020):
Grading Scale (valid 01.08.2018-31.07.2020):
Details on the schedule (applies in this implementation):
More accurate timetable is published in the main page.