LEARNING OUTCOMES
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 and the possibilities to utilize neural networks.
Credits: 5
Schedule: 10.01.2023 - 21.02.2023
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Petri Rönnholm
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: Finnish, Swedish, English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
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 for whole curriculum period:
Examination and assignments
Workload
valid for whole curriculum period:
Lectures, assignments, self-study, preparation for examination + examination
DETAILS
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
SDG: Sustainable Development Goals
9 Industry, Innovation and Infrastructure
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language : English
Teaching Period : 2022-2023 Spring III
2023-2024 Spring IIIEnrollment :
Registration for the courses via Sisu (sisu.aalto.fi).