Communication and Media Engineering (CME)
Digital Image Processing
|Recommended prior knowledge||
|Learning objectives / competencies||
The student will gain an overview on established and modern image processing techniques. The course provides tools, methods, models and techniques for the following topics: image formation, optics, imagers, color, image segmentation, image analysis, image features, image alignment, estimation in computer vision, programming and deep learning.
The student will understand basic problems in image processing and machine vision, e.g. image segmentation, feature detection, image matching or estimation problems in alignment.
He/she will know methods, algorithms and common techniques to solve the above mentioned problems.
The student will be able to computationally apply the methods on given low-level and higher-level image processing tasks in real world computer vision problems.
|Requirements for awarding credit points||
Digital Image Processing: written exam K60
|Credits and Grades||
4 CP, grades 1 ... 5
Prof. Dr.-Ing. Stefan Hensel
|Frequency||jedes 2. Semester|
Digital Image Proc.