Image processing and analysis

The course gives an introduction to image processing and analysis methods and algorithms. The course consists of two parts – basic and advanced. The basic part is primarily devoted to general principles of image acquisition, preprocessing and some simple analytical methods. The second part introduces several advanced methods for image analysis and classification as well as analysis of hyperspectral images. In both parts the theory is supplemented with real life examples and exercises.

The course is introductory and practical oriented, all lectures illustrate the theoretical material with real world examples, but the most of the methods are given without deep mathematical background. However, all corresponding math can be found in the books and articles, presented in reference section at the end of this document.

The first part of the course includes 7 lectures (120–150 minutes each) with live exercises. The second part includes 5 lectures and exercises. The outline of the lectures is given below. Most of the lectures have corresponding practice sets, where students will try the discussed methods. The practice sets as well as dataset with images, needed to complete the sets, are distributed among course participants.

Each part of the course has 2 ECTS points value. In order to evaluate the student activity a report is needed for each practice set. The reports should include all used images (originals and processed) and their descriptions, details of how a particular problem has been solved, answers to questions, student comments, necessary to understand what have been done, and conclusions.

The full course description can be found here. Look at the box on the left side of this page to download some course materials.