Syllabus
| Course supervisor: | Dipl.-Ing. Wanda Benešová, PhD |
| Supervising department: | Institute of Applied Informatics (UAI FIIT) |
| Course objective: | In this course, the students achieve a basic understanding of the theory of digital image processing such as digital representation of visual information, image acquisition and image parameters, advanced sensor technologies for obtaining a 2D and 3D image information. Students will be familiar with the basic techniques such as image preprocessing, changing the dynamic scale, histogram methods, linear convolution method (edge filtering, blurring), noise reduction etc. In the field of computer graphics,the students will learn the basic principles of vector graphics, rasterization, basic geometric primitives, geometric transformation by matrix operations. A separate chapter will be given to an introduction to color theory. Key topics of the multimedia part are dedicated to: data compression of sound, image and video signal, the principle of data reduction in the spectral domain as well as the standard MP3, JPEG, JPEG2000 and MPEG compression standards. |
| Key words: | multimedia, data compression |
| Form of teaching: | lecture, laboratory/construction practice, project/semestral paper |
| Course methods: | Lectures Lab exercises During the semester, the students will work on a project using the computer vision C++ library OpenCV Intel. |
| Time allowance (lecture/seminar): | 2/3 |
| Course completion: | exercises (40%), midterm test (10%), final exam (50%) |
| Mode of completion and credits: | Exam (6 credits) |
| Type of study: | usual |
| Taught for the form of: | full-time, attendance method |
| Prerequisites for registration: | none |
| Regular assessment: | exercises (40%) midterm test (10%) |
| Final assessment: | final test(50%) |
Lectures
Image processing
- brief historical context of image processing, principles of human perception of visual information, applications in the area of image processing.
- signal sampling, digital representation of the image 2D signal, grayscale and color images,
- resolution in space, dynamics of the video signal, aliasing.
- capturing of the image in 2D/3D space, capturing of the color images
- linear filtration, convolution, basic filter kernels
- image edge detection, edge sharpening, thresholding
- basics of image enhancement, noise reduction
Computer graphics
- Introduction to computer graphics
- Point-plotting techniques
- Two-dimensional geometric transformation
- Clipping and drawing
- Color models (RGB, HLS, CMYK, CNS, CIE L*a*b*), Color Mapping
Digital signal processing and multimedia
- 1D/ 2D digital data acquisition, representation of data,
- 1D/ 2D linear discrete transform (Discrete Fourier Transform, Discrete Cosine Transform),
- data reduction in spectral domain, PCA ( Principal component analysis),
- standards of multimedia – audio and video data compression MPEG1,2,4,7
- audio processing:
Basics of digital audio, quantization and transmission of Audio. Audio Compression and psychoacoustic model, Audio MPEG