This course focuses on the state-of-the-art techniques for digital image and video technology. These techniques and their applications cover almost all areas of technical professions dealing with human interaction. A significant part of the course is focused on the methods of image signal processing and main hardware and software functional blocks of related imaging systems. The aim of the laboratory exercises is to familiarize with advanced methods for capturing, processing and reproduction of image information. Due to the fast progress in this area, the content of the lectures and exercises is being continuously updated.
Knowledge of linear algebra, mathematical analysis, and analysis of signals and systems.
1. Linear algebra for multidimensional signal processing, matrix representation of images, spectral representation.
2. Multiscale image processing, pyramidal decomposition, continuous and discrete wavelet transform.
3. Human visual system characteristics and models.
4. Real imaging systems and their transfer characteristics.
5. Modelling of image signals, basic models of noise, methods of image reconstruction, noise reduction.
6. Super-resolution, compressed sensing.
7. High dynamic range (HDR) image acquisition and reproduction.
8. Capturing and processing of images from light-field camera.
9. Parallelization of image processing algorithms, utilization of GPU.
10. Principles of 3D imaging, stereoscopic and volumetric imaging, digital holography.
11. TV systems with high-definition (HDTV, UHDTV), high frame rate (HFR) and a wide color gamut (WCG).
12. Projection technology, recording and reproduction of images in digital cinema (DCI).
13. Colorimetry in image technology and color management.
14. Acquisition and processing of scientific image data in astronomy and biomedicine.
1. Matrix representation for multidimensional image signals. Spectral representation of images.
2. Methods for Subjective and objective image quality methods assessment.
3. Image sharpening algorithms.
4. Superresolution (super-resolution) for image post-processing.
5. High dynamic range (HDR) image acquisition and transmission. Semester project assignment.
6. Acquisition and transmission of stereoscopic images.
7. Parallelization of selected image processing algorithms, utilization of GPU.
8. Measurement of transfer characteristics of digital cameras.
9. Measurement of the properties of photographic filters.
10. Measurement of image sensor parameters.
11. Scientific image data acquisition and preprocessing in astronomy and biomedicine.
12. Work on semester projects.
13. Presentation of semester projects.
14. Test, assessment.
 Gonzalez, R. C., Woods, R. E., Digital image processing, Upper Saddle River: Prentice-Hall, 2007.
 Gonzalez, R. C., Woods, R. E., Eddins, S. L., Digital image processing using MATLAB, Natick: Gatesmark, 2009.
 Woods, J. W., Multidimensional signal, image, and video processing and coding, Amsterdam: Academic Press, 2012.
 Milanfar, P., Super-resolution imaging, Boca Raton: CRC, 2011.
 Bovik, A. C., Handbook of image and video processing, Amsterdam: Elsevier, 2005.
 Cristobal, G., Schelkens, P., Thienpont, H., Optical and digital image processing: fundamentals and applications, Weinheim: Wiley, 2011.
 Dufaux, F., Pesquet-Popescu, B., Cagnazzo, M., Emerging technologies for 3D video: creation, coding, transmission and rendering, Chichester: Wiley, 2013.
 Mrak, M., Grgić, M, Kunt, M., High-quality visual experience: creation, processing and interactivity of high-resolution and high-dimensional video signals, Heidelberg: Springer, 2010.
 Reinhard, E., High dynamic range imaging: acquisition, display, and image-based lighting, Burlington: Morgan Kaufmann/Elsevier, 2010.
 Poynton, C., Digital video and HDTV algorithms and interfaces, Amsterdam: Morgan Kaufmann, 2003.