The research and teaching activities of the Division cover most aspects of modern imaging technology, from fundamental topics to the newest and currently fastest-growing fields: digital image processing together with multimedia techniques, multimedia data compression, image analysis and object recognition, and deep neural networks in digital media. A separate field is the digital processing of measurement signals and the improvement of measurement quality by means of digital signal processing methods. The Division’s teaching activities also include programming courses.

The Division comprises three laboratories:

The Laboratory of Deep Neural Network Applications in Digital Media works on applications of deep neural networks in various areas of multimedia processing, including object detection and recognition, data compression and steganography.

The Laboratory of Hardware Algorithms for Digital Media conducts research on the development and optimisation of algorithms and architectures for video data processing and compression. In particular, its research and development work covers:

  • modification of the software algorithms of video coding standards with a view to their efficient implementation in integrated circuits;
  • development of new methods for compressing multimedia and measurement data for transmission and archiving;
  • development of new hardware and hardware–software architectures for video compression and processing systems;
  • development of new hardware microarchitectures for individual modules of video codecs;
  • efficient mapping of architectures and microarchitectures onto programmable FPGA devices and ASICs.

The Laboratory of Digital Processing of Measurement Signals (CPSP) works on methods of processing measurement data:

  • in systems for monitoring older people (using radar sensors and depth sensors);
  • in optical signal analysis systems (in the wavelength range 200–1600 nm);
  • in acoustic signal analysis systems (in the frequency range 0–25 kHz).

The aim of this research is to develop a coherent methodology for processing measurement data, comprising:

  • methods for reconstructing the measurand;
  • methods for calibrating the measurement system;
  • methods for evaluating measurement uncertainty.