This diploma thesis focuses on current possibilities concerning the employment of wavelet transformation for video signal compression. One part of the work is devoted to the necessary execution of this task in practise. This deals with video signal and its features description, wavelet transformation and compression methods. The second part concentrates on description of selected compression method. It is the SPIHT (Set Partitioning In Hierarchical Trees) algorithm which is intended for compression of static image data. The algorithm is modified for usage with video signal compression which is specific for its time redundancy. The algorithm is called 3D SPIHT as it works in the spatial and time domain. The algorithm is implemented in the MATLAB programming environment which provides a sophisticated support for wavelet transformation (Wavelet Toolbox). To provide a simple and intuitive encoder control there has been developed an application delivering graphical user interface (GUI). On displayed image previews and measured graphs the user can change encoder parameters and monitor performed changes. There are four image test-sequential modes containing various scenes with different features. The final part of the work is focused on testing of the proposed encoding scheme, various image test-sequential modes and encoder settings. Measured values are graphically displayed and analyzed.

This master's thesis deals with lossless video compression. This thesis includes basic concepts and techniques used in image representation. The reader can find an explanation of basic difference between lossless video compression and lossy video compression and lossless video compression limitations. There is also possible find a description of the basic blocks forming the video codec (every block is described in detail). In every block there are introduced its possible variants. Implemented lossless videocodec was compared with common lossless videocodecs.