Codec for multimedia services using wavelets and fractals.
Increase in technological advancements in fields of telecommunications, computers and television have prompted the need to exchange video, image and audio files between people. Transmission of such files finds numerous multimedia applications such as, internet multimedia, video conferencing, videophone, etc. However, the transmission and rece-ption of these files are limited by the available bandwidth as well as storage capacities of systems. Thus there is a need to develop compression systems, such that required multimedia applications can operate within these limited capacities. This dissertation presents two well established coding approaches that are used in modern' image and video compression systems. These are the wavelet and fractal methods. The wavelet based coder, which adopts the transform coding paradigm, performs the discrete wavelet transform on an image before any compression algorithms are implemented. The wavelet transform provides good energy compaction and decorrelating properties that make it suited for compression. Fractal compression systems on the other hand differ from the traditional transform coders. These algorithms are based on the theory of iterated function systems and take advantage of local self-similarities present in images. In this dissertation, we first review the theoretical foundations of both wavelet and fractal coders. Thereafter we evaluate different wavelet and fractal based compression algorithms, and assess the strengths and weakness in each case. Due to the short-comings of fractal based compression schemes, such as the tiling effect appearing in reconstructed images, a wavelet based analysis of fractal image compression is presented. This is the link that produces fractal coding in the wavelet domain, and presents a hybrid coding scheme called fractal-wavelet coders. We show that by using smooth wavelet basis in computing the wavelet transform, the tiling effect of fractal systems can be removed. The few wavelet-fractal coders that have been proposed in literature are discussed, showing advantages over the traditional fractal coders. This dissertation will present a new low-bit rate video compression system that is based on fractal coding in the wavelet domain. This coder makes use of the advantages of both the wavelet and fractal coders discussed in their review. The self-similarity property of fractal coders exploits the high spatial and temporal correlation between video frames. Thus the fractal coding step gives an approximate representation of the coded frame, while the wavelet technique adds detail to the frame. In this proposed scheme, each frame is decomposed using the pyramidal multi-resolution wavelet transform. Thereafter a motion detection operation is used in which the subtrees are partitioned into motion and non-motion subtrees. The nonmotion subtrees are easily coded by a binary decision, whereas the moving ones are coded using the combination of the wavelet SPIHT and fractal variable subtree size coding scheme. All intra-frame compression is performed using the SPIHT compression algorithm and inter-frame using the fractal-wavelet method described above. The proposed coder is then compared to current low bit-rate video coding standards such as the H.263+ and MPEG-4 coders through analysis and simulations. Results show that the proposed coder is competitive with the current standards, with a performance improvement been shown in video sequences that do not posses large global motion. Finally, a real-time implementation of the proposed algorithm is performed on a digital signal processor. This illustrates the suitability of the proposed coder being applied to numerous multimedia applications.