Towards efficient video compression using scalable vector graphics on the Cell/B.E.

With the emergence of multi-core CPUs, parallel computing has made the leap from being a paradigm mainly used in high performance computing to imposing itself as one of the standards used in mainstream computing. The field of video compression and decompression naturally embraces parallel computing since video compression is a computationally intensive task that can be successfully distributed among two or more computing cores. This paper describes a different approach to video compression based on image vectorization on the novel Cell/B.E. architecture. Video frames are analyzed and interesting features such as edges, corners and patches are extracted, with significant performance speedups obtained on the Cell processor and maintaining good image quality. Finally, the features and the topological relations between them are used to reconstruct the original image.