Video compression using 3D multiscale recurrent patterns

In this paper, we propose a new 3D pattern matching based video compression algorithm. Spatiotemporal prediction tools are used to exploit both the temporal and the spatial redundancies, and the resulting residue is encoded using a 3D data coding extension of the Multidimensional Multiscale Parser (MMP) algorithm. MMP was originally proposed as a generic lossy data compression algorithm. A high degree of adaptivity and versatility allowed it to be competitive with state-of-the-art transform-based compression methods for a wide range of applications and data sets. The performance of the proposed algorithm is compared with that of H.264/AVC, achieving close results for some data sets, which indicates the potential of the pattern matching paradigm as an alternative to the traditional hybrid video codecs.