Multiresolution vector transform coding for video compression

A novel image and video compression algorithm based on block and vector transformations used in a multiresolution approach is described. The algorithm is shown to yield substantial compression gains over regular block coding with only a small increase in the computational load. In particular, the transform efficiency on a first-order Markov process is demonstrated to exceed that of a block transformation and approach the efficiency of the full transformation as the correlation factor approaches unity. Experiments with real video data also illustrate the compression gains for a variety of vector transformations, including vector DCT (discrete cosine transform) and vector Hadamard. Combined with an inherent robustness to vector loss, the proposed transformation is very well suited for applications requiring low bit rates over a degraded channel such as packet video during network congestion.<>