Multiresolution vector transform coding for video compression

  • Authors:

  • Brian DeCleene;Henrik Sorensen

  • Affiliations:

  • Department of Electrical Engineering, University of Pennsylvania, Philadelphia, PA;Department of Electrical Engineering, University of Pennsylvania, Philadelphia, PA

  • Venue:
  • ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: image and multidimensional signal processing - Volume V
  • Year:
  • 1993

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Abstract

This paper describes a new image and video compression algorithm based on block and vector transformations used in a multiresolution approach. 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 and vector Hadamard.