Lossless compression of correlated images/data with low complexity encoder using distributed source coding techniques

  • Authors:

  • Mortuza Ali;Manzur Murshed

  • Affiliations:

  • Gippsland School of Comp. and IT, Monash University, Churchill, VIC, Australia;Gippsland School of Comp. and IT, Monash University, Churchill, VIC, Australia

  • Venue:
  • ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
  • Year:
  • 2005

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Abstract

This paper presents a novel lossless compression technique to transmit correlated images or data within sensor networks of inexpensive devices by exploiting the temporal correlation under the distributed source coding paradigm where the complexity of the encoder is much lower than that of the decoder. The technique operates in pixel-domain to avoid any lossy transform and relies on syndrome decoding of trellis codes by innovatively encoding the final state of the trellis. Experimental results on standard test video sequences proved superiority of this technique against the entropy based LZW lossless coding as well as a recently developed asymptotically lossless distributed source coding technique.