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Lossless Compression of Correlated Images/Data with Low Complexity Encoder Using Distributed Source Coding Techniques

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Image Analysis and Recognition (ICIAR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3656))

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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.

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© 2005 Springer-Verlag Berlin Heidelberg

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Ali, M., Murshed, M. (2005). Lossless Compression of Correlated Images/Data with Low Complexity Encoder Using Distributed Source Coding Techniques. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2005. Lecture Notes in Computer Science, vol 3656. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11559573_38

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  • DOI: https://doi.org/10.1007/11559573_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29069-8

  • Online ISBN: 978-3-540-31938-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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