New virtual SPIHT tree structures for very low memory strip-based image compression

Li Wern Chew, Li Minn Ang, Kah Phooi Seng

    Research output: Contribution to journalArticlepeer-review

    23 Citations (Scopus)

    Abstract

    Images obtained with wavelet-based compression techniques such as set-partitioning in hierarchical trees (SPIHT) yield very good results. However, a lot of memory space is required as the wavelet coefficients for the whole image need to be stored for the process of set-partitioning coding. In this letter, we propose new virtual SPIHT tree structures for very low memory strip-based image compression. The advantage of the proposed work is that it reduces the memory requirements for practical software and hardware implementations significantly without sacrificing performance.

    Original languageEnglish
    Pages (from-to)389-392
    Number of pages4
    JournalIEEE Signal Processing Letters
    Volume15
    DOIs
    Publication statusPublished - 01 Dec 2008

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