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 journalArticle

22 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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