Very low-memory wavelet compression architecture using strip-based processing for implementation in wireless sensor networks

Li Wern Chew, Wai Chong Chia, Li Minn Ang, Kah Phooi Seng

    Research output: Contribution to journalArticlepeer-review

    25 Citations (Scopus)

    Abstract

    This paper presents a very low-memory wavelet compression architecture for implementation in severely constrained hardware environments such as wireless sensor networks (WSNs). The approach employs a strip-based processing technique where an image is partitioned into strips and each strip is encoded separately. To further reduce the memory requirements, the wavelet compression uses a modified set-partitioning in hierarchical trees (SPIHT) algorithm based on a degree-0 zerotree coding scheme to give high compression performance without the need for adaptive arithmetic coding which would require additional storage for multiple coding tables. A new one-dimension (1D) addressing method is proposed to store the wavelet coefficients into the strip buffer for ease of coding. A softcore microprocessor-based hardware implementation on a field programmable gate array (FPGA) is presented for verifying the strip-based wavelet compression architecture and software simulations are presented to verify the performance of the degree-0 zerotree coding scheme.

    Original languageEnglish
    Article number479281
    JournalEurasip Journal on Embedded Systems
    Volume2009
    DOIs
    Publication statusPublished - 01 Dec 2009

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