Listless Highly Scalable Set Partitioning in Hierarchical Trees Coding for Transmission of Image over Heterogenous Networks

This paper present a listless implementation of fully scalable image coding based on set partitioning in hierarchical trees algorithm. Fully Scalable set partitioning in hierarchical trees(FSSPIHT) image coding algorithm is a very effective state-of-art technique for compression of wavelet transformed images and having quality to give good compression efficiency, full embeddedness and rate scalability. However, the use of four continuously growing linked lists, limit its applications to achieve high quality images in memory constrained environments. The proposed Listless highly scalable set partitioning in hierarchical trees (LHS-SPIHT) coding is an attempt to implement(FSSPIHT) algorithm without lists, that uses state markers with only 4 bits/coefficients(on an average) to keep track of pixels, set and subsets information. Simulation results show that the proposed listless highly scalable SPIHT (FS-SPIHT) coder has nearly the same coding performance as that of SPIHT and FS-SPIHT. It requires significantly smaller memory compared to these coders and suitable for coding the image for transmission over heterogenous networks.