An efficient and Highly Scalable Listless SPIHT Image Compression Framework

The set partitioning in hierarchical trees is a powerful image compression algorithm. It has reasonable complexity and produces rate scalable bit-stream. Unfortunately, SPIHT fails to explore the multi-resolution nature of wavelet transform as output bit-stream doesn't support resolution scalability. Moreover it requires huge memory complex management depends on utilizing lists with about 2.5 size. This paper proposes three related algorithms. first one modifies reduce its improve efficiency especially at low rates. second main contribution paper. provides simultaneous solution scalability problems SPIHT. Memory reduced by status bits average per pixel instead lists. Resolution maintained encoding levels increasing order within each coding pass. Another important attribute our algorithm that very little increment comparison original In contrast, existing solutions have much more complexity, and/or resources. third slightly lower than but same time, performance.