Low Memory Low Complexity Image Compression Using HS- SPIHT Encoder

Due to the large requirement for memory and the high complexity of computation, JPEG2000 cannot be used in many conditions especially in the memory constraint equipment. The line-based W avelet transform was proposed and accepted because lower memory is required without affecting the result of W avelet transform, In this paper, the improved lifting schem e is introduced to perform W avelet transform to replace Mallat method that is used in the original line-based wavelet transform. In this a three-adder unit is adopted to realize lifting scheme. It can perform wavelet transform with less computation and reduce memory than Mallat algorithm. The corresponding HS_SPIHT coding is designed here so that the proposed algorithm is more suitable for equipment. W e proposed a highly scale image compression scheme based on the Set Partitioning in Hierarchical Trees (SPIHT) algorithm. Our algorithm, called Highly Scalable SPIHT (HS_SPIHT), supports High Compression efficiency, spatial and SNR scalability and provides l bit stream that can be easily adapted to give bandwidth and resolution requirements by a simple transcoder (parse). The HS_SPIHT algorithm adds the spatial scalability feature without sacrificing the S NR embeddedness property as found in the original SPIHT bit stream. Highly scalable image compression scheme based on the SPIHT algorithm the proposed algorithm used, highly scalable SPIHT (HS_SPIHT) Algorithm, adds the spatial scalability feature to the SPIHT algorithm through the introduction of multiple resolution dependent lists and a resolution-dependent sorting pass. SPIHT keeps the import features of the original SPIHT algorithm such as compression efficiency, full SNR Scalability and low complexity.