Highly Scalable Single List Set Partitioning in Hierarchical Trees Image Compression

Abstract

A highly scalable image compression system produces a compressed image that can be easily decoded at several bit-rates (qualities) and resolutions (sizes). This is a very interesting feature in the heterogeneous environments of the Internet to satisfy the different user's requests. This paper proposes a new algorithm termed Highly Scalable-Single List-SPIHT (HS-SLS). The proposed HS-SLS algorithm produces a highly scalable bit-stream that is both rate and resolution scalable. The flexible bit-stream of the HS-SLS encoder can easily be adapted to various resolution requirements at any bit-rate using a very simple scaling process that is performed on-the-fly and without the need to decode the bit-stream. A unique feature of the new algorithm is that it has low memory requirement and low complexity due to its simple memory management. In addition, the size of the usable memory is fixed and thus can be predefined which avoids the dynamic memory allocation problem. These features make the HS-SLS algorithm very suitable for hardware implementation. The price paid for these valuable features is very slight decrement in the algorithm's performance as compared to the original SPIHT algorithm. Index Terms: Highly Scalable Image Compression, Low Memory Image Compression, Rate scalability, Resolution scalability, Set Partitioning image Compression, SPIHT, Wavelet image compression, Zero-tree coding.