In the Name of Allah

Rapid advances in networking technologies and the explosive growth of the Internet in recent years have increasingly raised the heterogeneity issue (in end-users processing capabilities and access bandwidth) for transmission of visual information. The traditional approach of providing multiple bitstreams, each tailored for one class of decoding requirements to address the heterogeneity issue is very inefficient and only covers very limited classes of end-users. Scalable coding that generates a bitstream which consists of a set of embedded parts that offer increasingly better signal-tonoise ratio (SNR) and/or spatial and/or temporal resolution, is widely considered as a promising coding approach for image/video transmission in heterogeneous environments. This thesis presents a family of highly scalable wavelet-based image and video coding systems based on the powerful set partitioning in hierarchical trees (SPIHT) algorithm. A framework for highly scalable SPIHT (HS-SPIHT) coding is first introduced. The main idea is to separately encode each level of the spatial resolution subbands in the wavelet decomposed image to achieve spatial scalability, while benefiting from the tree structure and the efficient set partitioning rule defined by SPIHT to preserve the compression efficiency. In this framework two novel algorithms, HS-SPIHT-I and HS-SPIHT-II, are proposed. Both algorithms fully support SNR and spatial scalability for image coding and output flexible bitstreams that are