Wavelet video coding with application in network streaming

In this dissertation, we propose to adopt the joint source-channel coding (JSCC) approach in the design of a wavelet-based fine granular scalable (WavFiGS) video codec, which targets the application of streaming compressed video over packet networks. The WavFiGS coding system consists of a base layer (BL) codec that employs a hybrid coding - motion compensation with discrete wavelet transform (DWT) - architecture and an error-resilient enhancement layer (EL) codec that uses a robust progressive bit-plane coding scheme.; We investigate the application of context modeling approach in embedded wavelet image coding and propose several novel schemes. The proposed image coding scheme is employed in the inter-frame coding of the BL. The inter-frame residual coding is completed by the proposed macro-block stack-run codec. The EL codec is based on error-resilient elementary Golomb (EG) coding and progressive bit-plane coding. The output bitstream of the EL coder can be fragmented in such a way that each delivered EL packet is decoded independently and contributes to the improvement of the reconstruction quality of the decoded video.; In order to study the performance of the WavFiGS, we propose an efficient transmission strategy to stream FGS videos. Based on the justification that the BL is essential to the reconstruction of a video signal and that the delivery of the EL is less critical, it is proposed that the BL be protected by forward error correction (FEC). The EL be left without any FEC and is only protected by the error resilience incorporated into the EL source coder. We also establish an analytical model to optimally determine the channel coding rate under different packet loss probabilities. The effectiveness of both the streaming strategy and the analytical model was corroborated by our experimental results.