Efficient Error Protection for Image and Video Transmission over Noisy Channels
Youssef Charfi · 2004
This dissertation discusses several aspects and proposes improved methods of joint source-channel coding for efficient image and video data transmission over noisy channels. First, we propose a joint source-channel coding system for fractal image compression. The system allocates the available transmission bitrate between the source and the channel coders using a Lagrange multiplier optimization technique and unequal error protection. Simulation results show that our method outperforms previous work in this field that only covered coding with a fixed-length fractal code. Secondly, we discuss our findings with regard to the real-time aspect of newly emerging systems for the protection of embedded wavelet bitstreams against bit errors and packet erasures. Recently proposed algorithms for the distortion-rate optimization of channel coding rate assignments to different parts of the compressed bitstream are not suited to many real-time applications, since they require the operational distortion-rate function of the source coder with a rather timeconsuming computation. We propose the use of parametric models, instead of the true operational distortion-rate curves. We further propose a Weibull model of the distortion-rate curve, and show its superiority to the previous models for real-time applications. The Weibull model is used in two important joint sourcechannel coding applications: Unequal error protection for the transmission of embedded image and video bitstreams over binary symmetric channels, and unequal loss protection for the transmission over packet erasure channels. Extensive simulations show, that using our parametric model instead of the true operational distortion-rate function, similar expected distortion is achieved, while, additionally, the real-time constraint is satisfied. The third segment of this study discusses distortion-rate optimization of the progressive error protection of embedded codes. This is of utmost importance in