| Video streaming applications over IP networks have attracted a lot of attention recently as a key enabling technology for future video distribution. In the first part of this research (i.e. Chapters 3--5), we seamlessly integrate video preprocessing, error resilient scalable source coding, constant quality rate adaptation, prioritizing packetization, and DiffServ based QoS networks into one system in this research.;A constant quality video rate control (CQVRC) scheme is proposed for non-scalable MPEG4 video to meet both the constant bit-rate (CBR) channel and the receiver buffer constraints in Chapter 3. CQVRC exploits a large decoder buffer, future frame information and temporal scene segmentation to achieve much smoother video quality than previous rate control schemes such as TM5 and MPEG4 VM. CQVRC for scalable video is realized by embedding the minimal R-D (rate-distortion) information and relying on a piecewise linear R-D model within an enhancement layer (EL).;By considering spatial temporal quality tradeoff, one sophisticated content-aware rate control (CARC) scheme is formulated. Both spatial quality and the temporal frame rate are jointly manipulated for the best performance. A scalable video streaming system incorporating CARC is also presented.;Delivering MPEG4-FGS bitstream over the DiffServ network is investigated in Chapter 5. It is shown that, although the prioritized stream benefits from the prioritized network, its gain is heavily dependent on how well the video source and network priorities match each other.;The second part of this research (i.e. Chapters 6 and 7) is focused on techniques to improve video quality for the digital video broadcasting (DVB) applications. The R-D optimization technique is investigated to handle both progressive and interlaced video in Chapter 6. Both quantization parameters and coding modes are optimized. Several heuristics are also developed to achieve results that are close to the optimal one at a much lower computational cost.;A fast algorithm to perform integer- and half-pel motion search for interlaced video is presented in Chapter 7 by exploiting the correlation between the frame- and the field-type integer-pel search as well as the correlation between integer-pel SAD and half-pel SAD. |
