RD-Optimized Rate Shaping for Scalable Coded Streaming Video

Today, the wide variety of devices in the digital world ranges from desktops to mobile phones. Within the currently available interactive multimedia applications, which are very demanding in terms of video quality and coding efficiency, the cost as well as the limited performances of scalability obtained in the current standards remain unacceptable. That is why, there is a need for intrinsically scalable video coding schemes providing fully progressive bit streams. Scalable Video Coding targets on seamless delivery of digital content and access to the same, enabling optimal user centered multi-channel and cross-platform media services, providing a straightforward solution for universal video delivery to a broad range of applications. Scalable video coding gives a nice way to perform rate shaping for video streams adapting to the available transmission resource. The work in this thesis deals with a rate-distortion approach in Scalable Video Coding in order to achieve a performance that is comparable to a non-scalable system. The ratedistortion curves of the scaled video streams are employed to adapt to both static and dynamic channels. We consider a multi-user scenario which reflects network heterogeneity and propose to perform a joint optimization between these multiple streams which have different performance curves.