optimized scalable video transmission based on conditional replenishment of jpeg2000 code-blocks with motion compensation
A video stored as a sequence of JPEG2000 images can provide the scalability, flexibility, and accessibility that is lacking in current predictive motion-compensated video coding standards; however, streaming this sequence would consume considerably more bandwidth. This paper presents a new method for optimized streaming of a JPEG2000 video that relies on motion compensation and server-optimized conditional replenishment to reduce temporal redundancy, in collaboration with an intelligent client policy for reconstructing the available content. In particular, we propose transmission of motion vectors and an optimized number of layers, possibly zero, for each code-block of the JPEG2000 representation of each new frame. We also proposethe use of a sliding window to optimize a group of frames such that code-blocks of these frames have more than one chance of being enhanced if that is beneficial to subsequent frames. Rate-distortion optimization in the Lagrangian sense is employed to achieve the lowest possible MSE. It is expected that mobile clients with their limited processing powers would benefit from this work in real-time and interactive applications, such as teleconferencing and surveillance. This paper introduces the concept, formulates optimization criteria, and compares the performance withalternative strategies.
teleconferencing video signal processing image coding image communication