Resource-Constrained Low-Complexity Video Coding for Wireless Transmission

Constrained resources like memory, power, bandwidth and delay requirements in many mobile systems pose limitations for video applications. Standard approaches for video compression and transmission do not always satisfy system requirements. In this thesis we have shown that it is possible to modify and optimize conventional algorithms in order to convert them into low-complexity solutions and satisfy system constraints.
We have studied low-complexity approaches for video compression without motion estimation. We have proposed scalable (progressive) solutions for video compression with low memory consumption based on image coding standards. Scalability aspects were studied for distributed video coding as well. We have compared temporal scalability for distributed and scalable video coding and provided recommendations for the choice of one of these solutions based on the system requirements. Another comparison regarded power consumption for distributed video coding and H.264/AVC standard. We also proposed a scalable-to-lossless extension of transform domain Wyner-Ziv codec that allows bit savings compared to lossless coding by standard algorithms. Scalability aspects were also studied in perspective of video quality. We proposed a new metric for objective quality assessment that considers frame rate.
As many applications deal with wireless video transmission, we performed an analysis of compression and transmission systems with a focus on power-distortion trade-off. We proposed an approach for ratedistortion-complexity optimization of upcoming video compression standard HEVC. We also provided a new method allowing decrease of power consumption on mobile devices in 3G networks. Finally, we proposed low-delay and low-power approaches for video transmission over wireless personal area networks, including 60GHz fiber-wireless link.