For mobile multimedia systems, advances in battery technology have been much slower than those in memory, graphics, and processing power, making power consumption a major concern in mobile systems. The computational complexity of video codecs, which consists of CPU operations and memory accesses, is one of the main factors affecting power consumption. In this thesis, we propose a method that achieves near-optimal video quality while respecting user-defined bounds on the complexity needed to decode a video. We start by formulating a scenario with a single receiver as a rate-distortion optimization problem and we develop an efficient decoder-complexity-aware video encoding method to solve it. Then we extend our approach to handle multiple heterogeneous receivers, each with a different complexity requirement. Our experimental results show that our method can achieve up to 97% and an average of 97% of the optimal solution value in single receiver and multiple receiver scenarios, respectively.

With recent advances in computing and communication technologies, ubiquitous access to high quality multimedia content such as high definition video using smart phones, Netbooks, or tablets is a fact of our daily life. However, power is still a major concern for any mobile device, and requires optimization of power consumption using a power model for each multimedia application, such as a video decoder. In this paper, a generic decoding complexity model for the motion compensation (MC) process, which constitutes up to 25% of the computational complexity and hence power consumption of an H.264/AVC decoder, has been proposed. For the model to remain independent from a specific implementation or platform, it has been developed by analysing the MC algorithm as described in the standard. Simulation results indicate that the proposed model estimates MC complexity with an average accuracy of 95.63%, for a wide range of test sequences using both JM and x.264 software implementations of H.264/AVC. For a dedicated hardware implementation of the MC module the modeling accuracy is around 89.61%, according to our simulation results. It should be noted that in addition to power consumption control, the proposed model can be used for designing a receiver-aware H.264/AVC encoder, where the complexity constraints of the receiver side are taken into account during compression.

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In most video streaming applications the available bandwidth may vary during transmission due to the shared nature of IP networks. For efficient bandwidth utilization and in order to manage network congestions, the outgoing bitrate of a streaming application should adapt to changes in network traffic. Current encoders have no strategy for acting in response to bitrate variations that occur as a result of changes in network condition. The time it takes to adapt has a significant impact on the received video quality. A slower response means that more packets are dropped by the network, which in turn results in a lower video quality. Furthermore, a slower response makes the congestion to persist for a longer period of time.In this paper an improved adaptive rate control algorithm for the x264 encoder has been proposed. The proposed scheme is able to adapt the bitrate, by considering the available network capacity, much faster than the conventional method. Simulation results indicate that the proposed algorithm is able to adjust to a bitrate in less than 15 frames, where as it takes more than 42 frames for the conventional method to reach the same bitrate. Consequently, the proposed scheme has no quality degradation or packet loss in %83 of test cases where the bitstream has been exposed to various network conditions, while the conventional rate control reduces quality to 24.02 dB in average in all test cases but one. This improved performance has been achieved with minimum added computational complexity.

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