Computational Complexity Optimization on H.264 Scalable/Multiview Video Coding

The H.264/MPEG-4 Advanced Video Coding (AVC) standard is a high efficiency and flexible video coding standard compared to previous standards. The high efficiency is achieved by utilizing a comprehensive full search motion estimation method. Although the H.264 standard improves the visual quality at low bitrates, it enormously increases the computational complexity. The research described in this thesis focuses on optimization of the computational complexity on H.264 scalable and multiview video coding. Nowadays, video application areas range from multimedia messaging and mobile to high definition television, and they use different type of transmission systems. The Scalable Video Coding (SVC) extension of the H.264/AVC standard is able to scale the video stream in order to adapt to a variety of devices with different capabilities. Furthermore, a rate control scheme is utilized to improve the visual quality under the constraints of capability and channel bandwidth. However, the computational complexity is increased. A simplified rate control scheme is proposed to reduce the computational complexity. In the proposed scheme, the quantisation parameter can be computed directly instead of using the exhaustive Rate-Quantization model. The linear Mean Absolute Distortion (MAD) prediction model is used to predict the scene change, and the quantisation parameter will be increased directly by a threshold when the scene changes abruptly; otherwise, the comprehensive Rate-Quantisation model will be used. Results show that the optimized rate control scheme is efficient on time saving. Multiview Video Coding (MVC) is efficient on reducing the huge amount of data in multiple-view video coding. The inter-view reference frames from the adjacent views are exploited for prediction in addition to the temporal prediction. However, due to the increase in the number of reference frames, the computational complexity is also increased. In order to manage the reference frame efficiently, a phase correlation algorithm is utilized to remove the inefficient inter-view reference frame from the reference list. The dependency between the inter-view reference frame and current frame is decided based on the phase correlation coefficients. If the inter-view reference frame is highly related to the current frame, it is still enabled in the reference list; otherwise, it will be disabled. The experimental results show that the proposed scheme is efficient on time saving and without loss in visual quality and increase in bitrate. The proposed optimization algorithms are efficient in reducing the computational complexity on H.264/AVC extension. The low computational complexity algorithm is useful in the design of future video coding standards, especially on low power handheld devices

A simplified rate control algorithm for H.264/SVC

The objective of scalable video coding is to enable the generation of a unique bitstream that can adapt to various bitrates, transmission channels and display capabilities. The scalability is categorised in terms of temporal, spatial, and quality. Effective Rate Control (RC) has important ramifications for coding efficiency, and also channel bandwidth and buffer constraints in real-time communication. The main target of RC is to reduce the disparity between the actual and target bit-rates. In order to meet the target bitrate, a predicted Mean of Absolute Difference (MAD) between frames is used in a rate-quantisation model to obtain the Quantisation Parameter (QP) for encoding the current frame. The encoding process exploits the interdependencies between video frames; therefore the MAD does not change abruptly unless the scene changes significantly. After the scene change, the MAD will maintain a stable slow increase or decrease. Based on this observation, we developed a simplified RC algorithm. The scheme is divided in two steps; firstly, we predict scene changes, secondly, in order to suppress the visual quality, we limit the change in QP value between two frames to an adaptive range. This limits the need to use the rate-quantisation model to those situations where the scene changes significantly. To assess the proposed algorithm, comprehensive experiments were conducted. The experimental results show that the proposed algorithm significantly reduces encoding time whilst maintaining similar rate distortion performance, compared to both the H.264/SVC reference software and recently reported work