Computationally efficient techniques for H.264/AVC transcoding applications

Providing universal access to end-users is the ultimate goal of the communications, entertainment and broadcasting industries. H.264/AVC has become the coding choice for broadcasting, and entertainment (i.e., DVD/Blu-ray), meaning that the latest set-top boxes and playback devices support this new video standard. Since many existing videos had been encoded using previous video coding standards (e.g., MPEG-2), playing them back on the new devices will be possible only if they are converted or transcoded into the H.264/AVC format. In addition, even in the case that videos are compressed using H.264/AVC, transmitting them over different networks for different user applications (e.g., mobile phones, TV) will require transcoding in order to adapt them to different bandwidth and resolution requirements. This thesis tackled the H.264/AVC transcoding problems in 3 aspects. At first, we propose the algorithms that improve the resultant video quality of the transform-domain MPEG-2 to H.264/AVC transcoding structure. Transform-domain transcoding offers the least complexity. However, it produces transcoded videos suffering from some inherent video distortions. We provide a theoretical analysis for these distortions and propose algorithms that compensate for the distortions. Performance evaluation shows that the proposed algorithms greatly improve the resultant transcoded video quality with reasonable computational complexity. Second, we develop an algorithm that speeds up the process of the pixel-domain MPEG-2 to H.264/AVC transcoding. Motion re-estimation is the most time consuming process for this type of transcoding. The proposed algorithm accelerates the motion re-estimation process by predicting the H.264/AVC block-size partitioning. Performance evaluation shows the proposed algorithm significantly reduces the computational complexity compared to the existing state-of-the-art method, while maintaining the same compression efficiency. At last, we propose the algorithm that accelerates the transcoding process of downscaling a coded H.264/AVC video into its downscaled version using arbitrary downscaling ratios. To accelerate the process of encoding the downscaled video, the proposed algorithm derives accurate initial motion vectors for the downscaled video, thus greatly reducing the computational complexity of the motion re-estimation process. Compared to other downscaling state-of-the-art methods, the proposed method requires the least computation while yields the best compression efficiency.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat