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In this paper, a fast intra prediction algorithm for High Efficiency Video Coding (HEVC) is proposed by adopting the mode correlation between adjacent coding units. The proposed approach is realized by two pieces. Firstly, the prediction mode and partition structure for the current coding unit will inherit its optimal prediction coding unit directly if the Structural Similarity (SSIM) between the adjacent coding units satisfies the threshold condition. Secondly, unless the first case occurs, a two-step rough mode decision with adaptive threshold method including Sum of Absolute Difference (SAD) and Sum of Absolute Hadamard Transformed Difference (SATD) criterions is used to accelerate intra mode decision process based on HEVC test Model (HM) encoder. Besides, the most probable mode (MPM) which refers to the optimal prediction mode of the coded left and upper Prediction Units (PUs) surrounding the current PU is also considered. Experimental results show that the proposed algorithm can save 30.18 % encoding time on average with negligible loss of coding efficiency compared with HM10.0. The complexity and the bitrate are reduced by 11.45 and 0.46 % respectively compared with coding tree pruning method. [ABSTRACT FROM AUTHOR]

With advances in broadcasting technologies, people are now able to watch videos on devices such as televisions, computers, and mobile phones. Scalable video provides video bitstreams of different size under different transmission bandwidths. In this paper, a semantic scalability scheme with four levels is proposed, and tennis videos are used as examples in experiments to test the scheme. Rather than detecting shot categories to determine suitable scaling options for Scalable Video Coding (SVC) as in previous studies, the proposed method analyzes a video, transmits video content according to semantic priority, and reintegrates the extracted contents in the receiver. The purpose of the lower bitstream size in the proposed method is to discard video content of low semantic importance instead of decreasing the video quality to reduce the video bitstream. The experimental results show that visual quality is still maintained in our method despite reducing the bitstream size. Further, in a user study, we show that evaluators identify the visual quality as more acceptable and the video information as clearer than those of SVC. Finally, we suggest that the proposed scalability scheme in the semantic domain, which provides a new dimension for scaling videos, can be extended to various video categories. [ABSTRACT FROM AUTHOR]