Abstract
Determining the best partitioning structure for a given Coding Tree Unit (CTU) is one of the most time consuming operations within the HEVC encoder. The brute force search through quadtree hierarchy has a significant impact on the encoding time of high definition (HD) videos. This paper presents a fast coding unit size decision-taking algorithm for intra prediction in HEVC. The proposed algorithm utilizes a low complex texture analysis technique based on the local range property of a pixel in a given neighborhood. Simulation results show that the proposed algorithm achieves an average of 72.24% encoding time efficiency improvement with similar rate distortion performance compared to HEVC reference software HM12.0 for HD videos.
Highlights
Cisco’s Data Traffic forecast statistics show that 80-90% of the global Internet traffic will be video data by 2017, and a significant proportion of the above percentage will be high definition content [1]
Simulations were conducted on a range of high definition (HD) and CIF video sequences of natural and synthetic content
The second algorithm is the gradient based intra prediction method discussed in Satish et al [7]
Summary
Cisco’s Data Traffic forecast statistics show that 80-90% of the global Internet traffic will be video data by 2017, and a significant proportion of the above percentage will be high definition content [1]. HEVC is the latest video coding standard produced by Joint Collaborative Team on Video Coding (JCT-VC). HEVC supports multiple PU sizes that enhance inter and intra prediction processes. The HEVC encoder evaluates combinations of coding unit partitions and prediction modes to determine the best coding unit size and prediction mode for a given CTU. As a result, increased number of prediction modes and partition block sizes in return increases the complexity of rate-distortion (RD) optimization process. This paper introduces a fast and less complex coding unit size decision-taking algorithm for HEVC intra coding. Less computational power required for the texture analysis and savings from the early termination process of the proposed algorithm, altogether account for an average computational complexity saving of 72.24% for encoding HD videos, while maintaining a marginal impact on the coding efficiency.
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