Research Article
An Adaptive Slice Type Decision Algorithm for HEVC Based on Local Luminance Histogram
@INPROCEEDINGS{10.1007/978-3-030-90196-7_28, author={Pengyu Liu and Yue Zhang and Shanji Chen and Kun Duan and Xuan Sun and Tenghe Cui}, title={An Adaptive Slice Type Decision Algorithm for HEVC Based on Local Luminance Histogram}, proceedings={Artificial Intelligence for Communications and Networks. Third EAI International Conference, AICON 2021, Xining, China, October 23--24, 2021, Proceedings, Part I}, proceedings_a={AICON}, year={2021}, month={11}, keywords={High Efficiency Video Coding (HEVC) Local luminance histogram Scene-change detection Slice type decision}, doi={10.1007/978-3-030-90196-7_28} }- Pengyu Liu
Yue Zhang
Shanji Chen
Kun Duan
Xuan Sun
Tenghe Cui
Year: 2021
An Adaptive Slice Type Decision Algorithm for HEVC Based on Local Luminance Histogram
AICON
Springer
DOI: 10.1007/978-3-030-90196-7_28
Abstract
Video frame type decision is one of the key factors affecting coding efficiency. Based on the framework of High Efficiency Video Coding (HEVC), an adaptive frame type decision algorithm based on local luminance histogram is proposed in this paper. Firstly, the local luminance histogram was calculated at the coding tree unit (CTU) level, and the difference of local luminance histogram between two frames was used to characterize the degree of inter-frame content variation. Secondly, scene-change frame is determined by comparing the degree of inter-frame content variation in the scene-change detection window, and it is defined as I frame. Finally, the Mini-GOP size is adaptively determined according to the correlation between the degree of inter-frame content variation and Mini-GOP size. GPB frame and B frame are adaptively determined for the video sequences with I frame defined. The experimental results show that, compared with the relevant algorithms in x265, the proposed algorithm can achieve efficient adaptive decision of video frame type under the premise of reducing the algorithm complexity by nearly 5%, and effectively improve the efficiency of video coding.
