Adaptive Video Frame Type Decision Algorithm Based on Local Luminance Histogram

LIU Pengyu; ZHANG Yue; JIA Kebin; DUAN Kun; LIU Chang; SUN Xuan; CUI Tenghe

doi:10.11999/JEIT211199

Volume 45 Issue 1

Jan. 2023

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Article Navigation > Journal of Electronics & Information Technology > 2023 > 45(1): 300-307

LIU Pengyu, ZHANG Yue, JIA Kebin, DUAN Kun, LIU Chang, SUN Xuan, CUI Tenghe. Adaptive Video Frame Type Decision Algorithm Based on Local Luminance Histogram[J]. Journal of Electronics & Information Technology, 2023, 45(1): 300-307. doi: 10.11999/JEIT211199

Citation:

LIU Pengyu, ZHANG Yue, JIA Kebin, DUAN Kun, LIU Chang, SUN Xuan, CUI Tenghe. Adaptive Video Frame Type Decision Algorithm Based on Local Luminance Histogram[J]. Journal of Electronics & Information Technology, 2023, 45(1): 300-307. doi: 10.11999/JEIT211199

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Adaptive Video Frame Type Decision Algorithm Based on Local Luminance Histogram

doi: 10.11999/JEIT211199

1.
The Information Department, Beijing University of Technology, Beijing 100124, China
2.
Advanced Information Network Beijing Laboratory, Beijing 100124, China
3.
Computational Intelligence and Intelligent Systems Beijing Key Laboratory, Beijing 100124, China

Funds: The National Key Research and Development Program of China (2018YFF01010100), The Beijing Natural Science Foundation (4212001), The Key R&D and Transformation Program of Qinghai Province (2022-QY-205)

Received Date: 2021-11-01
Rev Recd Date: 2022-03-25

Available Online: 2022-04-15

Publish Date: 2023-01-17

Abstract

Abstract

The video frame type decision is one of the key factors affecting the efficiency of video coding. This paper proposes an adaptive video frame type decision algorithm based on local luminance histogram to improve the x265 encoding performance. Firstly, the local luminance histograms of frames are calculated at the level of 64×64 Coding Tree Unit (CTU), and the difference of local luminance histogram between frames is used to represent the degree of scene variation between frames. Secondly, Intra-coded picture (I-frame) detection window is introduced. I-frame is determined by comparing the degree of scene variation between frames. Finally, the Mini Group Of Picture (MiniGOP) size is determined according to the correlation between the degree of scene variation and MiniGOP size, so as to determine adaptively Generalized P and B picture (GPB-frame) and Bidirectionally predicted picture (B-frame). Experimental results show that compared with the relevant algorithms in x265, the proposed algorithm can effectively reduce the coding complexity of x265, and decide I/GPB/B-frame efficiently and adaptively with nearly 5% less coding time.
- Video coding,
- x265,
- Local luminance histogram,
- Video frame type decision

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References(20)

References

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