Texture-intensity-based fast coding unit size determination method for high-efficiency video coding intracoding
15 September 2014 Texture-intensity-based fast coding unit size determination method for high-efficiency video coding intracoding
Xiangqun Li, Xiaohai He, Xiaohong Wu, Zhengyong Wang
Author Affiliations +
Abstract
The quad-tree-based picture partition scheme in high-efficiency video coding (HEVC) provides significant coding efficiency improvements, particularly for high-resolution videos. However, its flexible block partitions and numerous intraprediction modes result in a substantial increase in computational complexity compared with previous video coding standards because of the necessity of determining the best coding unit (CU) partitions. A fast HEVC intracomputation method that uses image textural feature information instead of the traditional rate-distortion (R-D) cost value is proposed. This information is used to control the CU partition at the exterior of the xCompressCU function in the HEVC model coding framework. The method is comprised of two key steps: (1) simulation of the CU partition of the current frame image and calculation of the strength value of the textural features of each sub-block; and (2) disregard of some CU partition depths in the xCompressCU function, with no R-D cost calculation being required in the corresponding prediction mode. By leveraging these two steps, the computational complexity of the encoder is effectively lowered. Experimental results indicate that the proposed method reduces the coding time computational complexity of the current HEVC model by approximately 39.08% with negligible loss of coding efficiency.
© 2014 SPIE and IS&T 0091-3286/2014/$25.00 © 2014 SPIE and IS&T
Xiangqun Li, Xiaohai He, Xiaohong Wu, and Zhengyong Wang "Texture-intensity-based fast coding unit size determination method for high-efficiency video coding intracoding," Journal of Electronic Imaging 23(5), 053005 (15 September 2014). https://doi.org/10.1117/1.JEI.23.5.053005
Published: 15 September 2014
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Cited by 6 scholarly publications.
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KEYWORDS
Copper

Video coding

Computer programming

Video

Standards development

Image compression

Plutonium

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