A Fast Selection Method of Skip Mode Based on Bayesian Minimal Risk Decision

A technology for risk decision-making and fast selection, applied in the field of video coding, to achieve the effect of reducing calculation and improving coding speed

Active Publication Date: 2018-07-03
SHANGHAI JIAOTONG UNIV
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AI Technical Summary

Problems solved by technology

In order to get the best coding performance, all CUs use recursive traversal to find the best coding mode. In this process, Rate-Distortion Optimization (RDO) technology will be used to get the best performance, but this will bring great Computational complexity

Method used

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  • A Fast Selection Method of Skip Mode Based on Bayesian Minimal Risk Decision
  • A Fast Selection Method of Skip Mode Based on Bayesian Minimal Risk Decision
  • A Fast Selection Method of Skip Mode Based on Bayesian Minimal Risk Decision

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Embodiment Construction

[0021] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0022] Such as figure 2 As shown, the flow chart of the SKIP mode rapid selection method based on Bayesian minimum risk decision-making in the present invention: firstly, the rate-distortion cost of the SKIP mode of the current coding unit is used as the decision feature, and the first four frames are studied online statistically, for different quantization parameters and For different coding unit depths, the conditional probability distributions of the decision features when the SKIP mode and no...

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Abstract

The present invention provides a method for quickly selecting SKIP mode based on Bayesian minimum risk decision-making. The specific steps are: firstly, the rate-distortion cost of the SKIP mode of the current coding unit is used as the decision feature, and the first four frames are studied online statistically, and for different quantization parameters and different coding unit depths, the conditional probability distributions of the decision features when the SKIP mode and non-SKIP mode are most preferred are respectively obtained through non-parametric probability density estimation. Then based on the statistical information of online learning, the Bayesian risk minimum model is used to make early judgments on the SKIP mode of the remaining frames. This method can quickly determine the SKIP mode while ensuring the encoding performance, thereby skipping other unnecessary calculations of the predictive encoding mode, which can effectively reduce the encoding complexity of the HEVC encoder, and is conducive to the implementation of the HEVC encoder. real-time applications.

Description

technical field [0001] The invention relates to the technical field of video coding, in particular to a fast selection of SKIP mode based on Bayesian minimum risk decision-making. Background technique [0002] With the rapid development of science and technology, people have higher and higher requirements for visual and audio quality, and high-definition video and ultra-high-definition video have begun to receive widespread attention. HEVC is a new generation of video compression standard and is regarded as the successor of the ITU-T H.264 / MPEG-4AVC standard. It was developed by ISO / IEC Moving Picture Experts Group (MPEG) and ITU-TVideo Coding Experts Group (VCEG) in 2004, and officially became an international video coding standard on January 26, 2013. HEVC is considered to not only improve image quality, but also achieve twice the compression rate of H.264 / MPEG-4AVC, that is, the bit rate is reduced by 50% under the same image quality. [0003] As a new-generation video ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N19/109H04N19/147
Inventor 张小云胡强石志儒高志勇陈立
Owner SHANGHAI JIAOTONG UNIV
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