Abstract
The H.266/Versatile Video Coding (VVC) standard is the latest video coding standards released by the Joint Video Exploration Group (JVET). These new technologies have brought more than 40% increase in compression rate and brought huge coding complexity. In order to reduce the coding complexity of VVC, we propose a fast Coding Unit (CU) partition decision algorithm combining Bayes algorithm and Improved De-blocking Filter (IDBF). The algorithm includes two stages. In the parameter update stage, the original VVC Test Model (VTM) is used to encode every certain video frame, and the Rough Mode Decision evaluation cost (JRMD) generated during the encoding process is used to update the parameters of the Bayes algorithm. In the fast coding stage, the video frame between two parameter update frames is encoded. First, the JRMD of the current CU is calculated and compares it with the split threshold to decide whether the current CU continues to split. If the current CU continues to be split, the current CU is divided into the same 16 simulation blocks, and the IDBF is used to calculate the texture direction and texture complexity of each simulation block. According to the texture features contained in the simulation block, the texture distribution position and texture complexity in the current CU can be judged, so that some bad candidate splitting modes can be discarded. Experimental results show that the proposed method can reduce the complexity of VVC about 56.08%, while Bjontegaard delta bit rate (BDBR) only increases by 1.30%.
Highlights
A good video coding standard helps reduce the volume of the video and keep the picture quality as unchanged as possible
We found that the algorithm that directly uses the rough mode decision (RMD) process calculation information to speed up the Coding Unit (CU) partition decision has a good effect
It includes two algorithms: Bayes-based CU partition decision algorithm and CU splitting mode decision algorithm based on Improved De-blocking Filter (IDBF)
Summary
A good video coding standard helps reduce the volume of the video and keep the picture quality as unchanged as possible. Regarding the related algorithms of statistical methods, [9] proposed an algorithm that can speed up CU splitting, which uses video texture complexity and Bayes decision. This algorithm can effectively terminate the CU partition early. Reference [16] proposed an adaptive mode decision algorithm based on video texture features for HEVC intra prediction. Reference [25] proposed an algorithm that uses statistical information This algorithm uses the standard deviation and the statistical characteristics of the number of split and non-split CUs to speed up the CU partition decision, and has achieved good results. The method uses an improved de-blocking filter to determine the CU separation mode
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