Abstract
The new version of the Context-based Adaptive Binary Arithmetic Coding (CABAC) that is used in the latest Versatile Video Coding (VVC) technology is the state-of-the-art in the field of entropy compression of video data. This paper gives an in-depth analysis of possible, further extensions of the CABAC technique for even more accurate estimation of the probabilities of coded data symbols. The paper considers four author’s examples of such extensions. With respect to these examples, the paper shows the practical limitations of further increasing the efficiency of the newest version of CABAC used in VVC. Results show that for the considered methods of improvements the limit of gain in compression is up to 0.2073% on average, when compressing the VVC video data.
Highlights
Today, as much as 80% of all the data that is transmitted in IT networks represents video
The goal of this paper is to provide an in-depth analysis of possible, further extensions of the method of estimating probabilities of bins in the Versatile Video Coding (VVC) Context-based Adaptive Binary Arithmetic Coding (CABAC) technique
REMARKS VVC CABAC is currently the most efficient entropy coding technique that is practically used in video compression
Summary
As much as 80% of all the data that is transmitted in IT networks represents video. In connection with the above entropy coding has been the object of intensive scientific studies for years Such works have especially been pursued in the context of video data compression. A milestone in this research was the development of the Context-based Adaptive Binary Arithmetic Coding (CABAC) technique in the early 2000s [9] This technique is a very sophisticated method of applying arithmetic coding [10], [11], [16], [34]–[38] for entropy compression of syntax elements data in a video encoder. The CABAC technique ranks among the most efficient entropy encoders for video data This is why it has found practical application in the three most advanced video compression technologies, developed.
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