A neural network-based video bit-rate control algorithm for variable bit-rate applications of versatile video coding standard

Versatile video coding is a new video coding standard that has more capabilities and higher coding efficiency compared with its predecessor. Practical video storage and transmission applications face constrained buffer size and available bandwidth. It is necessary to design the appropriate rate control algorithm to overcome such challenges. In this paper, the non-linear relationship between consumed bits, buffer size, and quantization parameter is estimated by taking the advantages of artificial neural networks, and a rate control algorithm is developed for real-time variable bit rate applications of the versatile video coding standard. The proposed rate control algorithm performs the control action in only one step that results in faster control action. The experimental results show that the proposed algorithm controls the bit-rate as well as the buffer state. Also, the rate-distortion analysis shows that the well-known A-domain algorithm has only 2.7% bit-rate reduction in comparison with the proposed method.

Automated summary

This paper proposes a rate control algorithm based on artificial neural networks for real-time variable bit rate applications of the versatile video coding standard. The new algorithm achieves faster control action while effectively controlling both bit-rate and buffer state.