A Low-Parametric Model for Bit-Rate Estimation of VVC Residual Coding

TL;DR

This paper introduces a simple linear model with four features for fast and accurate bit rate estimation of residual blocks in VVC, improving over existing methods in accuracy and efficiency.

Contribution

It proposes a low-parametric linear model with four features for residual bit rate estimation in VVC, enhancing speed and accuracy over previous models.

Findings

Outperforms existing methods in mean absolute and relative error

Deviates less than 4 bits on average over large dataset

Efficient for real-time rate-control applications

Abstract

There are many tasks within video compression which require fast bit rate estimation. As an example, rate-control algorithms are only feasible because it is possible to estimate the required bit rate without needing to encode the entire block. With residual coding technology becoming more and more sophisticated, the corresponding bit rate models require more advanced features. In this work, we propose a set of four features together with a linear model, which is able to estimate the rate of arbitrary residual blocks which were compressed using the VVC standard. Our method outperforms other methods which were used for the same task both in terms of mean absolute error and mean relative error. Our model deviates by less than 4 bit on average over a large dataset of natural images.