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.
@article{arxiv.2202.07369,
title = {A Low-Parametric Model for Bit-Rate Estimation of VVC Residual Coding},
author = {Fabian Brand and Christian Herglotz and André Kaup},
journal= {arXiv preprint arXiv:2202.07369},
year = {2022}
}