Content-Driven Frame-Level Bit Prediction for Rate Control in Versatile Video Coding

Fuente: arXiv
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Autori principali: Premkumar, Amritha, Rajendran, Prajit T, Menon, Vignesh V, Herglotz, Christian
Natura: Preprint
Pubblicazione: 2026
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author Premkumar, Amritha
Rajendran, Prajit T
Menon, Vignesh V
Herglotz, Christian
author_facet Premkumar, Amritha
Rajendran, Prajit T
Menon, Vignesh V
Herglotz, Christian
contents Rate control allocates bits efficiently across frames to meet a target bitrate while maintaining quality. Conventional two-pass rate control (2pRC) in Versatile Video Coding (VVC) relies on analytical rate-QP models, which often fail to capture nonlinear spatial-temporal variations, causing quality instability and high complexity due to multiple trial encodes. This paper proposes a content-adaptive framework that predicts frame-level bit consumption using lightweight features from the Video Complexity Analyzer (VCA) and quantization parameters within a Random Forest regression. On ultra-high-definition sequences encoded with VVenC, the model achieves strong correlation with ground truth, yielding R2 values of 0.93, 0.88, and 0.77 for I-, P-, and B-frames, respectively. Integrated into a rate-control loop, it achieves comparable coding efficiency to 2pRC while reducing total encoding time by 33.3%. The results show that VCA-driven bit prediction provides a computationally efficient and accurate alternative to conventional rate-QP models.
format Preprint
id arxiv_https___arxiv_org_abs_2602_06242
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Content-Driven Frame-Level Bit Prediction for Rate Control in Versatile Video Coding
Premkumar, Amritha
Rajendran, Prajit T
Menon, Vignesh V
Herglotz, Christian
Image and Video Processing
Multimedia
Rate control allocates bits efficiently across frames to meet a target bitrate while maintaining quality. Conventional two-pass rate control (2pRC) in Versatile Video Coding (VVC) relies on analytical rate-QP models, which often fail to capture nonlinear spatial-temporal variations, causing quality instability and high complexity due to multiple trial encodes. This paper proposes a content-adaptive framework that predicts frame-level bit consumption using lightweight features from the Video Complexity Analyzer (VCA) and quantization parameters within a Random Forest regression. On ultra-high-definition sequences encoded with VVenC, the model achieves strong correlation with ground truth, yielding R2 values of 0.93, 0.88, and 0.77 for I-, P-, and B-frames, respectively. Integrated into a rate-control loop, it achieves comparable coding efficiency to 2pRC while reducing total encoding time by 33.3%. The results show that VCA-driven bit prediction provides a computationally efficient and accurate alternative to conventional rate-QP models.
title Content-Driven Frame-Level Bit Prediction for Rate Control in Versatile Video Coding
topic Image and Video Processing
Multimedia
url https://arxiv.org/abs/2602.06242