Efficient Modeling and Low Complexity Implementation of Rate Estimation in Versatile Video Coding

In Versatile Video Coding (VVC), Rate-Distortion Optimized Quantization (RDOQ) is a widely adopted technique to strike a balance between bit rate and distortion. However, the computational complexity introduced by RDOQ poses significant challenges for real-time applications. To address this issue, we propose a low-complexity rate estimation model to accelerate the conventional RDOQ approach. Through comprehensive analysis, we have identified the generalized Gaussian distribution (GGD) as an efficient model for simulating the distribution of transform coefficients. Leveraging this insight, we developed a GGD-based rate estimator to expedite the selection of quantization levels. Experimental results demonstrate that the proposed model achieves an average encoding time reduction of 13.15%, with only a minimal impact on BD-Rate.

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Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10889055
Citations
1
Primary Topic
Advanced Data Compression Techniques
Type
article
Field-Weighted Citation Impact
1.28
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article

Efficient Modeling and Low Complexity Implementation of Rate Estimation in Versatile Video Coding

Hui Zhao, Jun Sun, Yanze Wang, Tianyi Sun
1 citations
Advanced Data Compression Techniques
1.28
article

Efficient Modeling and Low Complexity Implementation of Rate Estimation in Versatile Video Coding

Hui Zhao, Jun Sun, Yanze Wang, Tianyi Sun
article en
1 citations

Abstract

In Versatile Video Coding (VVC), Rate-Distortion Optimized Quantization (RDOQ) is a widely adopted technique to strike a balance between bit rate and distortion. However, the computational complexity introduced by RDOQ poses significant challenges for real-time applications. To address this issue, we propose a low-complexity rate estimation model to accelerate the conventional RDOQ approach. Through comprehensive analysis, we have identified the generalized Gaussian distribution (GGD) as an efficient model for simulating the distribution of transform coefficients. Leveraging this insight, we developed a GGD-based rate estimator to expedite the selection of quantization levels. Experimental results demonstrate that the proposed model achieves an average encoding time reduction of 13.15%, with only a minimal impact on BD-Rate.

Peking University (CN)
Openalex Percentile: Top 23%
Advanced Data Compression Techniques
1.28
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