The Bjontegaard Bible -- Why your Way of Comparing Video Codecs May Be Wrong
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Abstract (arXiv)
In this paper, we provide an in-depth assessment on the Bjontegaard Delta. We construct a large data set of video compression performance comparisons using a diverse set of metrics including PSNR, VMAF, bitrate, and processing energies. These metrics are evaluated for visual data types such as classic perspective video, 360^circ video, point clouds, and screen content. As compression technology, we consider multiple hybrid video codecs as well as state-of-the-art neural network based compression methods. Using additional supporting points inbetween standard points defined by parameters such as the quantization parameter, we assess the interpolation error of the Bjontegaard-Delta (BD) calculus and its impact on the final BD value. From the analysis, we find that the BD calculus is most accurate in the standard application of rate-distortion comparisons with mean errors below 0.5 percentage points. For other applications and special cases, e.g., VMAF quality, energy considerations, or inter-codec comparisons, the errors are higher (up to 5 percentage points), but can be halved by using a higher number of supporting points. We finally come up with recommendations on how to use the BD calculus such that the validity of the resulting BD-values is maximized. Main recommendations are as follows: First, relative curve differences should be plotted and analyzed. Second, the logarithmic domain should be used for saturating metrics such as SSIM and VMAF. Third, BD values below a certain threshold indicated by the subset error should not be used to draw recommendations. Fourth, using two supporting points is sufficient to obtain rough performance estimates.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Apr 2023.
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Citing papers per year: 2025: 2; 2026: 2.
4 papers.
- 2025UGAE: Unified Geometry and Attribute Enhancement for G-PCC Compressed Point Cloudscited by 1
- 2025SineLoRADelta: Sine-Activated Delta Compressioncited by 0
- 2026DUGAE: Unified Geometry and Attribute Enhancement via Spatiotemporal Correlations for G-PCC Compressed Dynamic Point Cloudscited by 0
- 2026PaaF: Raising the perceived quality of INR-Based Image Compressioncited by 0
- 2026PaaF: Raising the perceived quality of INR-Based Image Compression19 Jun 2026
- 2026DUGAE: Unified Geometry and Attribute Enhancement via Spatiotemporal Correlations for G-PCC Compressed Dynamic Point Clouds27 Mar 2026
- 2025UGAE: Unified Geometry and Attribute Enhancement for G-PCC Compressed Point Clouds27 Oct 2025
- 2025SineLoRADelta: Sine-Activated Delta Compression28 May 2025