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Bj{\o}ntegaard Delta (BD): A Tutorial Overview of the Metric, Evolution, Challenges, and Recommendations

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arxiv 2401.04039 v1 pith:BXWGLPGW submitted 2024-01-08 cs.MM cs.ITeess.IVmath.IT

Nabajeet Barman , Maria G. Martini , Yuriy Reznik This is my paper · ORCID
classification cs.MMcs.ITeess.IVmath.IT
keywords metricdifferentevolutionmetricsproposedqualityresultsvarious
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The Bj{\o}ntegaard Delta (BD) method proposed in 2001 has become a popular tool for comparing video codec compression efficiency. It was initially proposed to compute bitrate and quality differences between two Rate-Distortion curves using PSNR as a distortion metric. Over the years, many works have calculated and reported BD results using other objective quality metrics such as SSIM, VMAF and, in some cases, even subjective ratings (mean opinion scores). However, the lack of consolidated literature explaining the metric, its evolution over the years, and a systematic evaluation of the same under different test conditions can result in a wrong interpretation of the BD results thus obtained. Towards this end, this paper presents a detailed tutorial describing the BD method and example cases where the metric might fail. We also provide a detailed history of its evolution, including a discussion of various proposed improvements and variations over the last 20 years. In addition, we evaluate the various BD methods and their open-source implementations, considering different objective quality metrics and subjective ratings taking into account different RD characteristics. Based on our results, we present a set of recommendations on using existing BD metrics and various insights for possible exploration towards developing more effective tools for codec compression efficiency evaluation and comparison.

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Cited by 4 Pith papers

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    Knowledge-distilled students with 64 or more channels match the rate-distortion performance of a 128-channel teacher while cutting memory by 68% and energy by 34%.

  3. Streamable Neural Video Compression: A Mixed Precision Approach for Cross-Platform Deployment

    eess.IV 2026-08 conditional novelty 4.0 of 10

    Running I-frames and feature-reset operations in FP32 while P-frames run in FP16 gives cross-GPU deterministic bitstreams with negligible compression-efficiency cost.

  4. The JPEG XL Image Coding System: History, Features, Coding Tools, Design Rationale, and Future

    cs.MM 2025-06 conditional novelty 2.0 of 10

    A detailed, author-written companion document to the JPEG XL standard, describing history, every coding tool, design rationale, and self-assessed compression performance claims.

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