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Users prefer Jpegli over same-sized libjpeg-turbo or MozJPEG

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arxiv 2403.18589 v1 pith:RNFJHRI3 submitted 2024-03-27 eess.IV cs.CV

Martin Bruse , Luca Versari , Zoltan Szabadka , Jyrki Alakuijala This is my paper · ORCID
classification eess.IVcs.CV
keywords imageslibjpeg-turbomozjpegjpeglibitspixelqualityused
verification ladder T0 review T1 audit T2 compute T3 formal
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We performed pairwise comparisons by human raters of JPEG images from MozJPEG, libjpeg-turbo and our new Jpegli encoder. When compressing images at a quality similar to libjpeg-turbo quality 95, the Jpegli images were 54% likely to be preferred over both libjpeg-turbo and MozJPEG images, but used only 2.8 bits per pixel compared to libjpeg-turbo and MozJPEG that used 3.8 and 3.5 bits per pixel respectively. The raw ratings and source images are publicly available for further analysis and study.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. JPEG AIC2026: A large-scale dataset for fine-grained assessment of image coding

    eess.IV 2026-07 conditional novelty 7.0 of 10

    AIC2026 is a large-scale benchmark of 9,618 fine-grained distorted images spanning 17 conventional and learned codec configurations across 20 CVVDP-based perceptual levels.

  2. 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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