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Lode Vandevenne

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    Benchmarking JPEG XL lossy/lossless image compression
    Evgenii Kliuchnikov
    Evgeniy Upenik
    Jon Sneyers
    Luca Versari
    Touradj Ebrahimi
    Optics, Photonics and Digital Technologies for Imaging Applications VI, SPIE (2020)
    Preview abstract JPEG XL is a practical, royalty-free codec for scalable web distribution and efficient compression of high-quality photographs. It also includes previews, progression, animation, transparency, wide gamut, and high bit depth. Experiments performed during standardization have shown the feasibility of economical storage without perceptive quality loss, lossless recompression of existing JPEG, and fast software encoders and decoders. We disclose the results of subjective and objective evaluations. Users expect faithful reproductions of ever-larger images. JPEG XL is faster to share and more economical to store: 60% savings vs. JPEG at equivalent visual quality. We quantify this impact using a subjective evaluation versus existing codecs including HEVC-HM-YUV444 and JPEG. New image codecs have to co-exist with the previous generation for several years. JPEG XL is unique in providing value for both existing JPEGs as well as new users. It includes coding tools to reduce the transmission and storage costs of JPEG by 22% while allowing byte-for-byte exact reconstruction of the original JPEG. Avoiding transcoding and additional artifacts helps to preserve our digital heritage. Applications require fast and low-power decoding. JPEG XL was designed to benefit from multicore and SIMD, and actually decodes faster than JPEG. We report the resulting speeds on ARM and x86 CPUs. To enable reproduction of these results, we open sourced the JPEG XL software in 2019. View details
    JPEG XL next-generation image compression architecture and coding tools
    Ruud van Asseldonk
    Moritz Firsching
    Thomas Fischbacher
    Sebastian Gomez
    Evgenii Kliuchnikov
    Robert Obryk
    Krzysztof Potempa
    Alexander Rhatushnyak
    Jon Sneyers
    Zoltan Szabadka
    Luca Versari
    SPIE Applications of Digital Image Processing, SPIE (2019)
    Preview abstract An update on the JPEG XL standardization effort: JPEG XL is a practical approach focused on scalable web distribution and efficient compression of high-quality images. It will provide various benefits compared to existing image formats: significantly smaller size at equivalent subjective quality; fast, parallelizable decoding and encoding configurations; features such as progressive, lossless, animation, and reversible transcoding of existing JPEG; support for high-quality applications including wide gamut, higher resolution/bit depth/dynamic range, and visually lossless coding. Additionally, a royalty-free baseline is an important goal. The JPEG XL architecture is traditional block-transform coding with upgrades to each component. We describe these components and analyze decoded image quality. View details
    Brotli: A General-Purpose Data Compressor
    Andrea Farruggia
    Paolo Ferragina
    Evgenii Kliuchnikov
    Robert Obryk
    Zoltan Szabadka
    ACM Transactions on Information Systems (2019)
    Preview abstract Brotli is an open source general-purpose data compressor introduced by Google in late 2013 and now adopted in most known browsers and Web servers. It is publicly available on GitHub and its data format was submitted as RFC 7932 in July 2016. Brotli is based on the Lempel-Ziv compression scheme and planned as a generic replacement of Gzip and ZLib. The main goal in its design was to compress data on the Internet, which meant optimizing the resources used at decoding time, while achieving maximal compression density. This article is intended to provide the first thorough, systematic description of the Brotli format as well as a detailed computational and experimental analysis of the main algorithmic blocks underlying the current encoder implementation, together with a comparison against compressors of different families constituting the state-of-the-art either in practice or in theory. This treatment will allow us to raise a set of new algorithmic and software engineering problems that deserve further attention from the scientific community. View details
    Preview abstract Guetzli is a new JPEG encoder that aims to produce visually indistinguishable images at a lower bit-rate than other common JPEG encoders. It optimizes both the JPEG global quantization tables and the DCT coefficient values in each JPEG block using a closed-loop optimizer. Guetzli uses Butteraugli, our perceptual distance metric, as the source of feedback in its optimization process. We reach a 29-45% reduction in data size for a given perceptual distance, according to Butteraugli, in comparison to other compressors we tried. Guetzli's computation is currently extremely slow, which limits its applicability to compressing static content and serving as a proof- of-concept that we can achieve significant reductions in size by combining advanced psychovisual models with lossy compression techniques. View details
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