Guetzli: Perceptually Guided JPEG Encoder
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Abstract (arXiv)
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.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 Mar 2017.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 1.
6 papers.
- 2023Random-Access Neural Compression of Material Texturescited by 23
- 2024Multiscale Sliced Wasserstein Distances as Perceptual Color Difference Measurescited by 14
- 2022Measuring Perceptual Color Differences of Smartphone Photographscited by 8
- 2023Learning a Deep Color Difference Metric for Photographic Imagescited by 6
- 2022A Unified Image Preprocessing Framework For Image Compressioncited by 1
- 2021Modeling Image Quantization Tradeoffs for Optimal Compressioncited by 0
- 2024Multiscale Sliced Wasserstein Distances as Perceptual Color Difference Measures14 Jul 2024
- 2023Random-Access Neural Compression of Material Textures26 May 2023
- 2023Learning a Deep Color Difference Metric for Photographic Images27 Mar 2023
- 2022A Unified Image Preprocessing Framework For Image Compression15 Aug 2022
- 2022Measuring Perceptual Color Differences of Smartphone Photographs26 May 2022
- 2021Modeling Image Quantization Tradeoffs for Optimal Compression14 Dec 2021