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| Filename extension | .jxl |
|---|---|
| Internet media type | image/jxl [1] |
| Magic number | FF 0A or 00 00 00 0C 4A 58 4C 20 0D 0A 87 0A [2] |
| Developed by | |
| Type of format | Lossy/lossless bitmap image format |
| Extended from | |
| Standard | ISO/IEC 18181 [4] |
| Open format? | Yes (royalty-free [5] ) |
| Website |
|
JPEG XL is a royalty-free raster-graphics file format that supports both lossy and lossless compression. It is designed to outperform existing raster formats and thus become their universal replacement. [5]
The name consists of JPEG (for the Joint Photographic Experts Group , which is the committee which designed the format), X (part of the name of several JPEG standards since 2000: JPEG XT, JPEG XR, JPEG XS), and L (for long-term). The L was included because the authors' intention is for the format to replace the legacy JPEG and last just as long, too. [6]
The main authors of the specification are Jyrki Alakuijala, Jon Sneyers, and Luca Versari. Other collaborators are Sami Boukortt, Alex Deymo, Moritz Firsching, Thomas Fischbacher, Eugene Kliuchnikov, Robert Obryk, Alexander Rhatushnyak, Zoltan Szabadka, Lode Vandevenne, and Jan Wassenberg.
In August 2017, JTC1 / SC29 / WG1 (JPEG) published a call for proposals for JPEG XL, the next generation image encoding standard. [7] The proposals were submitted by September 2018, leading to a committee draft in July 2019. [8] It was mainly based on a combination of a proposal called PIK, [9] submitted by Google, and a proposal called FUIF [10] — itself based on FLIF — submitted by Cloudinary.
The bitstream was informally frozen on 24 December 2020 with the release of version 0.2 of the libjxl reference software. [11] The file format and core coding system were formally standardized on 13 October 2021 and 30 March 2022 respectively. [4] [12]
The JPEG XL call for proposals [7] talks about the requirement of a next generation image compression standard with substantially better compression efficiency (60% improvement) comparing to JPEG. The standard is expected to outperform the still image compression performance shown by HEIC, AVIF, WebP, and JPEG 2000. It also provides efficient lossless recompression options for images in the traditional/legacy JPEG format.
JPEG XL supports lossy compression and lossless compression of ultra-high-resolution images (up to 1 terapixel), up to 32 bits per component, up to 4099 components (including alpha transparency), animated images, and embedded previews. It has features aimed at web delivery such as advanced progressive decoding [13] and minimal header overhead, as well as features aimed at image editing and digital printing, such as support for multiple layers, CMYK, and spot colors. It is specifically designed to seamlessly handle wide color gamut color spaces with high dynamic range such as Rec. 2100 with the PQ or HLG transfer function.
The main features are: [14] [15] [16]
JPEG XL is based on ideas from Google's PIK format and Cloudinary's FUIF format (which was in turn based on FLIF). [20]
The format is mainly based on two encoding modes:
Any additional/extra channels (e.g. alpha, depth, thermal, spot colors, etc.) are always encoded in the modular mode. It was based on FUIF, combined with elements of lossless PIK, lossless WebP, and new ideas that have been developed during the collaborative phase of the standardization process. [22] Modular mode allows lossy compression with the help of the modified Haar transform called "squeeze" which has progressive properties, quality of the image increases with the amount of data loaded.
One of the ways VarDCT-based images can be loaded more progressively is by saving the DC coefficients in a separate "DC frame" that uses modular squeeze: allowing previews corresponding to 1:16, 1:32 etc subsampled images. A squeeze transform can also be used to encode the alpha channel progressively together with VarDCT-encoded color channels, making both modes work in tandem.
JPEG XL defaults to a visually near-lossless setting that still provides good compression. [17]
These modes can be assisted by separate modeling of specific image features called:
JPEG XL codec can losslessly transcode a widely-supported subset of JPEG files, by directly copying JPEG's DCT block coefficients to 8×8 VarDCT blocks, making smaller file sizes possible due to JPEG XL's superior entropy coding. This process is reversible and it allows for the original JPEG file to be reconstructed bit-for-bit, although constraints limit support for some files. [23]
Prediction is run using a pixel-by-pixel decorrelator without side information, including a parameterized self-correcting weighted ensemble of predictors. Context modeling includes specialized static models and powerful meta-adaptive models that take local error into account, with a signaled tree structure and predictor selection per context. Entropy coding is LZ77-enabled and can use either asymmetric numeral systems or Prefix codes (useful for low-complexity encoders, or reducing the overhead of short streams). [15]
Animated (multi-frame) images do not perform advanced inter-frame prediction, though some rudimentary inter-frame coding tools are available:
Besides Cloudinary, throughout JPEG XL's preliminary implementation in web browsers, various representatives of well-known industry brand names have publicly voiced support for JPEG XL as their preferred choice, including Facebook, [25] [26] Adobe, [27] [28] Intel and the Video Electronics Standards Association, [29] [30] The Guardian, [31] [32] Flickr and SmugMug, [33] Shopify, [34] the Krita Foundation, [35] and Serif Ltd. [36]
Google's stance on JPEG XL is ambiguous, as it has contributed to the format but refrained from shipping an implementation of it in Chromium and Google Chrome. An extension to enable JPEG XL support in Chrome [37] and Firefox [38] became available in January 2024.
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| Initial release | December 27, 2019 [39] |
|---|---|
| Stable release | 0.10.2 / March 8, 2024 |
| Repository | https://github.com/libjxl/libjxl [40]  |
| Written in | C++ |
| Operating system | |
| License | New BSD License (previously Apache License 2.0) |
| Website | jpeg |
libjxlcjxldjxlfjxlbenchmark_xlfile-jxlSupport for JPEG XL in Chromium and Chrome web browsers was introduced for testing April 1, 2021 [66] and removed on December 9, 2022 - with support removed in version 110. [67] [68] The Chrome team cited a lack of interest from the ecosystem, insufficient improvements, and a wish to focus on improving existing formats as reasons for removing JPEG XL support. [66] [69] [67] The decision was met with opposition from the community, with many voicing support for JPEG XL on Chromium's bug tracker. [66] [70] [69] Jon Sneyers, co-author of the JPEG XL spec, has questioned the conclusions drawn by the Chrome team, saying: "I think there has been an unfortunate misinterpretation of the data ... which has unfortunately lead [ sic ] to an incorrect decision." [71] The decision was also criticized by Greg Farough from the Free Software Foundation, who said it demonstrated Google's "disturbing amount of control" over the web and web browsers. [72]
| Common Name | Part | First public release date (First edition) | ISO/IEC Number | Formal Title |
|---|---|---|---|---|
| JPEG XL | Part 1 | 30 March 2022 | ISO/IEC 18181-1 | JPEG XL Image Coding System — Part 1: Core coding system [4] |
| Part 2 | 13 October 2021 | ISO/IEC 18181-2 | JPEG XL Image Coding System — Part 2: File format [12] | |
| Part 3 | 3 October 2022 | ISO/IEC 18181-3 | JPEG XL Image Coding System — Part 3: Conformance testing | |
| Part 4 | 5 August 2022 | ISO/IEC 18181-4 | JPEG XL Image Coding System — Part 4: Reference software |
A codec is a device or computer program that encodes or decodes a data stream or signal. Codec is a portmanteau of coder/decoder.
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder.
JPEG is a commonly used method of lossy compression for digital images, particularly for those images produced by digital photography. The degree of compression can be adjusted, allowing a selectable tradeoff between storage size and image quality. JPEG typically achieves 10:1 compression with little perceptible loss in image quality. Since its introduction in 1992, JPEG has been the most widely used image compression standard in the world, and the most widely used digital image format, with several billion JPEG images produced every day as of 2015.
JPEG Network Graphics is a JPEG-based graphics file format which is closely related to PNG: it uses the PNG file structure as a container format to wrap JPEG-encoded image data.
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Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.
A compression artifact is a noticeable distortion of media caused by the application of lossy compression. Lossy data compression involves discarding some of the media's data so that it becomes small enough to be stored within the desired disk space or transmitted (streamed) within the available bandwidth. If the compressor cannot store enough data in the compressed version, the result is a loss of quality, or introduction of artifacts. The compression algorithm may not be intelligent enough to discriminate between distortions of little subjective importance and those objectionable to the user.
ICER is a wavelet-based image compression file format used by the NASA Mars rovers. ICER has both lossy and lossless compression modes.
libjpeg is a free library with functions for handling the JPEG image data format. It implements a JPEG codec alongside various utilities for handling JPEG data. It is written in C and distributed as free software together with its source code under the terms of a custom permissive (BSD-like) free software license, which demands attribution. The original variant is maintained and published by the Independent JPEG Group (IJG). Meanwhile, there are several forks with additional features.
libavcodec is a free and open-source library of codecs for encoding and decoding video and audio data.
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JPEG XR is an image compression standard for continuous tone photographic images, based on the HD Photo specifications that Microsoft originally developed and patented. It supports both lossy and lossless compression, and is the preferred image format for Ecma-388 Open XML Paper Specification documents.
PGF is a wavelet-based bitmapped image format that employs lossless and lossy data compression. PGF was created to improve upon and replace the JPEG format. It was developed at the same time as JPEG 2000 but with a focus on speed over compression ratio.
CineForm Intermediate is an open source video codec developed for CineForm Inc by David Taylor, David Newman and Brian Schunck. On March 30, 2011, the company was acquired by GoPro which in particular wanted to use the 3D film capabilities of the CineForm 444 Codec for its 3D HERO System.
WebP is a raster graphics file format developed by Google intended as a replacement for JPEG, PNG, and GIF file formats. It supports both lossy and lossless compression, as well as animation and alpha transparency.
A video coding format is a content representation format of digital video content, such as in a data file or bitstream. It typically uses a standardized video compression algorithm, most commonly based on discrete cosine transform (DCT) coding and motion compensation. A specific software, firmware, or hardware implementation capable of compression or decompression in a specific video coding format is called a video codec.
Free Lossless Image Format (FLIF) is a lossless image format claiming to outperform PNG, lossless WebP, lossless BPG and lossless JPEG 2000 in terms of compression ratio on a variety of inputs.
JPEG XT is an image compression standard which specifies backward-compatible extensions of the base JPEG standard.
AV1 Image File Format (AVIF) is an open, royalty-free image file format specification for storing images or image sequences compressed with AV1 in the HEIF container format. It competes with HEIC, which uses the same container format built upon ISOBMFF, but HEVC for compression. Version 1.0.0 of the AVIF specification was finalized in February 2019.
The current contributors have committed to releasing it publicly under a royalty-free and open source license.
