Fact-checked by Grok 2 weeks ago

Joint Photographic Experts Group

The Joint Photographic Experts Group (JPEG) is an international joint committee established in November 1986 by the (ISO), the (IEC), and the then-Consultative Committee for International Telegraph and Telephone (CCITT, now the or ITU) to develop and maintain standardized methods for the digital compression and coding of continuous-tone still images. Operating as Working Group 1 (WG 1) within ISO/IEC Joint Technical Committee 1, Subcommittee 29 (JTC 1/SC 29) on Coding of Audio, Picture, Multimedia and Hypermedia Information, the committee focuses on creating efficient coding techniques for digital images to support applications in , , and across , , and systems. The JPEG committee's foundational work culminated in the original JPEG standard, formally known as ISO/IEC 10918 (also ITU-T Recommendation T.81), which was approved and first published in 1992 after a development process spanning 1986 to 1993. This landmark standard introduced lossy compression based on the discrete cosine transform (DCT), enabling significant reductions in file sizes for photographic images while maintaining acceptable visual quality, thereby facilitating the widespread adoption of digital photography, web imaging, and consumer electronics. Over the decades, JPEG has produced a family of extensions and successor standards, including JPEG 2000 (ISO/IEC 15444 series, published starting 2000) for higher-quality wavelet-based compression, JPEG XR (ISO/IEC 29199, 2009) for high-dynamic-range imaging, and more recent developments like JPEG XT (ISO/IEC 18477 series, 2015) for high dynamic range, JPEG Pleno (ISO/IEC 21794 series, 2019) for light fields and holography, JPEG XL (ISO/IEC 18181 series, 2022) for modern lossless and lossy coding with enhanced features such as animation support, JPEG AI (ISO/IEC 6048 series, 2025) for learning-based image coding, and JPEG Trust (ISO/IEC 21617 series, 2025) for establishing trust and authenticity in digital media. In addition to its technical contributions, the JPEG committee meets four times annually to advance ongoing projects, such as explorations into emerging applications like DNA-based media storage (JPEG DNA, under development as of 2025), ensuring its standards remain relevant to evolving technologies in , visual data explosion, and sustainable digital ecosystems. The group's collaborative structure, open to experts from national standards bodies and liaison organizations, has earned it recognition, including a 2019 Technology and Engineering Emmy Award from the National Academy of Television Arts and Sciences for its impact on .

Background and Purpose

Establishment

The Joint Photographic Experts Group (JPEG) was formally established in November 1986 during its inaugural meeting in , , as a collaborative effort between the for Standardization's Technical Committee 97, Subcommittee 2, Working Group 8 (ISO TC 97/SC 2/WG 8) and the International Telegraph and Telephone Consultative Committee's VIII (CCITT SGVIII), the predecessor to 16. This joint committee was created to develop international standards for compressing continuous-tone still images, responding to the increasing demand for efficient handling in emerging applications. The founding group consisted of approximately 15 individual experts with formal ties to the parent organizations, including key figures such as Hiroshi Yasuda from (NTT) in , who served as convener of ISO TC 97/SC 2/WG 8, and Manfred Worlitzer, special for CCITT SGVIII. These members represented a mix of expertise from standards bodies and entities, with initial discussions on the group's formation dating back to March 1986. Over time, the committee expanded to include broader participation from industry leaders such as and , alongside academic contributors, to address the technical challenges of image coding. This establishment occurred amid the rapid expansion of in the 1980s, fueled by the proliferation of personal computers like the IBM PC and Apple Macintosh, which introduced graphical user interfaces and capabilities. The concurrent availability of affordable scanners and digital cameras generated large volumes of image data—often requiring millions of bytes per high-resolution color image—that strained existing storage and transmission infrastructures. Without standardized , across devices and networks remained limited, prompting the need for a versatile solution to reduce image sizes by factors of 10 to 50 while preserving visual quality, as demonstrated by prior successes like the CCITT Group 3 facsimile standard for bilevel images. JPEG later evolved into Working Group 1 (WG 1) under Subcommittee 29 (SC 29) of ISO/IEC Joint Technical Committee 1 (JTC 1), maintaining its focus on still image coding standards.

Objectives

The Joint Photographic Experts Group (JPEG) was established with the primary aim of developing a single, flexible standard for the compression of continuous-tone still images, designed to support a broad spectrum of applications including , , teleconferencing, transmission, , communications, and scientific visualization. This standard sought to provide an efficient, interoperable framework for encoding and decoding images, enabling effective storage and transmission while accommodating diverse user needs across industries. A key emphasis of the JPEG objectives was on lossy compression techniques to achieve high compression ratios—often 10:1 or greater—while preserving acceptable visual quality by minimizing perceptible distortions to levels below human visibility thresholds. To address scenarios requiring data integrity, the standard also included provisions for lossless compression modes, which ensure exact reproduction of the original image without any information loss, albeit with lower compression efficiency compared to lossy methods. The scope of JPEG's work was deliberately limited to still images, excluding video or motion content, which was deferred to the related (MPEG) for handling. It encompassed both (single-component) and color (multi-component) images, supporting sample precisions of 8 bits and 12 bits per component to facilitate compatibility with various systems. This focused delineation allowed JPEG to prioritize universal applicability for static visual data without overextending into dynamic media formats.

History

Early Formation

The Joint Photographic Experts Group (JPEG) held its inaugural meeting from November 11 to 13, 1986, in Parsippany, New Jersey, USA, where approximately 20 experts gathered to initiate the development of a standardized compression method for continuous-tone still images. At this session, Graham Hudson was elected as the committee chair, and participants presented 14 preliminary coding techniques, setting the stage for a structured evaluation process. The meeting emphasized the need for a versatile standard supporting both lossless and lossy compression, with applications in digital photography, facsimile, and multimedia systems. Subsequent early meetings focused on refining requirements and evaluating proposals. In March 1987, at a session in , , the committee officially registered 12 coding schemes from various contributors, including predictive coding methods and transform-based approaches. A key decision emerged in June 1987 during the first formal selection meeting, where subjective quality assessments narrowed the field to three finalists, prompting the formation of ad hoc groups to further evaluate and hybridize the algorithms. These groups prioritized a hybrid approach combining (DCT) for analysis with predictive elements for , favoring it over pure due to its superior performance in balancing compression ratios and image fidelity. The committee faced significant challenges in reconciling divergent proposals, particularly the Adaptive Discrete Cosine Transform (ADCT) submitted by , which advocated an 8x8 block-based DCT method, against competing schemes like and from other members. Disagreements centered on trade-offs between , implications, and perceptual quality, requiring iterative testing and consensus-building across international participants. By the second selection meeting in January 1988 in , , the ADCT-based hybrid was selected as the core method following rigorous objective and subjective evaluations, establishing a timeline for a proof-of-concept implementation by the end of 1988 to validate its viability for the draft standard. This phase solidified JPEG's foundational direction toward a flexible, widely applicable framework.

Development of Initial Standards

Following the selection of the (DCT) as the core method in 1988, the (JPEG) focused on rigorous validation and refinement of the proposed standard from 1989 to 1991. This phase involved extensive testing of the validation model, which included software simulations to assess encoding and decoding performance across various image types and ratios. Hardware prototypes were also developed and evaluated to ensure practical implementability, with subjective assessments conducted to verify that the maintained acceptable visual fidelity for photographic images. These efforts confirmed the robustness of the DCT-based approach while identifying necessary adjustments for and efficiency. In 1991, JPEG held key meetings to resolve remaining design choices, including the selection of profiles and operational modes for the standard. The baseline profile was prioritized for broad adoption, emphasizing sequential DCT-based coding as the primary mode, alongside and hierarchical modes to support applications requiring layered or multi-resolution decoding. The lossless mode was incorporated to handle scenarios where no quality loss was permissible. These modes were integrated into the draft to provide flexibility without compromising framework. By November 1991, the Draft International Standard () for Part 1 was balloted, incorporating no major technical changes from the final working draft. The development culminated in the approval of the baseline JPEG standard on September 18, 1992, as Recommendation T.81, which defined the core framework for continuous-tone still images. This was simultaneously prepared as ISO/IEC 10918-1, formally published in 1994 after identical adoption by ISO/IEC JTC 1/SC 29. The standard's Part 1 outlined the encoding and decoding processes, while Part 2 specified compliance testing procedures to ensure consistent implementation across systems. These publications marked the completion of the initial JPEG effort, building on exploratory proposals from 1986-1988 that had shaped the group's objectives.

Post-2000 Advancements

Following the establishment of the baseline standard in 1992, the Joint Photographic Experts Group initiated efforts to address limitations in compression efficiency and functionality for emerging applications. In March 1997, the committee issued a call for proposals to develop a successor standard, leading to the launch of the project under ISO/IEC JTC 1/SC 29/WG 1. This effort culminated in the publication of ISO/IEC 15444-1 in December 2000, which introduced wavelet-based compression techniques offering superior lossless performance compared to the methods of the original . During the 2000s, the committee expanded its portfolio to support advanced imaging needs, particularly for (HDR) content. In 2009, was advanced to final draft status, with full publication as ISO/IEC 29199-2 in 2010; this format was designed to handle HDR images efficiently while maintaining compatibility with existing workflows. Building on this, JPEG XT emerged in the mid-2010s as ISO/IEC 18477-1:2015, providing with legacy JPEG decoders through a layered structure that embeds tone-mapped low images within HDR codestreams. In the , the committee explored next-generation formats amid growing and demands. A call for proposals for was issued in 2018, aiming for a versatile to supersede multiple formats; the resulting ISO/IEC 18181-1 (first edition 2022; second edition 2024) saw limited adoption due to competing alternatives, though expanded with the PDF Association's announcement in November 2025 to incorporate into the PDF specification. Concurrently, advancements integrated JPEG with web-oriented standards, such as enhanced for JFIF file interchange and metadata embedding in extensions like JPEG 2000's JP2 container, facilitating broader interoperability in and online distribution.

Organization and Governance

Structure within ISO/IEC

The Joint Photographic Experts Group (JPEG) is designated as ISO/IEC JTC 1/SC 29/WG 1, having been reorganized into this structure in 1991 after its original establishment as a joint ISO/CCITT (now ) group that initially functioned as a under JTC 1/SC 2/WG 8, operating under Joint Technical Committee 1 (JTC 1) for within the (ISO) and the (IEC). Leadership roles within the include a convenor responsible for overall coordination, vice-convenors providing support in key functions, and chairs for subgroups focused on specialized areas such as , systems, and requirements, all appointed in accordance with ISO/IEC procedures to guide technical deliberations. The committee maintains a regular meeting cadence of quarterly plenary sessions, with venues rotating globally to promote international involvement, complemented by groups formed for targeted tasks like standard refinements or exploratory studies between plenaries.

Collaboration and Membership

The Joint Photographic Experts Group (JPEG), formally known as ISO/IEC JTC 1/SC 29/WG 1 in collaboration with Study Group 16, maintains an open membership model accessible to national standards bodies, organizations, and individual experts. Participation is facilitated through national member bodies of ISO and IEC, such as the (ANSI) in the United States and the Japanese Industrial Standards Committee (JISC) in Japan, which nominate experts to working group meetings. Additionally, organizations with Category C liaison status, including major industry players like Adobe Systems, , and , contribute actively alongside academic institutions and other entities, enabling diverse input from hundreds of experts worldwide. Key collaborations extend beyond its foundational partnership with , where joint recommendations such as T.81 for the original standard are developed to ensure alignment in multimedia coding. The committee holds formal liaisons with the (IETF) to address network transport protocols for JPEG technologies, exemplified by recent coordination on JPEG AI for efficient data handling in internet applications. Similarly, a Category C liaison with the (W3C) supports integration of JPEG standards into web technologies, promoting interoperability for image formats in online environments. Decision-making within the JPEG committee follows ISO's consensus-based process, where proposals are refined through discussion among participating experts and national bodies to achieve broad agreement, avoiding formal votes unless necessary to resolve impasses. Contributions from industry leaders like , focusing on mobile imaging, and ensure balanced perspectives, with final approvals requiring at least two-thirds support from participating members if is not fully attained. This approach fosters high-impact standards through inclusive, iterative refinement.

Technical Principles

Core Compression Techniques

The core compression techniques in JPEG standards revolve around three primary stages: the (DCT) for spatial-to-frequency domain conversion, quantization to discard less perceptible information, and entropy encoding for lossless data compaction. These methods, designed to achieve high compression ratios while maintaining visual quality, form the backbone of lossy in the ISO/IEC 10918 series. The DCT operates on blocks of samples, transforming them into a set of 64 DCT coefficients that represent spatial , with low frequencies concentrated in the upper-left corner. The forward DCT is mathematically defined as: F_{uv} = \frac{1}{4} C_u C_v \sum_{x=0}^{7} \sum_{y=0}^{7} f_{xy} \cos\left[\frac{(2x+1)u\pi}{16}\right] \cos\left[\frac{(2y+1)v\pi}{16}\right] where f_{xy} is the input sample value (level-shifted by 128 for 8-bit data), F_{uv} is the DCT coefficient at frequency indices u and v, and the scaling factors are C_0 = \frac{1}{\sqrt{2}} and C_{u,v} = 1 for u,v \geq 1. This formulation, derived from the type-II DCT, enables efficient energy compaction for natural . The DCT reconstructs the spatial block via a similar over frequencies: f_{xy} = \frac{1}{4} \sum_{u=0}^{7} \sum_{v=0}^{7} C_u C_v F_{uv} \cos\left[\frac{(2x+1)u\pi}{16}\right] \cos\left[\frac{(2y+1)v\pi}{16}\right] with level-shifting applied post-reconstruction to recover the original range. Quantization follows the DCT, dividing each coefficient by a corresponding value from an 8x8 quantization table and rounding to the nearest integer, which introduces irreversibility by attenuating high-frequency details: F^q_{uv} = \text{round}\left( \frac{F_{uv}}{Q_{uv}} \right) where Q_{uv} is the table entry. The standard provides example tables in Annex K, optimized based on human visual sensitivity; for luminance, Table K.1 uses values that increase toward higher frequencies to preserve low-frequency structure. A representative excerpt of this table (full 8x8 matrix) is:
1611101624405161
1212141926586055
1413162440576956
1417222951878062
182237566810910377
243555648110411392
49647887103121120101
7292959811210010399
Dequantization during decoding multiplies the quantized coefficients by Q_{uv} before the inverse DCT. Entropy encoding applies to the quantized s after reordering them via a zigzag scan, which traverses the 8x8 block diagonally from low to high frequencies (starting at coefficient F^q_{00} and ending at F^q_{77}) to group nonzero values efficiently and exploit the sparsity of high frequencies in typical images. For coefficients, differential encoding computes the difference from the prior block's , categorized by magnitude (0-11 bits) and Huffman-coded using derived tables; additional bits encode the exact value and sign. coefficients are encoded as run-length pairs (zeros followed by a nonzero value), with the run length (0-15) and category (0-10) Huffman-coded, followed by bits; end-of-block (EOB) and zero-run-length codes handle trailing zeros. These variable-length codes, based on statistically optimized (e.g., Tables K.3-K.6), achieve further without loss.

Color and Data Handling

JPEG employs a conversion from the input RGB model to to separate (Y) from (Cb and Cr) components, leveraging the human visual system's reduced sensitivity to color details compared to . This transformation is defined using coefficients from Recommendation BT.601, with the following equations for 8-bit values ranging from 0 to 255: \begin{align} Y &= 0.299R + 0.587G + 0.114B, \\ Cb &= -0.1687R - 0.3313G + 0.500B + 128, \\ Cr &= 0.500R - 0.4187G - 0.0813B + 128. \end{align} These equations ensure Y represents perceived brightness, while and capture blue and red differences, respectively, scaled to the range 0-255. To further optimize storage, JPEG applies after conversion, reducing the resolution of and relative to Y since color information can be approximated with fewer samples without noticeable quality loss. Common ratios include , where is subsampled by a factor of 2 in both horizontal and vertical directions, halving the data for each channel compared to full sampling. This technique, specified in the baseline standard, typically results in one sample per 4:1 block of samples, enabling ratios that preserve visual fidelity. Image data in JPEG is organized into scans, which can be either interleaved—where samples from all color components are mixed within the same for efficient —or non-interleaved, separating components into distinct scans for targeted decoding or . The file structure uses marker segments to delineate sections, such as the Start of Image (SOI) marker (0xFFD8) at the beginning and End of Image (EOI) marker (0xFFD9) at the conclusion, with additional segments for headers like the Start of Frame (SOF) that define image parameters and such as and . These markers facilitate modular and of application-specific data without altering the core compressed stream. For flexible decoding, JPEG supports and hierarchical modes that enable multi-resolution access to image data. In mode, the encoded data is organized into scans that build image quality incrementally, allowing low-resolution previews before full refinement, achieved by spectral selection or successive approximation of coefficients. Hierarchical mode extends this by structuring the image as a pyramid of frames at decreasing resolutions, where each higher level refines the previous one, supporting scalable decoding from coarse overviews to fine details without reprocessing the entire file. These modes are particularly useful for bandwidth-constrained environments, as they permit partial reconstruction based on available data.

Standards Portfolio

ISO/IEC 10918 Series (JPEG Baseline)

The ISO/IEC 10918 series, commonly known as the JPEG standard, defines the foundational framework for lossy and lossless compression of continuous-tone still images using discrete cosine transform (DCT)-based techniques. Published in 1994, this series establishes requirements for encoding and decoding processes that balance compression efficiency with image quality preservation for photographic content. It supports various operational modes and profiles tailored to different applications, from basic grayscale images to color photographs, ensuring interoperability across devices and software. Part 1 of the series (ISO/IEC 10918-1:1994) outlines the core requirements and guidelines for digital compression and coding, focusing on a lossy DCT-based method that transforms spatial image data into frequency coefficients for efficient quantization and entropy coding. This part specifies sequential encoding processes, including baseline and extended sequential profiles; the baseline profile supports 8 bits per sample for grayscale or color images (typically using YCbCr color space with three components), employs Huffman coding for entropy, and is designed for broad compatibility in resource-constrained environments. The extended sequential profile extends this to 12 bits per sample and includes an option for arithmetic coding, enabling higher precision for applications requiring finer gradations, such as medical imaging. It also supports progressive encoding, which refines image quality in multiple scans for faster partial rendering, and lossless mode, which uses predictive differential coding to achieve reversible compression with ratios around 2:1 for typical images. These profiles ensure that compressed data can be decoded to reconstruct images with acceptable visual fidelity, typically achieving 10:1 to 20:1 compression ratios for color photographs without severe artifacts. Parts 2 through 5, developed between 1995 and 2013, expand on Part 1 by addressing implementation , additional features, and practical deployment. Part 2 (ISO/IEC 10918-2:1995) provides testing procedures to validate that encoders and decoders adhere to the specifications in Part 1, including tests for syntax, decoding accuracy, and error handling across supported profiles. Part 3 (ISO/IEC 10918-3:1997) introduces extensions such as hierarchical encoding for scalable resolution and spatially variable quantization for adaptive . Part 4 (ISO/IEC 10918-4:1999) establishes registration authorities for standardizing new profiles, tags, and color spaces, ensuring extensibility while maintaining uniqueness in implementations like (Still Picture Interchange File Format). Part 5 (ISO/IEC 10918-5:2013, originally proposed in 1992) defines the (JFIF), a minimal that embeds Part 1 s with for and thumbnails, facilitating simple file exchange without wrappers. Amendments to the series have enhanced portability and reliability over time. The JFIF specification, first detailed in and formally integrated as Part 5, serves as a robust for baseline JPEG data, supporting 1 or 3 color channels at 8 bits each and enabling widespread adoption in formats like .jpg files. Later updates, including amendments to Parts 3 and 4 in 1999 and beyond, introduced provisions for registering new compression variants and improved error resilience through better marker definitions, allowing streams to recover from transmission errors in networked environments. These evolutions have solidified the series' role as a versatile for , influencing billions of daily image transmissions.

ISO/IEC 15444 Series (JPEG 2000)

The ISO/IEC 15444 series, commonly referred to as , constitutes a comprehensive family of international standards for still image coding, introduced to address limitations in earlier compression methods by leveraging transforms for enhanced efficiency and flexibility. Published under the auspices of the Joint Photographic Experts Group () within ISO/IEC JTC 1/SC 29, the series began with Part 1 in December 2000 and has expanded through subsequent parts up to at least Part 17 by 2023, though the core extensions span Parts 2 through 15 from 2001 to 2020. This suite supports a wide range of applications, from to , by enabling scalable, progressive, and resilient image representation without relying on block-based discrete cosine transforms used in prior standards. Part 1 of the series (ISO/IEC 15444-1:2000, with subsequent amendments and editions up to 2024) establishes the foundational core coding system for bi-level, , palettized, or continuous-tone color images. It utilizes the (DWT) as the primary decomposition mechanism, employing 9/7-tap biorthogonal filters for irreversible ( to achieve high visual quality at low bit rates, while a reversible 5/3 wavelet transform enables bit-preserving lossless coding within the same framework. The standard specifies the codestream syntax, including via embedded block coding with optimized truncation (EBCOT), and includes an amendment defining the JP2 for wrapping codestreams with metadata such as information and markers. This core enables features like quality and resolution , allowing decoders to extract lower-fidelity versions from a single codestream. Parts 2 through 15 extend the core capabilities, introducing specialized functionalities for diverse use cases while maintaining compatibility with Part 1. For instance, Part 2 (2004, amended through 2023) adds advanced extensions to the coding engine, including arbitrary transforms, multiple component transformations for , and support for non-photometric color spaces. Part 10 (2008, amended 2011 and 2015) provides volumetric extensions for three-dimensional data, such as medical scans, by incorporating a Z-dimension into the decomposition and precinct structure for efficient tile-based coding. Part 11 (2007, amended 2013) focuses on wireless applications, defining error protection syntaxes like residual error management and to enhance robustness during transmission over error-prone channels. Other notable extensions include Part 6 (2003) for compound documents via the JPM format, Part 9 (2005, with amendments) for client-server interactions via JPIP, and Part 15 (2019) for high-throughput coding with an alternate block coder that boosts encoding speed by up to 10 times at minimal efficiency cost. The codestream syntax across parts supports embedded for , such as XML boxes in JP2/JPX formats. Compared to baseline , the series delivers superior ratios for high-resolution , often achieving 20-30% better efficiency in visually lossless scenarios due to the wavelet-based multi-resolution that captures spatial redundancies more effectively. It introduces region-of-interest (ROI) , where specific areas receive higher bit allocation for prioritized quality, useful in applications like or diagnostics. Additionally, its error resilience—through packetization, error detection markers, and graceful degradation—makes it ideal for streaming over networks, reducing artifacts from bit errors that plague DCT-based methods. These attributes have cemented 's role in professional workflows, despite computational demands.

Additional Extensions

Beyond the core ISO/IEC 10918 and 15444 series, the Joint Photographic Experts Group has developed several supplementary standards that address specific needs in , such as lossless coding, () support, and motion sequences. These extensions expand the applicability of JPEG technologies to niche domains like , archival preservation, and professional photography without altering the foundational frameworks.

JPEG LS (ISO/IEC 14495)

JPEG LS, standardized as ISO/IEC 14495-1 in 1999, provides a lossless and near-lossless method for continuous-tone still images using combined with modeling and . The core coding system employs a simple linear predictor to estimate pixel values based on neighboring samples, followed by -based adaptive to achieve ratios typically 2:1 for lossless mode on photographic images, making it suitable for applications requiring exact such as diagnostics and archiving. Unlike transform-based methods, JPEG LS avoids floating-point operations, enabling low-complexity implementation on resource-constrained devices, and supports bit depths up to 16 bits per component. This standard was designed to fill the gap between highly efficient but lossy JPEG baseline and bulky uncompressed formats, with near-lossless modes allowing controlled error introduction for slight efficiency gains. Its adoption in formats like underscores its reliability in clinical environments where is paramount.

JPEG XR (ISO/IEC 29199)

Originally developed by as HD Photo and standardized as ISO/IEC 29199-2 in 2009 (with updates through 2020), JPEG XR employs a block-based lapped for both lossy and of high-quality still images, particularly those with content. The format divides images into 4x4 or 8x8 blocks, applies an overlapping transform to reduce boundary artifacts, and uses adaptive Huffman or for efficiency, achieving compression performance comparable to while requiring fewer computational resources—often 50% less memory and processing time for decoding. It supports pixel formats from 1 to 16 bits per channel, including floating-point for , transparency via alpha channels, and tiling for large images, making it ideal for professional screens, , and systems. integrated JPEG XR into Windows Imaging Component and Office applications, promoting its use in scenarios demanding high fidelity and progressive loading. Despite limited widespread adoption due to patent concerns resolved in 2017, it remains a robust option for workflows.

JPEG XT (ISO/IEC 18477)

Published in 2015 with core specifications updated in ISO/IEC 18477-1:2020, JPEG XT extends the baseline (ISO/IEC 10918) format to support and wider color gamuts while maintaining full , allowing legacy decoders to extract a standard (SDR) version from the . The extension uses to represent the difference between an SDR tone-mapped and the original data, encoded with additional quantization and transform steps, enabling dynamic ranges up to 14 stops and bit depths beyond 8 bits per channel. This approach preserves the simplicity of pipelines for SDR fallback, with typical file size increases of 20-50% for enhancement depending on scene complexity. Targeted at consumer and professional , JPEG XT facilitates the transition to displays without disrupting existing ecosystems, and its profile for integer arithmetic ensures efficient processing. The standard's multi-part structure includes guidelines for handling and conformance testing, promoting interoperability in and .

Motion JPEG 2000 (ISO/IEC 15444-3)

As part of the family, ISO/IEC 15444-3, first issued in 2002 and revised in 2007, defines (MJ2) for compressing and storing sequences of JPEG 2000-coded frames, suitable for video-like applications such as archival film and scientific visualization. The format wraps individual JPEG 2000 codestreams in an (compatible with MP4), including metadata for timing, audio tracks, and frame rates, without inter-frame prediction to maintain independent frame decoding and scalability. This enables random access and quality scalability per frame, with compression efficiencies similar to single-image JPEG 2000 but extended to motion sequences up to . Primarily used in preservation and medical video, MJ2 supports lossless modes and has been integrated into tools like FFmpeg for professional workflows. Its design prioritizes long-term stability over real-time performance, distinguishing it from full video codecs.

JPEG XL (ISO/IEC 18181)

JPEG XL, standardized as ISO/IEC 18181-1 in 2022, provides a modern image coding format supporting both lossless and lossy compression with advanced features for efficiency and versatility. It uses a combination of modular compression tools, including a squeeze transform for decorrelation and entropy coding with ANS (Asymmetric Numeral Systems), achieving better compression than JPEG for lossy images and supporting lossless modes comparable to PNG or FLAC for images. The standard supports wide color gamuts, HDR, transparency, animation (up to 60 fps), and progressive decoding, with bit depths from 1 to 32 bits per channel. Designed for web, storage, and archival use, JPEG XL offers backward compatibility modes for JPEG and PNG, enabling gradual adoption. Its development addressed needs for faster encoding/decoding and smaller files in the era of high-resolution imaging, with implementations available in libraries like libjxl as of 2025.

Ongoing Developments

JPEG AI

JPEG AI, designated as ISO/IEC 6048, represents the Joint Photographic Experts Group's first for learning-based image coding, leveraging neural networks to advance efficiency. The initiative began in 2019 with a call for evidence to explore -driven technologies surpassing traditional methods, evolving into an official new work item in February 2021. It progressed to Draft (DIS) status during the 103rd meeting in April 2024 and achieved full approval at the 106th meeting in January 2025. At its core, JPEG AI utilizes end-to-end architectures for , enabling a unified that serves both and requirements. This includes encoding side information within the compressed domain to support AI tasks such as and super-resolution, allowing machines to perform analysis without complete decompression and thereby minimizing latency and resource use. The supports 8- and 10-bit color depths, progressive decoding, and royalty-free baseline implementations, making it adaptable for diverse hardware and software environments. The standard's objectives center on addressing the escalating demands of visual data in AI ecosystems by delivering substantial bandwidth savings—approximately 30% improved compression over state-of-the-art methods at matching subjective quality levels—for applications like , systems, and media distribution. By prioritizing with legacy formats through compatible file structures and codestreams, facilitates seamless integration into existing workflows, promoting widespread adoption without disrupting established infrastructures.

JPEG Trust

JPEG Trust is an developed by the Joint Photographic Experts Group () to establish and verify trust in , particularly images and videos, by providing mechanisms for , , and assurance. Initiated in 2022 in response to rising concerns over and AI-generated content, the project addresses the need for interoperable tools to track media origins and detect alterations. The core foundation, specified in ISO/IEC 21617-1, advanced to Draft () status in January 2024 following the 102nd JPEG meeting and was published as an in January 2025. This framework builds on existing standards without altering compression techniques, focusing instead on annotations embedded securely within media files. At its core, JPEG Trust employs cryptographic signing to authenticate media creators and modifications, ensuring that any changes to the content or its are verifiable. tracking records the lifecycle of the media, from capture to distribution, using structured that documents origins, edits, and attributions in a tamper-evident manner. Tamper detection mechanisms, akin to blockchain-like chains of custody, allow users to validate the integrity of the media by checking cryptographic hashes and signatures against potential alterations. These components form a modular that supports considerations and secure handling, enabling stakeholders to assess trustworthiness without relying on centralized authorities. The standard's applications are particularly vital in combating deepfakes and -generated media, where it facilitates origin verification to distinguish authentic content from synthetic or manipulated versions. By integrating with camera pipelines and existing JPEG formats such as JPEG and , JPEG Trust enables devices to embed trust at the point of capture, supporting end-to-end verification in journalistic, legal, and contexts. This integration enhances user confidence in visual evidence, especially amid advancements in generative technologies.

Emerging Projects

The JPEG Systems initiative, formalized as the ISO/IEC 19566 series and under development since 2018, establishes a comprehensive framework to promote among all standards. This multi-part addresses system-level aspects such as file formats, codestream packaging, embedding, and application programming interfaces (), enabling consistent handling of data across diverse platforms and use cases. By providing foundational elements like the JPEG universal metadata box format (JUMBF) in Part 5, it supports extensible for enhanced functionality, including rights management and quality metrics, without altering core algorithms. Ongoing work includes application-specific extensions, such as Part 6 for 360-degree imaging and Part 8 for lightweight "snackable" content delivery, ensuring 's adaptability to modern streaming and immersive applications. JPEG Pleno, specified in the ISO/IEC 21794 series and progressing since around , extends the JPEG portfolio to advanced plenoptic modalities beyond traditional 2D photography. It offers a unified coding framework for light fields, , point clouds, and texture-plus-depth representations, derived from the plenoptic function to capture richer scene information for immersive experiences. Key components include Part 2 for light field coding, which defines syntax for multi-view arrays and associated to enable efficient and rendering, and Part 5 for holographic , supporting both and continuous-tone holograms with decompression processes optimized for display. The standard emphasizes modularity, allowing integration of various coding tools while maintaining with existing infrastructure. Current efforts focus on (Part 3), reference software (Part 4), and quality methodologies (Part 7), with active development on learning-based approaches for to meet demands in and . Looking ahead, emerging JPEG projects draw influences from recent standards like (ISO/IEC 18181, published in 2022), which, despite challenges in widespread adoption, continues to inform explorations in high-efficiency coding and lossless . Ongoing amendments to , such as those defining profiles and levels, highlight potential for further enhancements in responsive image delivery. JPEG XE is an emerging exploration activity focused on event-based vision, a new image modality from event-based visual sensors that capture changes in scenes asynchronously. Initiated in , it aims to develop an for efficient representation and coding of event data to enable in sensing, processing, and transmission. At the 108th JPEG meeting in September 2025, JPEG XE advanced to Committee Draft stage, with ongoing calls for proposals to evaluate technologies for this domain.

Applications and Impact

Common Implementations

JPEG has become the for image storage in , with cameras from major manufacturers like and Nikon routinely producing .jpg files using the baseline JPEG format to balance file size and quality. These files integrate EXIF , which embeds details such as camera model, exposure settings, and timestamp directly into the JPEG structure, facilitating post-processing and organization. This integration, enabled by the ISO/IEC 10918 standard, ensures compatibility across devices and software without requiring separate metadata files. On the web and in mobile applications, progressive JPEG—a mode defined in the standard—receives broad support from modern browsers, including , , and , allowing images to load in multiple passes for a smoother viewing experience on slower connections. Platforms like further leverage JPEG compression during image uploads, automatically reducing file sizes to manage and while recommending a minimum width of 1080 pixels to maintain visual fidelity. In professional sectors, JPEG LS offers for , where it is specified in the standard to preserve diagnostic integrity without data loss, making it ideal for applications like radiology scans. Similarly, is widely adopted for , with organizations such as and the using it to compress high-resolution multispectral data from missions like , achieving efficient storage while supporting both lossy and lossless modes.

Technological Influence

The JPEG standard has maintained significant market dominance in digital imaging, with approximately 73.6% of websites utilizing the format for image delivery as of November 2025. This prevalence stems from JPEG's efficient balance of and quality, which has been instrumental in enabling the explosive growth of and online photo sharing by making high-quality image transmission feasible over limited connections. For instance, platforms like and rely heavily on JPEG for user-uploaded photos, facilitating billions of daily shares without overwhelming network infrastructure. JPEG's widespread adoption has spurred innovations in subsequent image formats, particularly by highlighting limitations that developers sought to overcome. The format's discrete cosine transform-based compression, while effective, often introduced visible artifacts that prompted the creation of alternatives like WebP and AVIF, which build on similar principles but incorporate advanced techniques such as VP8 keyframe encoding in WebP to achieve 25-34% smaller file sizes at comparable quality. Similarly, AVIF leverages the AV1 codec to deliver superior compression efficiency—up to 50% file size reduction over JPEG—while addressing JPEG's blocky distortions through more sophisticated intra-frame prediction and better handling of high-dynamic-range content. These advancements in algorithms, directly motivated by JPEG's shortcomings, have led to broader improvements in perceptual quality metrics and support for features like transparency and animation in modern web standards. Despite its influence, JPEG faces criticisms for visible compression artifacts, especially in low-quality settings where blockiness, ringing around edges, and color banding become prominent due to its lossy nature. These distortions, arising from quantization errors in the process, degrade image fidelity in scenarios requiring high detail, such as professional or . This has driven a push toward alternatives for high-fidelity applications, with formats like gaining traction for their ability to maintain clarity at lower bitrates, reflecting an ongoing evolution in response to JPEG's inherent trade-offs.

References

  1. [1]
    [PDF] iso/iec 10918-1 (1986-1993) - ITU
    The JPEG Recommendation | International Standard (ITU-T T.81 | ISO/IEC 10918-1 [1]), first published in. 1992, is still the most popular and most used picture- ...
  2. [2]
    About JPEG
    The Joint Photographic Experts Group (JPEG) committee (ISO/IEC JTC 1/SC 29/WG 1) has a long tradition in the creation of still image coding standards.
  3. [3]
    ISO/IEC JTC 1/SC 29 - Coding of audio, picture, multimedia and ...
    Creation date: 1991. Scope. Standardization in the field of. Efficient coding of digital representations of images, audio and moving pictures, including.
  4. [4]
    ISO/IEC 10918-1:1994 - Information technology
    2–5 day deliveryGeneral information. Status. : Published. Publication date. : 1994-02. Stage. : Close of review [90.60]. Edition. : 1. Number of pages. : 182. Technical ...
  5. [5]
    [PDF] The First Joint ITU|ISO/IEC Still Image Compression Standards
    Jul 23, 2005 · o ISO and ITU (then known as CCITT) joined forces in 1986 to create the Joint Photographic Experts Group (JPEG) committee to establish a ...
  6. [6]
    [PDF] ISO/IEC JTC 1/SC 29 N 22568 - IETF
    Feb 14, 2025 · This standard provides a framework for image compression to support rapidly growing visual data demands, enabling more. Page 5. ISO/IEC JTC 1/ ...
  7. [7]
    ISO, IEC and ITU's committee for JPEG receives Emmy Award
    Oct 24, 2019 · The experts behind the technology, collectively known as the ISO/IEC and ITU Joint Photographic Experts Group of ISO/IEC JTC 1's subcommittee SC ...
  8. [8]
    [PDF] The JPEG Still Picture Compression Standard
    To meet the differing needs of many applications, the JPEG standard includes two basic compression methods, each with various modes of operation. A DCT-based ...Missing: context personal
  9. [9]
    [PDF] itu-t81.pdf
    Joint Photographic Experts Group; JPEG: The informal name of the committee which created this. Specification. The “joint” comes from the CCITT and ISO/IEC ...
  10. [10]
    None
    ### Summary of JPEG Standard Goals and Objectives
  11. [11]
    [PDF] when and how the Royalty-Free JPEG patent policy got lost
    “CCITT and ISO/IEC have long established cooperative relationships. In. June 1989, an ad hoc group of CCITT and ISO/IEC JTC 1 leaders met to review the then ...
  12. [12]
    [PDF] JPEG25 still strong_IEEE_Final - ResearchGate
    At the first JPEG meeting. (Parsippany, Nov. 1986), 14 different techniques were presented, but only 12 proposals were officially registered in Darmstadt in ...
  13. [13]
    [PDF] The JPEG Still Picture Compression Standard
    After its selection of a DCT-based method in 1988,. JPEG discovered that a DCT-based lossless mode was difficult to define as a practical standard against ...
  14. [14]
    JPEG-1 standard 25 years: past, present, and future reasons for a ...
    Aug 31, 2018 · ... 1986 resulting in the formation of the joint photographic experts group (JPEG). CCITT provided the service requirements for JPEG's technical ...
  15. [15]
    [PDF] JPEG2000: The Upcoming Still Image Compression Standard
    It is interesting to note that JPEG2000 is being designed to address the requirements of a diversity of applications,. e.g. Internet, colour facsimile, printing ...
  16. [16]
    ISO/IEC 15444-1:2000 - Core coding system
    Publication date. : 2000-12 ; Stage. : Withdrawal of International Standard [95.99] ; Edition. : 1 ; Number of pages. : 226 ; Technical Committee : ISO/IEC JTC 1/SC ...
  17. [17]
    [PDF] An Overview of JPEG-2000 - The University of Arizona
    JPEG-2000 is an emerging standard for still image compression. This paper provides a brief history of the JPEG-2000 standardization process, an overview of ...
  18. [18]
    JPEG XR image coding system - ISO/IEC 29199-2:2010
    ISO/IEC 29199-2:2010 specifies a coding format, referred to as JPEG XR, which is designed primarily for continuous-tone photographic content.
  19. [19]
    [1908.03565] Committee Draft of JPEG XL Image Coding System
    Aug 12, 2019 · JPEG XL is a practical approach focused on scalable web distribution and efficient compression of high-quality images.Missing: proposal 2010s
  20. [20]
    JPEG XL image coding system - ISO/IEC 18181-1:2022
    Status. : Withdrawn ; Publication date. : 2022-03 ; Stage. : Withdrawal of International Standard [95.99] ; Edition. : 1 ; Number of pages. : 101.
  21. [21]
    JPEG 2000 Part 1, Core Coding, Lossless Compression
    May 8, 2024 · The 2000 standard was withdrawn and replaced over time by ISO/IEC 15444-1:2004 and later, ISO/IEC 15444-1:2016, both of which were also ...Missing: launch 1997
  22. [22]
    Image and Video Coding Related Standardization Activities of ISO ...
    JTC 1 currently has 20 SCs including SC 29 as well as study groups (SGs), special working groups (SWGs), and working groups (WGs). *2, ISO/IEC JTC: ...
  23. [23]
    ITU-T extensions to JPEG-1
    The Joint Photographic Expert Group (JPEG) was founded in 1986 by its parent bodies, the then ITU CCITT SG 8 and ISO/TC97/SC2/WG8 group. ITU-T Rec. T.81 | ISO ...Missing: structure | Show results with:structure
  24. [24]
    ISO/IEC Directives, Part 1 – Consolidated ISO
    Working group Convenors shall be appointed by the committee for up to three-year terms. Such appointments shall be confirmed by the National Body (or liaison).Missing: JPEG | Show results with:JPEG
  25. [25]
    Participation - JPEG.org
    Upcoming JPEG meetings ; 110th ISO/IEC JTC1/SC29/WG1 (JPEG) Meeting. Location: Sydney, Australia. January 10, 2026 - January 16, 2026 ; 111th ISO/IEC JTC1/SC29/ ...Missing: committee structure vice-
  26. [26]
    JPEG - INCITS
    Committee Meeting Calendar · Membership Information/Join the Committee. Group Participants. Adobe Systems Inc · Alibaba Group. Amazon Web Services Inc. Apple.Missing: organizations | Show results with:organizations
  27. [27]
    W3C - World Wide Web Consortium - ISO
    Liaisons ; ISO/IEC JTC 1/SC 2/WG 2, Universal coded character set, C ; ISO/IEC JTC 1/SC 29/WG 1, JPEG Coding of digital representations of images, C ; ISO/IEC JTC ...
  28. [28]
    Developing standards - ISO
    The voting process is the key to consensus. ... Developing ISO standards is a consensus-based approach and comments from all stakeholders are taken into account.Technical Committees · Get involved · Resources · Deliverables
  29. [29]
    JPEG 1
    The JPEG 1 standard (ISO/IEC 10918) was created in 1992 (latest version, 1994) as the result of a process that started in 1986.
  30. [30]
    ISO/IEC 10918-5:2013 - JPEG File Interchange Format (JFIF)
    2–5 day deliveryGeneral information ; Status. : Published ; Publication date. : 2013-05 ; Stage. : Close of review [90.60] ; Edition. : 1 ; Number of pages. : 9.
  31. [31]
    [PDF] JPEG File Interchange Format
    Sep 1, 1992 · The syntax of a JFIF file conforms to the syntax for interchange format defined in Annex B of ISO DIS 10918-1. In addition, a JFIF file uses ...Missing: IEC | Show results with:IEC
  32. [32]
    JPEG - JPEG 2000
    ### ISO/IEC 15444 Parts for JPEG 2000
  33. [33]
    ISO/IEC 15444-1:2019 - JPEG 2000 image coding system
    This Recommendation | International Standard defines a set of lossless (bit-preserving) and lossy compression methods for coding bi-level, continuous-tone grey ...Missing: launch 1997 wavelet
  34. [34]
    JPEG 2000 image coding system - ISO/IEC 15444-10:2008
    ... JPEG 2000 image coding system: Extensions for three-dimensional dataPart 10: Withdrawn (Edition 1, 2008). New version available: ISO/IEC 15444-10:2011 ...Missing: 3D | Show results with:3D
  35. [35]
    JPEG 2000 image coding system - ISO/IEC 15444-11:2007
    ISO/IEC 15444-11:2007 provides a syntax that allows JPEG 2000 coded image data to be protected for transmission over wireless channels and networks.
  36. [36]
    High-Throughput JPEG 2000 - ISO/IEC 15444-15:2019
    General information ; Publication date. : 2019-10 ; Stage. : Close of review [90.60] ; Edition. : 1 ; Number of pages. : 72 ; Technical Committee : ISO/IEC JTC 1/SC ...
  37. [37]
    JPEG2000: The upcoming still image compression standard
    JPEG2000 is a new still image compression standard for various image types, providing superior performance and addressing areas where current standards fail.Missing: rise personal
  38. [38]
    Applications for JPEG 2000
    Specifically, it has been shown that Motion JPEG2000 outperforms the state-of-the-art MPEG-4 in terms of coding efficiency, error resilience, complexity, ...
  39. [39]
    (PDF) The JPEG2000 still image coding system: An overview
    Aug 6, 2025 · A new standard is currently being developed, the JPEG2000. It is not only intended to provide rate-distortion and subjective image quality performance superior ...<|separator|>
  40. [40]
    ISO/IEC 14495-1:1999 - Information technology — Lossless and ...
    In stockThis Recommendation | International Standard defines a set of lossless (bit-preserving) and nearly lossless (where the. error for each reconstructed sample ...Missing: JPEG | Show results with:JPEG<|separator|>
  41. [41]
    JPEG LS
    JPEG LS was defined to address the need for effective lossless and near-lossless compression of continuous-tone still images. This standard can be broken into ...
  42. [42]
    JPEG Lossless Compression (ISO/IEC 14495)
    Nov 17, 2023 · Format Description for JPEG-LS -- Compression encoding for continuous-tone images with both lossless and near-lossless modes.
  43. [43]
    JPEG XR image coding system - ISO/IEC 29199-2:2020
    This document specifies a coding format, referred to as JPEG XR, which is designed primarily for continuous-tone photographic content.
  44. [44]
    JPEG XR
    Part 3: Motion JPEG XR ... JPEG XR Part 3, known in ITU-T as T.833, is the Motion JPEG XR file format specification. The Motion JPEG XR file format is designed to ...
  45. [45]
    JPEG XR - Microsoft Research
    The JPEG XR format is now widely used in Microsoft products and services, in particular in Microsoft Office, where often pictures in PowerPoint or Word files ...
  46. [46]
    JPEG XR File Format (JXR) - The Library of Congress
    Jun 17, 2021 · JPEG XR is a still-image compression standard and file format for continuous tone photographic images, based on technology originally developed ...
  47. [47]
  48. [48]
    ISO/IEC 18477-1:2020 - Core coding system specification
    This document specifies a coding format, referred to as JPEG XT, which is designed primarily for continuous-tone photographic content.
  49. [49]
    JPEG XT
    JPEG XT extends the JPEG specification in a completely backwards compatible way. Existing tools and software will continue to work with the new code streams.
  50. [50]
    ISO/IEC 18477-3:2015 - Information technology
    ISO/IEC 18477-3:2015 specifies a coding format, referred to as JPEG XT, which is designed primarily for continuous-tone photographic content.
  51. [51]
    JPEG 2000 image coding system - ISO/IEC 15444-3:2007
    ISO/IEC 15444-3:2007 specifies the use of the wavelet-based JPEG 2000 codec for the coding and display of timed sequences of images (motion sequences), ...
  52. [52]
    Motion JPEG 2000 File Format - Library of Congress
    Aug 4, 2021 · ISO/IEC 15444-3:2007. Information technology -- JPEG 2000 image coding system -- Motion JPEG 2000 (formal name); Motion JPEG 2000 (common name).
  53. [53]
    JPEG Committee releases a call for evidence for image ...
    Feb 17, 2020 · JPEG Committee releases a call for evidence for image compression based on AI. The 86th JPEG meeting was held in Sydney, Australia. Among the ...Jpeg Ai · Jpeg Pleno · Jpeg Systems<|control11|><|separator|>
  54. [54]
    90th Meeting – Online - JPEG AI becomes a new work item of ISO/IEC
    Feb 5, 2021 · The new JPEG AI Learning-based Image Coding System has become an official new work item registered under ISO/IEC 6048 and aims at providing compression ...Missing: interoperability | Show results with:interoperability
  55. [55]
    JPEG AI reaches Draft International Standard stage
    May 7, 2024 · The 103rd JPEG meeting was held online from April 8 to 12, 2024. During this JPEG meeting, the first learning-based standard, JPEG AI, reached the Draft ...
  56. [56]
    106th Meeting – Online - JPEG AI becomes an International Standard
    Feb 19, 2025 · ... JPEG Committee has reached out to other standardization organizations. The JPEG Committee, already a collaborative group under ISO/IEC and ITU-T ...
  57. [57]
    JPEG - JPEG AI
    ### Summary of JPEG AI
  58. [58]
  59. [59]
    ISO/IEC 6048-1:2025 - Information technology — JPEG AI learning ...
    In stockJPEG AI is an image coding technology for compression and processing of images for human and machine vision, with a core system for human vision reconstruction.Missing: 24495 | Show results with:24495
  60. [60]
    JPEG Systems
    JPEG Systems Part 1 is a technical report describing the packaging of information using codestreams and file formats in legacy formats and give guidelines for ...
  61. [61]
    JPEG Trust
    JPEG Trust (ISO/IEC 21617) provides a framework for establishing trust in media. This framework includes aspects of authenticity, provenance, attribution.Missing: 24670 | Show results with:24670
  62. [62]
    JPEG Trust reaches Draft International Standard
    Feb 15, 2024 · JPEG Trust reaches Draft International Standard. The 102nd JPEG meeting was held in San Francisco, California, USA, from 22 to 26 January 2024.Missing: 2022 | Show results with:2022
  63. [63]
    ISO/IEC 21617-1:2025 - Information technology — JPEG Trust
    This document specifies a framework for establishing trust in media. This framework includes aspects of authenticity, provenance and integrity through ...
  64. [64]
    [PDF] Coding of Still Pictures - JPEG DS
    This standard, ISO/IEC. 21617, was published in January 2025. JPEG Trust arises from an exploration that started five years ago of requirements for addressing.Missing: 2022 | Show results with:2022
  65. [65]
    Documentation on JPEG Trust
    JPEG Trust is an international standard for establishing trust in digital media and assessing the trustworthiness of digital media assets.Missing: 24670 | Show results with:24670
  66. [66]
  67. [67]
    JPEG Trust: an international standard facilitating the assessment of ...
    JPEG Trust provides a comprehensive framework addressing key elements such as provenance, authenticity, integrity, and copyright declaration. Built on top of ...
  68. [68]
    [PDF] An update on JPEG Trust
    Feb 11, 2023 · “JPEG Trust does not explicitly define trustworthiness but rather provides a framework and tools for individuals, organisations, and governing ...Missing: 24670 | Show results with:24670
  69. [69]
    New tool to combat deepfakes and build trust in media - IEC
    Jan 28, 2025 · The new standard, known as JPEG Trust, will enable photos and videos to be 'tagged' and authenticated, so that users and creators can build trust in media ...Missing: 24670 | Show results with:24670
  70. [70]
    ISO/IEC 19566-8:2023 - JPEG Snack
    JPEG systems — Part 8: JPEG Snack.
  71. [71]
    JPEG - JPEG Pleno
    ### Summary of JPEG Pleno
  72. [72]
    ISO/IEC 21794-2:2021 - Information technology — Plenoptic image ...
    This standard specifies a coded codestream format for light field modalities and associated metadata, and provides information on encoding tools.Missing: 21734 | Show results with:21734
  73. [73]
    JPEG XL
    JPEG XL offers significantly better image quality and compression ratios than legacy JPEG. It is designed for computationally efficient encoding and decoding ...Missing: discontinues 2022
  74. [74]
    Why is JPEG the only compressed image choice in most digital ...
    Jul 28, 2021 · The 2017 spec includes an eXIF block, so EXIF data is now in the PNG standard. PNG is still a bad choice, but the reasons are not the same ...Missing: Nikon metadata
  75. [75]
    Understanding EXIF and metadata - Canon Georgia
    EXIF is a standardized way of storing metadata, which is "behind-the-scenes" information saved with image data, including camera and shooting settings.
  76. [76]
    Description of Exif file format - MIT Media Lab
    Exif file format is the same as JPEG file format. Exif inserts some of image/digicam information data and thumbnail image to JPEG in conformity to JPEG ...
  77. [77]
    Progressive JPEG images: what is it and how it can improve website ...
    Apr 13, 2025 · Benefits of Progressive JPEG​​ Most popular browsers, like Firefox and Chrome, also support progressive images. But if you use an older version ...Benefits of Progressive JPEG · How to Use Progressive JPEG...
  78. [78]
    The ultimate guide to Progressive JPEG Images - The Webmaster
    Dec 20, 2022 · Progressive images work well with all modern browsers, including Chrome, Firefox, and Internet Explorer 9. The only browsers with significant ...Should You Save a JPEG as... · Progressive JPEG Converters
  79. [79]
    Image resolution of photos you share on Instagram
    Upload a photo with a width of at least 1080 pixels with an aspect ratio between 1.91:1 and 3:4. Make sure you're using a phone with a high-quality camera as ...
  80. [80]
    How to Upload High-Quality Images to Instagram | 4K Download
    Feb 19, 2024 · Whether it's a PNG, WEBP, JPEG, or HEIC image, you can optimise it with 4K Image Compressor before uploading to Instagram. This desktop ...
  81. [81]
    8.2.3 JPEG-LS Image Compression - DICOM
    Note. The context where the usage of lossy (near-lossless) compression of medical images is clinically acceptable is beyond the scope of the DICOM Standard.
  82. [82]
    The Current Role of Image Compression Standards in Medical ... - NIH
    The JPEG-XR standard was developed with the primary goal of compressing continuous-tone still images such as photographic images [62]. The standard originated ...
  83. [83]
    Accelerating JPEG 2000 Decoding for Digital Pathology and ...
    Imaging data captured by the European Space Agency's Sentinel 2 satellites are stored as JPEG 2000 bitstreams. Sentinel 2 level 2A data ...
  84. [84]
    JPEG 2000 Format - Airbus Space Solutions
    JPEG 2000 is an image compression format for satellite images, enabling variable compression, and is smaller than GeoTIFF while retaining quality.
  85. [85]
    Usage Statistics of JPEG for Websites, November 2025 - W3Techs
    JPEG is used by 73.6% of all the websites. Historical trend. This diagram shows the historical trend in the percentage of websites using JPEG. Our dedicated ...
  86. [86]
    How JPEG Became the Internet's Image Standard - IEEE Spectrum
    Jul 1, 2025 · For roughly three decades, the JPEG has been the World Wide Web's primary image format. But it wasn't the one the Web started with.
  87. [87]
    What are the advantages of JPEG? - Educative.io
    5. Good for online image sharing. JPEG has become the go-to format for image sharing, particularly on social media platforms and image hosting websites.
  88. [88]
    WebP Compression Study - Google for Developers
    Aug 7, 2025 · The study evaluated WebP compression in comparison to JPEG. We observed that the average WebP file size is 25%-34% smaller compared to JPEG file ...
  89. [89]
    Using Modern Image Formats: AVIF And WebP - Smashing Magazine
    Sep 29, 2021 · Some tests have shown that AVIF offers a 50% saving in file size compared to JPEG with similar perceptual quality. Note that there can be cases ...
  90. [90]
    Compression Artifact - an overview | ScienceDirect Topics
    Compression artifact refers to visual distortions or imperfections in an image caused by the process of digital compression, leading to a loss of image quality.<|control11|><|separator|>
  91. [91]
    What are jpeg artifacts and what can be done about them?
    Jan 16, 2012 · JPEG tends to introduce two three kinds of distortions: Visible block structure and halos around edges are usually referred to as JPEG artifacts.Missing: criticisms | Show results with:criticisms
  92. [92]
    Meet AVIF—The Sharp New Image Format That's Set To Replace ...
    Jan 22, 2024 · Why Is AVIF Better Than JPEG? It basically boils down to compression—AVIF delivers clearer images at much smaller file sizes than JPEG. Netflix ...