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High Efficiency Image File Format
High Efficiency Image File Format
High Efficiency Image File Format
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High Efficiency Image File Format (HEIF)
Comparison of JPEG, JPEG 2000, JPEG XR and HEIF files at similar file sizes
Filename extension
.heif, .heifs; .heic, .heics; .avci, .avcs; .HIF
Internet media typeimage/heif, image/heif-sequence; image/heic, image/heic-sequence; image/avif
Uniform Type Identifier (UTI)public.heif, public.heic
Developed byMoving Picture Experts Group (MPEG)
Type of formatImage container
Extended fromISOBMFF
StandardISO/IEC 23008-12 (MPEG-H Part 12)
Open format?Depends on contained format (e.g. HEIC vs. free AV1 Image File Format)
Websitewww.iso.org/standard/83650.html Edit this at Wikidata

High Efficiency Image File Format (HEIF) is a digital container format for storing individual digital images and image sequences. The standard covers multimedia files that can also include other media streams, such as timed text, audio and video.[1]

HEIF can store images encoded with multiple coding formats, for example both SDR and HDR images. HEVC is an image and video encoding format and the default image codec used with HEIF. HEIF files containing HEVC-encoded images are also known as HEIC files. Such files require less storage space than the equivalent quality JPEG.[2][3]

HEIF files are a special case of the ISO Base Media File Format (ISOBMFF, ISO/IEC 14496-12), first defined in 2001 as a shared part of MP4 and JPEG 2000. Introduced in 2015, it was developed by the Moving Picture Experts Group (MPEG) and is defined as Part 12 within the MPEG-H media suite (ISO/IEC 23008-12).

History

[edit]

The requirements and main use cases of HEIF were defined in 2013.[4][5] The technical development of the specification took about one and a half years and was finalized in the middle of 2015.[6]

Apple was the first major adopter of the format in 2017 with the introduction of iOS 11 using the HEIC variant. While HEIC became the default for iPhones, it is possible to revert the settings to allow photos to be recorded in the JPEG format.[7]

Android devices containing the appropriate hardware encoders received support for HEIC files with the release of Android 10 (2019).[8]

On some systems, pictures stored in the HEIC format are converted automatically to the older JPEG format when they are sent outside of the system, although incompatibility has led to problems such as US Advanced Placement test takers failing due to their phones uploading unsupported HEIC images by default,[9] leading the College Board to request students change the settings to send only JPEG files.[10]

Although HEIC is gaining in popularity, it is not universally supported; Adobe Photoshop is an example of a popular image editing software that only supports 8-bit HEIC and not 10-bit or 12-bit HEIC.[11]

Camera hardware (including mobile devices) are increasingly supporting outputting HEIC files and with color depth often higher than 8-bit color.[12]

Specifications

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HEIF files can store the following types of data:[1]

Image items
Storage of individual images, image properties and thumbnails.
Image derivations
Derived images enable non-destructive image editing, and are created on the fly by the rendering software using editing instructions stored separately in the HEIF file. These instructions (rectangular cropping, rotation by one, two or three quarter-turns, timed graphic overlays, etc.) and images are stored separately in the HEIF file, and describe specific transformations to be applied to the input images. The storage overhead of derived images is small.
Image sequences
Storage of multiple time-related and/or temporally predicted images (like a burst-photo shot or cinemagraph animation), their properties and thumbnails. Different prediction options can be used in order to exploit the temporal and spatial similarities between the images. Hence, file sizes can be drastically reduced when many images are stored in the same HEIF file.
Auxiliary image items
Storage of image data, such as an alpha plane or a depth map, which complements another image item. These data are not displayed as such, but used in various forms to complement another image item.
Image metadata
Storage of Exif, XMP and similar metadata which accompany the images stored in the HEIF file.

Encodings inside the container

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The HEIF container can store the following encodings:

  • JFIF (JPEG)
  • AV1
  • HEVC

As users cannot easily tell what encoding and encoding parameters an image was stored in, the HEIF container format can be confusing and makes comparison statements like “HEIF is better than JPEG” vague and inaccurate.

Simply knowing a file is in the HEIF container does not reveal much information, as it could be:

  • a JFIF (JPEG);
  • a poor quality (default settings) AV1; or
  • a very high quality AV1 encoding (which takes a lot of processing power and takes a few minutes to encode); or
  • an HEVC with poor quality parameters; or
  • an HEVC with high quality parameters.

MIAF

[edit]

The Multi-Image Application Format (MIAF) is a restricted subset of HEIF specified as part of MPEG-A. It defines a set of additional constraints to simplify format options, specific alpha plane formats, profiles and levels as well as metadata formats and brands, and rules for how to extend the format.[13]

HEIC: HEVC in HEIF

[edit]

High Efficiency Video Coding (HEVC, ITU-T H.265)[14] is an encoding format for graphic data, first standardized in 2013. It is the primarily used and implied default codec for HEIF as specified in the normative Annex B to ISO/IEC 23008-12 HEVC Image File Format.

While not introduced formally in the standard, the acronym HEIC (High-Efficiency Image Codec) is used as a brand and in the MIME subtypes image/heic and image/heic-sequence. If the content conforms to certain HEVC profiles, more specific brands can be used: HEIX for Main 10 of HEVC, HEIM for (Multiview) Main profile, and HEIS for (Scalable) Main (10) profile of L-HEVC.

A HEIC photo takes up about half the space of an equivalent quality JPEG file.[15] The initial HEIF specification already defined the means of storing HEVC-encoded intra images (i-frames) and HEVC-encoded image sequences in which inter prediction is applied in a constrained manner.

HEVC image players are required to support rectangular cropping and rotation by one, two, and three quarter-turns. The primary use case for the mandatory support for rotation by 90 degrees is for images where the camera orientation is incorrectly detected or inferred. The rotation requirement makes it possible to manually adjust the orientation of a still image or an image sequence without needing to re-encode it. Cropping enables the image to be re-framed without re-encoding. The HEVC file format also includes the option to store pre-derived images.[16]

Samples in image sequence tracks must be either intra-coded images or inter-picture predicted images with reference to only intra-coded images. These constraints of inter-picture prediction reduce the decoding latency for accessing any particular image within a HEVC image sequence track.

The .heic and .heics file name extensions are conventionally used for HEVC-coded HEIF files.[17] Apple products, for instance,[18] will only produce files with these extensions, which indicate clearly that the data went through HEVC encoding.[2]

AVCI: AVC in HEIF

[edit]

Advanced Video Coding (AVC, ITU-T H.264) is an older encoding format for video and images, first standardized in 2003. It is also specified as a codec to be supported in HEIF in normative Annex 5 to ISO/IEC 23008-12. The registered MIME types are image/avci for still images and image/avcs for sequences. The format is simply known as AVCI.

Apple products support playback of AVC-encoded .avci still image files and .avcs image sequence files[18] but will only generate .heic files.

AVIF: AV1 in HEIF

[edit]
This section is about AV1 and AVIF. For AVI, see Audio Video Interleave.
Main article: AVIF

AV1 is a video encoding format that is intended to be royalty-free, developed by the Alliance for Open Media (AOMedia). AV1 Image File Format (AVIF) is an image format based on this codec.[19]

The registered MIME type is image/avif for both still images and image sequences, and .avif is the file name extension.[20]

JPEG compression formats in HEIF files

[edit]

The original JPEG standard is the most commonly used and widely supported lossy image coding format. It was first released in 1992 by ITU-T and ISO/IEC. Although Annex H to ISO/IEC 23008-12 specifies JPEG (and indirectly Motion JPEG) as a possible format for HEIF coded image data, it is used in HEIF only for thumbnails and other secondary images. Therefore, neither a dedicated MIME subtype nor a special file extension is available for storage of JPEG files in HEIF container files.

Several other compression formats defined by the JPEG group can be stored in HEIF files:

  • Part 16 of the JPEG 2000 standard suite (ISO/IEC 15444-16 and ITU-T Rec. T.815) defines how to store JPEG 2000 images in HEIF container files.[21][22] Part 2 of the JPEG 2000 suite (ISO/IEC 15444-2 and ITU-T Rec. T.801)[23][24] also defines a different format for storing JPEG 2000 images in files that is also based on ISOBMFF.
  • Annex F of the JPEG XR image coding standard (ISO/IEC 29199-2 and ITU-T Rec. T.832) defines how to store JPEG XR images in HEIF container files.[25][26] Annex A of JPEG XR also defines a different file format for storing JPEG XR images in files that is TIFF-based, and Part 2 of the JPEG 2000 suite (ISO/IEC 15444-2 and ITU-T Rec. T.801) also supports a third file format for storing JPEG XR images in files that is based on ISOBMFF.
  • JPEG XS has its HEIF container support defined in ISO/IEC 21122-3.[27]

In 2017, Apple announced that it would adopt HEIC as the default image format in its new operating systems, gradually replacing JPEG.[28]

WXAM, SharpP

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The proprietary image format WXAM (or wxHEPC) developed by Tencent (used within, e.g., WeChat) is apparently based upon HEVC,[29] as is SharpP, which was developed by their SNG (Social Network Group) division.[30][31] However, their container format may not be HEIF-compatible. In March 2017, SharpP switched to AVS2[32] and was renamed TPG (Tiny Portable Graphics).[31][33]

Support

[edit]
See also: AVIF § Support
  • Nokia provides an open source C++ HEIF decoder, that also has a Java API.[16]
  • The open source library "libheif" supports reading and writing HEIF files.[34][35] From version 1.8.0, both reading and writing HEIC and AVIF are supported.[34]
  • An image codec called CopyTrans HEIC, which is free for personal use and available for Windows versions 7 through 10, supports opening HEIF files in Windows Photo Viewer without the Microsoft codec installed. (The Microsoft HEIC codec is only available for Windows 10, version 1803 and up in the Photos UWP app.)[36]

Operating systems

[edit]

Web browsers

[edit]

As of August 2024, only Safari supports HEIC format natively.[52]

For AVIF, Chrome, Firefox and Opera for desktop and Android support it. Safari on iOS 16 and iPadOS 16 supports AVIF format.[53]

Image editing software

[edit]

Image libraries

[edit]
  • libheif – ISO/IEC 23008-12:2017 HEIF and AVIF decoder and encoder.
  • SAIL – format-agnostic library with support of HEIC implemented on top of libavif.
  • FFmpeg
  • AVIF and HEIC unit - Delphi/Lazarus wrapper for libavif
  • JDeli - Java Image library with HEIC support
  • Nokiatech - Nokia's HEIF library with Java wrapper

Hardware

[edit]

Websites

[edit]
  • During May 2020, online Advanced Placement exams allowed students to submit photos of handwritten responses. Because the website was unable to process HEIF images, students whose phones defaulted to this image format were considered to have not submitted any response and often failed to complete the exam. College Board, which administers the exams, later provided a system for users to submit photos of answers via email. Because the iOS Mail app automatically converts HEIF images to JPEG, this mitigated the problem.[80]
  • Facebook supports the upload of HEIC but converts to JPEG or WebP on display.[81]
  • Discord does not support HEIC at all.[82]
  • Wikimedia Commons does not support HEIC.[83]

Patent licensing

[edit]
Further information: High Efficiency Video Coding § Patent holders

HEIF itself is a container that may not be subject to additional royalty fees for commercial ISOBMFF licensees. Nokia also grants its patents on a royalty-free basis for non-commercial purposes.[84] When containing images and image sequences encoded in a particular format (e.g., HEVC or AVC) its use becomes subject to the licensing of patents on the coding format.[85][86][87]

See also

[edit]
  • Better Portable Graphics (BPG) – another image file format using HEVC encoding, published by Fabrice Bellard in 2014
  • JPEG XL – an image file format developed since 2019 (standardization completed since 2022) and based on Google PIK [Wikidata] and Cloudinary FLIF (itself based upon FUIF [Wikidata]) claiming to outperform PNG, WebP, BPG and JPEG 2000 for lossless encoding at least
  • WebP – an image file format that features both lossy (based on VP8 and VP9) and lossless (independently developed) compression

References

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[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

High Efficiency Image File Format

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The High Efficiency Image File Format (HEIF) is an (ISO/IEC 23008-12) developed by the (MPEG) that defines a for storing individual still images, collections of related images (such as grids or bursts), image sequences (including animations), and associated metadata, enabling efficient interchange, editing, and display across devices and applications. Based on the (ISOBMFF), HEIF primarily employs (HEVC, ITU-T H.265 / ISO/IEC 23008-2) as its default codec for superior compression, though it supports other schemes like (AVC) and for broader compatibility. Standardized initially in December 2017 as part of the suite ( Part 12), HEIF builds on earlier work in image container technologies dating back to concepts shared with MP4 and in the early , with formal development accelerating in the to address the growing demand for high-quality imaging in mobile and web environments. The format was updated in its second edition (ISO/IEC 23008-12:2022) to include enhancements like support for predictive image coding, for exposure adjustments, and improved metadata handling. Key features of HEIF include the ability to embed multiple images or frames in a single file (reducing overhead compared to separate files), support for transparency via alpha channels, (HDR) and wide color gamut (WCG) for enhanced visual fidelity, depth maps for , and non-square pixel aspect ratios. These capabilities, combined with HEVC's compression, allow HEIF to achieve smaller file sizes than while preserving or improving image quality, making it particularly suitable for resource-constrained devices like smartphones. HEIF gained widespread adoption following Apple's integration in and in 2017, where it became the default format for photos using the .heic file extension and HEVC-encoded videos using the .mov file extension, followed by full support in in 2019 and native camera encoding in Android 11. Major camera manufacturers, including those producing devices for and Android ecosystems, have since incorporated HEIF for in-camera capture, contributing to its role as a modern successor to legacy formats like in consumer photography.

Overview

Definition and Purpose

The High Efficiency Image File Format (HEIF), formally defined in ISO/IEC 23008-12, serves as a for storing individual still images, collections of images, and image sequences, along with associated metadata. It builds upon the (ISOBMFF, ISO/IEC 14496-12) to provide an interoperable structure that enables the interchange, editing, and display of these visual assets. This encapsulation allows HEIF files to support a range of compressed , prioritizing in storage and transmission without altering the core of the underlying compression methods. HEIF was developed to deliver significantly better compression performance than legacy formats such as through its integration of advanced coding techniques. Its primary purpose is to facilitate high-quality image handling in resource-constrained environments like mobile devices and online platforms, where bandwidth and storage limitations are critical. Key to this goal are features such as embedding multiple images or sequences in a single file—ideal for burst photography or layered compositions—along with support for alpha channels enabling transparency and (HDR) for enhanced color and contrast representation. These capabilities address the limitations of older formats, promoting more versatile and efficient image workflows. A notable variant of HEIF is the HEIC profile, which specifies the use of (HEVC) for the encoded image data within the container. First standardized by the (MPEG) in 2015 and published by the (ISO) in 2017, HEIF emerged amid increasing demands for bandwidth-efficient formats capable of supporting evolving imaging technologies like HDR and .

Key Advantages

The High Efficiency Image File Format (HEIF) achieves superior compression efficiency compared to legacy formats like , typically producing file sizes up to 50% smaller while maintaining equivalent visual quality, thanks to its use of advanced codecs such as HEVC. For instance, a 12-megapixel compressed in at around 5 MB can be reduced to approximately 2.5 MB in HEIF without perceptible quality loss. This efficiency stems from block-based coding and predictive techniques in the underlying video codecs, enabling better handling of spatial redundancies in still images. HEIF supports an advanced feature set that extends beyond basic raster storage, including alpha channels for transparency, high dynamic range (HDR) imaging at 10-bit depths, and wide color gamut coverage such as BT.2020. It also enables lossless re-encoding of existing images by storing the original compressed data intact within the HEIF container, preventing generational quality degradation during repeated saves. A key capability of HEIF is its support for multi-image storage within a single file, allowing bursts of photos, panoramas, or even short animations to be bundled efficiently, which reduces overall storage requirements compared to separate files in traditional formats. This container-based design organizes multiple images and associated metadata cohesively, ideal for mobile capture scenarios. For , HEIF files can embed legacy JPEG images as fallback representations, ensuring display on systems lacking native HEIF support without requiring full conversion. This approach minimizes compatibility issues during the format's adoption. Compression advantages in HEIF typically achieve 40-50% file size reductions compared to , depending on image content and codec used. HEIF's compression advantages translate to significant bandwidth savings, particularly in web and mobile applications; for example, since adopting HEIF as the default photo format on iPhones starting with in 2017, Apple users have seen photo storage halved on devices and in , preserving quality while easing data transfer constraints.

Development History

Origins and Early Development

The High Efficiency Image File Format (HEIF) originated from the (HEVC, or H.265) standard, which was finalized by the (MPEG) in April 2013 as part of efforts to advance video compression efficiency. HEIF adapted HEVC's tools—originally designed for video sequences—to the domain of still images, promoting uniformity in media handling across video and photography applications. This extension addressed the growing need for better compression of static images, leveraging HEVC's superior performance over prior formats like . In July 2013, at the 105th MPEG meeting, requirements for still image coding using HEVC were issued. The first working draft of HEIF (ISO/IEC 23008-12) was developed shortly thereafter, emphasizing a container structure based on the (ISOBMFF) to enable flexible storage of single images or sequences. These early proposals prioritized compatibility with emerging high-resolution imaging, such as 4K photos from smartphones, where traditional struggled with file sizes amid rising storage and bandwidth constraints. Key industry drivers included the rapid evolution of mobile camera technology, with devices producing larger, higher-quality images that demanded more efficient formats beyond 2000's complexity. Companies like , heavily invested in mobile imaging, collaborated on these efforts to reduce storage needs in smartphones and cameras, anticipating widespread adoption for consumer . Pre-2015 milestones featured proof-of-concept demonstrations at MPEG meetings in 2014, where intra-HEVC coding achieved 40-50% better compression than at equivalent perceptual quality, validating the approach through subjective evaluations on diverse image sets.

Standardization and Evolution

The High Efficiency Image File Format (HEIF) was initially standardized by the (MPEG) in October 2015 as Part 12 of the suite, with the core specification published by the (ISO) as ISO/IEC 23008-12 in December 2017. This inaugural edition defined the foundational container structure based on the (ISOBMFF), primarily supporting (HEVC) for still images and sequences, enabling efficient storage, interchange, and editing of visual content. Subsequent amendments expanded the format's versatility. The 2017 edition itself incorporated provisions for broader codec compatibility beyond the initial HEVC focus, allowing integration with other compression methods while maintaining the ISOBMFF foundation. In 2018, the (AOM) published the initial specification for image support within the HEIF container, which evolved into the format and was formally standardized in 2020 as part of ISO/IEC 23000-22, introducing royalty-free AV1-based encoding as a key extension. Related standards further evolved the ecosystem. The Multi-Image Application Format (MIAF), specified in ISO/IEC 23000-22 and first published in June 2019, builds directly on HEIF to support mixed-media files combining images, audio, and video in a single container, enhancing for applications like and panoramic stitching. Proposals for integrating JPEG XL codec support into the HEIF container were discussed in MPEG working group meetings from 2020 to 2022, aiming to leverage 's lossless and progressive features within the established ISOBMFF structure, though full adoption remains under consideration. The second edition of the standard (ISO/IEC 23008-12:2022) introduced enhancements including predictive image coding, for exposure adjustments, and improved metadata handling with compact boxes for efficient storage of image properties and auxiliary , addressing needs for low-overhead applications. The third edition, published in 2025, incorporates these changes alongside low-overhead profiles.

Technical Specifications

The High Efficiency Image File Format (HEIF), as defined in ISO/IEC 23008-12:2025 (third edition), is built upon the (ISOBMFF), defined in ISO/IEC 14496-12, which organizes data into a hierarchical structure of boxes, each identified by a four-character code (4CC) and containing a size field followed by payload data that may include nested boxes. This extensible allows HEIF files to encapsulate individual images or collections as discrete "items" rather than timed tracks typical of video formats, enabling efficient storage of static media with associated metadata. At the root level, every HEIF file begins with a mandatory ftyp (file type) box, which declares the file's compatibility by listing supported brands in its compatible_brands field, such as 'heic' for HEVC-coded images using the Main Profile or 'heix' for those using Main 10 Profile or format range extensions. Following the ftyp box, the core structure is housed within a meta (metadata) box at the file root, which serves as the primary container for descriptive and organizational elements related to the image items. Inside the meta box, a hdlr (handler reference) box specifies the handler type as 'pict' to indicate that the enclosed items represent picture (image) data. Item management is facilitated by several key boxes within or referenced by meta. The iinf (item information) box provides details on each item, including unique item IDs, content types, and optional properties like item protection; for instance, compressed data is assigned item types specific to the , such as 'hvc1' for HEVC. The iloc (item location) box acts as an index, mapping each item ID to its storage location within the file, including offsets, lengths, base offsets, and extent counts to support both in-file and external references. Additionally, the pitm (primary item reference) box designates a specific item—often with ID 1—as the primary or cover when multiple items are present. HEIF files support both single-image and multi-image configurations, where all images are treated as independent items referenced by their IDs, allowing flexible organization without requiring a dedicated movie box for non-sequential content. By default, each item's data is limited to 4 GB due to 32-bit size fields in ISOBMFF, but extensions using 64-bit large-size boxes enable handling of larger individual items. This box-based architecture ensures with broader ISOBMFF parsers while enforcing HEIF-specific constraints on box ordering and hierarchy for image-centric files.

Metadata and File Organization

The High Efficiency Image File Format (HEIF) organizes metadata within its container using boxes derived from the (ISOBMFF), enabling flexible association of descriptive and transformative properties with image items. The primary metadata structure is housed in the 'meta' box, which contains the Item Information Box ('iinf') and Item Protection Box ('ipro') if is used, along with other elements for property management. This setup allows metadata to describe image characteristics, transformations, and relationships without altering the core coded image data. Item properties are central to HEIF metadata, stored in the Item Properties Box ('iprp'), which encapsulates an Item Property Container Box ('ipco') holding shared properties applicable to multiple items. Essential properties include the Image Spatial Extents ('ispe'), which defines the width and height of an image item in pixels, and the Pixel Information ('pixi'), specifying the number of color channels and their bit depths for accurate rendering. These properties are essential for decoders to interpret the spatial and color characteristics correctly, with 'ipco' allowing reuse across items to optimize file size. HEIF organizes image items through the Item Information Box ('iinf'), where each Item Information Entry ('infe') details an item's ID, type (e.g., 'hvc1' for HEVC-coded images), and flags such as hidden_item (bit 0 set to 1 to prevent display) and primary_item (bit 1 set to 1 to designate the main image). Items can be grouped logically, with support for auxiliary roles like thumbnails, marked via item type 'thmb' or auxiliary flags, allowing efficient storage of preview images without affecting the primary content. The Item Property Association Box ('ipma') maps these properties from 'ipco' to specific items by referencing item IDs and indices, ensuring targeted application while maintaining decoder compatibility through versioning and essential flags. Standard metadata formats like and XMP are integrated as separate items within the 'meta' box, using item types 'Exif' or 'xmpx' respectively, and linked to the primary image via the 'cdsc' (coded data) item reference type. Rotation and orientation adjustments are handled through transformative properties such as Image Rotation ('irot'), which specifies clockwise rotations of 90, 180, or 270 degrees, associated via 'ipma' to avoid re-encoding the image data. Similarly, 'ipma' applies branding properties like auxiliary image designation (for non-display items like alpha channels) and Clean Aperture ('clap'), which defines cropping regions to guide rendering without . A distinctive feature of HEIF metadata is its support for hierarchical item references, enabling complex compositions such as overlays, where an output item references input items (coded or derived) via types like 'dimg' for dependencies or specialized references for layering. This allows derived images, including overlays, to build upon base images while preserving metadata associations through chained references in the Item Reference Box ('iref'). Such organization facilitates advanced editing workflows, with properties propagating hierarchically to ensure consistent rendering across decoders.

Supported Codecs and Encodings

HEVC-Based Encoding (HEIC)

The HEIC profile within the High Efficiency Image File Format (HEIF) utilizes the (HEVC) codec, specifically employing from the Main Still Picture profile as defined in ISO/IEC 23008-12. This profile restricts inter-prediction to ensure compatibility with still image applications while leveraging HEVC's advanced compression tools. Files encoded under this profile typically use the .heic extension for single images and .heics for image sequences. HEVC-based encoding in HEIC relies on block-based prediction and , achieving significant compression improvements over H.264 (AVC) intra-coding, with bit-rate savings typically ranging from 25-50% for equivalent perceptual quality in still images (based on intra-coding benchmarks). It supports bit depths from 8 to 12 bits per channel and chroma subsampling formats including and 4:2:2, enabling high-fidelity representation of color and data. In the HEIF container, HEVC-coded image data is identified by item types such as 'hvc1' or 'hev1', where 'hvc1' stores parameter sets out-of-band in the sample description, and 'hev1' embeds them in-band within the bitstream. The HEVC decoder configuration, including profile, level, and parameter set details, is stored in the 'hvcC' box to facilitate decoding. Apple adopted HEIC as the default format for photos on iPhones starting with in 2017, integrating it with features like Live Photos, which are stored as HEVC-encoded image sequences in .heics files to capture short bursts of motion alongside the primary still image. Performance benchmarks presented at Apple's 2017 (WWDC) demonstrated that HEIC encoding takes longer than —up to several times the duration for high-quality settings—due to the of HEVC intra-coding, but results in file sizes roughly half that of comparable , highlighting the for superior compression.

AVC-Based Encoding (AVCI)

The AVC-based encoding profile, known as AVCI, integrates the Advanced Video Coding (AVC, or H.264) standard into the High Efficiency Image File Format (HEIF) container to enable efficient storage of still images using a widely supported codec. This profile restricts encoding to intra-frame only, utilizing AVC's Baseline or High profiles to ensure compatibility with existing hardware and software decoders that support video playback. AVCI files are typically identified by the .avci extension and serve as a bridge between legacy formats and more advanced HEIF capabilities. In terms of compression, AVCI employs block-based intra prediction, integer , and in-loop filtering, which provide enhancements over traditional by incorporating more sophisticated spatial prediction modes. This results in file sizes approximately 20-30% smaller than equivalent images at similar quality levels, though it falls short of the efficiency gains offered by HEVC-based encoding. For instance, studies show H.264 intra coding achieves bit-rate savings of 20-40% compared to across various test images, depending on content complexity. Within the HEIF file structure, AVC-encoded image items are designated using the 'avc1' or 'avc3' item type codes, where 'avc1' includes codec initialization data in the sample entry and 'avc3' places it separately in NAL units. The AVC decoder configuration, including sequence parameter sets (SPS) and picture parameter sets (PPS), is stored in the mandatory 'avcC' box to facilitate decoding. This setup aligns with the ISO Base Media File Format (ISOBMFF) handling of image items, allowing seamless integration with HEIF's metadata and multi-image features. AVCI was standardized as part of Amendment 1 to ISO/IEC 23008-12 in , extending the original HEIF specification to include AVC support alongside HEVC and for broader adoption. It is particularly useful as a transitional format on devices without dedicated HEVC , enabling photographers and applications to leverage HEIF's advanced organization—such as image collections and overlays—while relying on ubiquitous AVC decoders. A key limitation of AVCI is its higher bitrate requirements relative to HEVC, resulting in larger file sizes for comparable perceptual quality; for example, AVC-encoded HEIF images can be around 10-20% larger than their HEVC counterparts in practical tests. This makes AVCI less ideal for storage-constrained environments but valuable for interoperability in mixed codec ecosystems.

AV1-Based Encoding (AVIF)

The AV1 Image File Format () profile integrates the codec, developed by the (AOMedia) and released in 2018, into the High Efficiency Image File Format (HEIF) container. employs , utilizing only keyframes from its video compression framework to encode static images without inter-frame dependencies, enabling efficient single-image storage. Files in this profile typically use the .avif extension, distinguishing them from other HEIF variants while maintaining compatibility with the ISOBMFF-based structure. AVIF often achieves compression efficiencies comparable to or slightly superior (up to 30%) to HEVC-based formats like HEIC for still images, delivering smaller file sizes at equivalent visual quality, based on intra-coding benchmarks. This profile is fully royalty-free under AOMedia's open-source licensing, eliminating patent encumbrance barriers that affect proprietary . It supports (HDR) imaging through AV1's extended bit depth and capabilities, as well as transparency via alpha channel extensions in the codec, facilitating layered compositions without additional formats. In the HEIF container, images are handled via the 'av01' item type identifier, which signals -coded content to decoders. Configuration parameters, including sequence headers that define codec profiles, , and structure, are stored in the 'av1C' box, ensuring self-contained decoding without external dependencies. This setup allows seamless integration of as image items, supporting features like progressive refinement through multiple quality layers if present. The specification was first defined by AOMedia in version 1.0.0 in February 2019, focusing on still image storage with provisions for sequences. It was subsequently integrated into the HEIF standard via the ISO/IEC 23000-22 update in July 2020, formalizing as a supported within the broader container framework. By 2025, has gained significant traction for web imagery due to its open licensing and superior efficiency, with support in major browsers (as of November 2025) promoting its adoption alongside formats like . Ongoing proposals, including enhancements in the 2024 AOMedia discussions leading to version 1.2.0 released in November 2025, aim to refine animation capabilities by improving temporal composition and lossless modes for multi-frame sequences.

Other and Proprietary Encodings

HEIF supports the encapsulation of legacy images through a dedicated item type designated as 'jpeg', enabling a lossless re-wrapping process that embeds the original JPEG bitstream directly into the HEIF container without any re-compression or alteration of the image data. This approach facilitates compatibility with existing JPEG content, allowing HEIF files to serve as wrappers for traditional photographs while benefiting from the container's advanced metadata and multi-image capabilities. Similarly, images can be integrated into HEIF files using the 'png ' item type, which preserves the , transparency, and color information inherent to the PNG format. This embedding is particularly useful for graphics and images requiring exact reproduction, such as icons or diagrams, without introducing compression artifacts. encodings within HEIF include WXAM (also known as wxHEPC), developed by for optimized performance in Windows environments and specific applications like platforms. HEIF also supports (VVC, ISO/IEC 23090-3) for future-proof high-efficiency encoding and (ISO/IEC 21122-3) for low-latency professional applications, as per updates in ISO/IEC 23008-12:2022. These and additional options extend HEIF's flexibility for vendor-specific use cases but may limit compared to open standards. The Multi-Image Application Format (MIAF), defined in ISO/IEC 23000-22, builds on HEIF by imposing constraints that enhance interoperability for multi-image files, including support for mixed encodings such as and AVC within the same container for applications. This allows, for instance, a primary image paired with an auxiliary AVC-encoded layer in a single HEIF file, providing fallback compatibility while enabling advanced features like layered representations. Such configurations are valuable for ensuring broad device support in scenarios where high-efficiency codecs are unavailable. In practice, these other and proprietary encodings serve primarily as compatibility fallbacks, enabling the adoption of HEIF in ecosystems with diverse legacy content; for example, a HEIF file might use a JPEG item as the main image for universal viewing, supplemented by a proprietary encoding for enhanced quality on supported hardware.

Advanced Features

Image Sequences and Multi-Image Support

The High Efficiency Image File Format (HEIF) enables the storage of multiple images or image sequences within a single container file based on the ISO Base Media File Format (ISOBMFF), facilitating efficient organization of related visual content such as bursts or animations. This multi-image capability allows for the inclusion of still images, derived images, and timed sequences, all referenced and structured through specific boxes in the file format. In burst mode, HEIF supports the capture and storage of multiple similar images, such as a sequence from rapid , organized as timed items within the file. A cover image for the burst is designated using the 'cdsc' (content describes) item reference type in the 'iref' (item reference) box, which links a metadata track to the sequence track for quick identification of the primary frame. The 'pitm' (primary item) box further specifies the default or main image to display from the collection, ensuring seamless presentation of the burst as a cohesive unit. For animations and short clips, HEIF treats sequences of images as timed tracks, with playback timing defined by the 'tfdt' (track fragment decode time) box to synchronize frames. This structure is particularly suited for brief animated content, such as cinemagraphs or lightweight alternatives to GIFs, where images are encoded and sequenced for smooth reproduction. The 'iref' box manages interdependencies, such as overlays or derivations, enabling features like grid-based compositions for panoramic images constructed from multiple tiles in one file. This approach enhances storage efficiency on devices, consolidating multiple images from bursts into a single HEIF file and reducing the need for numerous separate files. The format's design supports up to 2³² items (approximately 4.3 billion) per file, limited by the 32-bit item ID in ISOBMFF, making it scalable for large collections while maintaining low overhead for typical mobile use cases.

Scalability and Compatibility Features

The High Efficiency Image File Format (HEIF) incorporates features that enable efficient storage and rendering of images with varying levels of detail within a single file. Scalable layers are supported through multi-layer image structures, where lower-resolution versions, such as thumbnails, can be embedded alongside higher-resolution master images, facilitating progressive loading and refinement. This is achieved using Item Property Association ('ipma') boxes in the ItemPropertyContainerBox, which link descriptive and transformative properties to specific image items, allowing for non-destructive and hierarchical resolution enhancement. For instance, a file might contain a low-resolution preview for quick display, with subsequent layers providing progressive refinement up to full resolution, as outlined in the format's entity group mechanisms for progressive rendering. The third edition of ISO/IEC 23008-12 (2025) introduces enhancements including explicit support for progressive decoding, rendering, and refinement of multi-layer images, along with signaling for camera intrinsic and extrinsic matrices, annotations for sequences, and renderable text items, improving for scalability features. HEIF also accommodates multi-view representations to support advanced applications like 3D and (AR). Stereo pairs are realized by storing left- and right-eye images as auxiliary items associated with a primary , enabling stereoscopic display without separate files. Depth maps, similarly treated as auxiliary images, provide spatial information that complements the master , allowing for AR rendering where depth data informs object placement and occlusion in virtual environments. These features leverage the format's item reference system to associate auxiliary content efficiently. To ensure broad compatibility across devices and software, HEIF includes mechanisms for handling display variations and . The Clean Aperture property, a transformative , defines a rectangular region for cropping, enabling consistent presentation by excluding padding or areas common in video-derived images. For transparency, alpha channels are supported via auxiliary images that store opacity data, which can be blended with the primary image using standard rules, preserving effects like or overlays in workflows involving layered graphics. High dynamic range (HDR) and wide color gamut (WCG) capabilities in HEIF are signaled through dedicated properties, supporting bit depths up to 16 bits per sample to capture extended and color precision. Color spaces such as BT.2020 are accommodated via the Colour Information Box ('colr') and Mastering Display Colour Volume Box ('mdcv'), which convey primaries, transfer characteristics, and maximum for accurate reproduction on compatible displays. This integration allows HEIF files to store HDR content derived from HEVC or other supported codecs without loss of fidelity. In the AV1-based encoding variant (AVIF), scalability is further enhanced for web applications through spatial scalability layers in the codec, permitting initial low-resolution decoding followed by higher-quality refinements as data loads progressively. This reduces bandwidth needs for responsive web imaging, with browser support enabling seamless integration since 2020 in major engines.

Adoption and Support

Operating Systems

Apple introduced full support for the High Efficiency Image File Format (HEIF), including the HEIC brand, in and , both released in 2017, enabling users to view, edit, and capture photos in this format natively. Since then, HEIF has become the default format for photos taken with the Camera app on compatible Apple devices, leveraging (HEVC) for compression to reduce file sizes by about half compared to while maintaining quality. This integration extends to and , with ongoing updates ensuring compatibility across Apple's ecosystem as of 2025. Android added HEIF encoding support starting with Android 8.0 () in 2017, allowing devices to save images in the HEIC format, though initial implementation focused on specific hardware capabilities. Native decoding of HEIF files became standard in , released in 2019, enabling seamless viewing and handling without third-party apps on supported devices. By 2025, Android supports Ultra HDR images in the HEIC format via updates like Android 16, with support for Ultra HDR in development for future enhancements in the Android Open Source Project (AOSP), reflecting its adoption for better efficiency in high-dynamic-range (HDR) photography. Microsoft provides HEIF support in Windows through the HEIF Image Extensions package, available via the since 2018, which allows reading and writing HEIF files in apps like and . For within the HEIF container, includes native decoding since its 2021 release, but full functionality often requires the separate Video Extension from the Store, particularly for encoding and advanced features as of 2025. HEIC-specific handling in improved with the 2023 November Cumulative Update, reducing the need for conversion during file transfers from devices, though the extensions remain essential for broader compatibility. Linux distributions handle HEIF through the open-source libheif library, which provides decoding and encoding for both HEIF and formats via a unified . Native support is available in major distributions like 20.04 and later, where libheif is included in repositories, allowing image viewers such as GNOME's to open HEIC and files out-of-the-box after installation. As of 2025, 24.04 and subsequent releases recommend updating to libheif version 1.20 or higher for enhanced compatibility with newer HEIF features from devices like recent iPhones, though kernel-level drivers in 6.10 focus on general multimedia improvements rather than specific AVIF acceleration.

Web Browsers and Software

Safari has provided native support for HEIC (High Efficiency Image Container, a subset of HEIF using HEVC encoding) since version 10.1 in 2017, enabling full decoding and display of HEIF files in web contexts on Apple platforms. As of November 2025, major browsers like Chrome, , and Edge do not offer native support for HEIC or broader HEIF formats due to licensing complexities associated with HEVC patents, though experimental implementations are in testing for potential rollout later in the year. For the AVIF variant of HEIF (using AV1 encoding), support is more widespread: Chrome has included it since version 85 in 2020, since version 93 in 2021, since version 16 in 2022, and Edge (Chromium-based) since version 121 in 2023. This allows AVIF images to be rendered natively across these browsers without additional plugins, facilitating efficient web delivery of high-quality visuals. Editing software adoption varies. added native import/export support in its June 2025 release (version 26.8), building on existing HEIF/HEIC handling capabilities, allowing users to open, edit, and save files in these formats while preserving up to 12-bit and HDR metadata. has supported HEIF/HEIC and decoding since version 2.10.22 in 2020 through integration with the libheif library, though export capabilities for may require specific build configurations and can encounter color fidelity issues in some workflows. , however, lacks native or HEIF support as of late 2025, with users relying on external conversion tools for compatibility, despite the application's inclusion of other modern formats like . Key libraries underpin much of this ecosystem. The open-source libheif, first released in 2017, provides robust C -based decoding and encoding for both HEIF (including HEIC) and , with version 1.20.2 (August 2025) enhancing multi-threaded performance and codec integration for broader application use. On Android, the HEIFWriter class in the Android framework enables encoding since API level 28 (2018), supporting programmatic creation of HEIF files in apps. By 2025, enjoys approximately 95% global browser support among major versions, driven by its royalty-free foundation and superior compression, positioning it as a preferred format for web imagery while HEIC remains confined primarily to ecosystems. Challenges persist for legacy software lacking native handling, often addressed via conversion utilities such as heif-convert from the libheif suite, which batch-transforms HEIC/ files to or without quality loss for compatibility in unsupported environments.

Hardware and Devices

Support for the High Efficiency Image File Format (HEIF) in hardware has primarily focused on encoding and decoding capabilities within mobile devices, cameras, and system-on-chips (SoCs), enabling efficient processing of HEIC and related variants without relying on software emulation. Apple's and Plus, released in 2016, introduced hardware capture of media in HEIF and HEVC formats, marking an early adoption in consumer smartphones. This integration allowed for smaller file sizes while maintaining high quality, leveraging dedicated hardware encoders in the device's signal processor. Professional and flagship cameras have also incorporated HEIF support for hybrid workflows. The , launched in 2020, supports recording in HEIF format alongside and RAW files, particularly for 10-bit HDR PQ images, using its built-in hardware to produce high-dynamic-range outputs directly from the sensor. Similarly, Qualcomm's Snapdragon 888 SoC, introduced in 2021, provides hardware-accelerated HEVC decoding, essential for HEIC processing in Android flagships like those from and others, enabling seamless playback and reduced latency in mobile applications. Advancements in AV1-based HEIF variants, such as , have appeared in recent SoCs. Apple's A17 Pro chip, debuted in 2023 with the , includes a dedicated hardware decoder, facilitating efficient decoding of AVIF images and videos for improved streaming and storage efficiency on mobile devices. Regarding display hardware, Samsung's QLED televisions since 2019 have offered partial HEIF compatibility in HDR modes, though full support varies by model and firmware, often limited to specific playback scenarios. platforms provide hardware HEIC encoding support on devices running or later, provided the underlying SoC includes compatible HEVC encoders. By 2025, graphics processing units have enhanced acceleration. GPUs, building on their hardware decoding introduced in prior architectures, offer full acceleration for processing in creative and rendering workflows, benefiting from the format's foundations for faster intra-frame decoding. Coverage of GPUs' HEIF support remains incomplete as of 2024, with driver updates focusing on broader media enhancements but lacking specific HEIF benchmarks in public documentation. Hardware decoding of HEIF formats significantly outperforms software alternatives, achieving up to 10 times faster processing speeds while reducing power consumption, particularly beneficial for battery-constrained mobile devices. This efficiency stems from dedicated silicon accelerators handling HEVC/AV1 operations, minimizing CPU load and enabling smoother real-time image handling compared to CPU-based software decoding.

Intellectual Property

Patent Licensing

The patent licensing for the High Efficiency Image File Format (HEIF) is primarily governed by the underlying codecs used in its profiles, with (HEVC, or H.265) forming the basis for key implementations and thus requiring access to HEVC essential patents. These patents are licensed through two main pools: HEVC Advance, established in 2015 to aggregate and offer fair, reasonable, and non-discriminatory terms for HEVC implementations, and the HEVC Patent Portfolio License originally managed by (now Via Licensing Alliance). To address fragmentation, licensors began contributing to joint pools around 2016, simplifying access to over 1,100 essential patent families worldwide. HEVC licensing fees typically include a per-device royalty of $0.20 after the first 100,000 units (which are ), plus potential content royalties for encoded media distributed commercially. Under the Via LA pool, the rate remains $0.20 per unit for volumes exceeding 100,000, with an annual cap of $25 million; new licenses after September 30, 2025, adjust to $0.30 in Region 1 (e.g., , ) and $0.20 in Region 2 (e.g., rest of world). HEVC Advance structures fees by device category (e.g., $0.20 for mobile devices, up to 1.00−1.00-2.00 for premium displays pre-2026) and region, with 50% discount in Region 2, annual caps up to $40 million, and a 25% increase for new licensees from January 1, 2026 (as of July 2025). In October 2025, Via LA settled disputes with over HEVC licensing. In November 2025, joined HEVC Advance as both licensor and licensee. Within HEIF, the HEIC profile—widely used for still images on Apple devices—relies on HEVC for intra-frame (still picture) coding and thus mandates an HEVC license, subjecting encoders, decoders, and content to the associated royalties. By contrast, the AVCI profile employs (AVC, or H.264) for compression, incurring lower fees of approximately $0.20 per unit after 100,000 free units via the AVC pool, with a $3.5 million annual cap—significantly less burdensome than HEVC due to fewer patents and established . A notable exception is the AVIF container within HEIF, which uses AV1 coding and operates under the royalty-free (AOMedia) Patent License 1.0, granting perpetual, worldwide, no-charge access to essential patents without enforcement obligations, provided licensees do not initiate offensive litigation. This structure avoids HEVC-style pools entirely, promoting broader adoption. As of 2025, adoption of royalty-free within HEIF has increased, particularly for web use, though HEVC-based HEIC remains prevalent in mobile devices due to licensing costs deterring some implementations. Several high-profile HEVC patent enforcement actions were resolved by 2023, including suits against in , where settlements facilitated licensing agreements and reduced ongoing disputes.

Implementation Considerations

Implementing HEIF requires consideration of open-source libraries for encoding and decoding, as well as integration with underlying codecs. The libheif library, an open-source implementation released in 2017, provides support for decoding and encoding HEIF files compliant with ISO/IEC 23008-12:2017, offering a C API suitable for integration into applications. For HEVC-based encoding within HEIF, libheif integrates with the library, which handles the HEVC compression, enabling efficient still image encoding while leveraging x265's optimization features. libheif has faced security vulnerabilities, including buffer overflows (e.g., CVE-2020-23109 in 2020 and CVE-2025-29482 in 2025), which have been addressed via patches, though ongoing vigilance is required. Best practices for HEIF deployment emphasize royalty avoidance and broad compatibility, particularly in web environments. Developers are advised to prioritize , a royalty-free alternative based on the codec within the HEIF container, to sidestep licensing fees associated with HEVC patents. For compatibility with legacy systems, implementations should include fallback mechanisms, such as embedding items within HEIF files to ensure display in environments lacking native HEIF support. Challenges in HEIF implementation include increased computational demands and potential vulnerabilities compared to simpler formats like . HEVC decoding in HEIF requires more resources due to its advanced compression algorithms, leading to higher decoder complexity and longer load times on resource-constrained devices. Regarding , 2023 audits revealed issues like use-after-free vulnerabilities in libraries such as libavif, though comprehensive public reports on full audits remain limited, underscoring the need for ongoing scanning. To ensure reliability, adherence to ISO is essential during development. The ISO/IEC 23008-12 standard includes test suites for validating HEIF compliance, covering aspects like file structure and codec integration. Profile selection plays a key role, with the 'hevc' recommended for still images to signal HEVC usage and maintain compatibility with main profile decoders. As of 2025, implementation advice leans toward prioritization for new projects due to its superior royalty-free status and growing ecosystem support, while using tools like FFmpeg for seamless conversion between HEIF and other formats. FFmpeg's built-in support facilitates batch conversions, such as from HEIF to , aiding migration workflows.

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