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Image file format
View on Wikipediafrom Wikipedia
 | This article possibly contains original research. (August 2025) |
An image file format is a file format for a digital image. There are many formats that can be used, such as JPEG, PNG, and GIF. Most formats up until 2022 were for storing 2D images, not 3D ones. The data stored in an image file format may be compressed or uncompressed. If the data is compressed, it may be done so using lossy compression or lossless compression. For graphic design applications, vector formats are often used. Some image file formats support transparency.
Raster formats are for 2D images. A 3D image can be represented within a 2D format, as in a stereogram or autostereogram, but this 3D image will not be a true light field, and thereby may cause the vergence-accommodation conflict.
Image files are composed of digital data in one of these formats so that the data can be displayed on a digital (computer) display or printed out using a printer. A common method for displaying digital image information has historically been rasterization.
Image file sizes
[edit]The size of raster image files is positively correlated with the number of pixels in the image and the color depth (bits per pixel). Images can be compressed in various ways, however. A compression algorithm stores either an exact representation or an approximation of the original image in a smaller number of bytes that can be expanded back to its uncompressed form with a corresponding decompression algorithm. Images with the same number of pixels and color depth can have very different compressed file sizes. Considering exactly the same compression, number of pixels, and color depth for two images, different graphical complexity of the original images may also result in very different file sizes after compression due to the nature of compression algorithms. With some compression formats, images that are less complex may result in smaller compressed file sizes. This characteristic sometimes results in a smaller file size for some lossless formats than lossy formats. For example, graphically simple images (i.e., images with large continuous regions like line art or animation sequences) may be losslessly compressed into a GIF or PNG format and result in a smaller file size than a lossy JPEG format.
For example, a 640 × 480 pixel image with 24-bit color would occupy almost a megabyte of space:
- 640 × 480 × 24 = 7,372,800 bits = 921,600 bytes = 900 KiB
With vector images, the file size increases only with the addition of more vectors.
Image file compression
[edit]There are two types of image file compression algorithms: lossless and lossy.
Lossless compression algorithms reduce file size while preserving a perfect copy of the original uncompressed image. Lossless compression generally, but not always, results in larger files than lossy compression. Lossless compression should be used to avoid accumulating stages of re-compression when editing images.
Lossy compression algorithms preserve a representation of the original uncompressed image that may appear to be a perfect copy, but is not a perfect copy. Often lossy compression is able to achieve smaller file sizes than lossless compression. Most lossy compression algorithms allow for variable compression that trades image quality for file size.
Major graphic file formats
[edit]
Including proprietary types, there are hundreds of image file types. The PNG, JPEG, and GIF formats are most often used to display images on the Internet. Some of these graphic formats are listed and briefly described below, separated into the two main families of graphics: raster and vector. Raster images are further divided into formats primarily aimed at (web) delivery (i.e., supporting relatively strong compression) versus formats primarily aimed at authoring or interchange (uncompressed or only relatively weak compression).
In addition to straight image formats, Metafile formats are portable formats that can include both raster and vector information. Examples are application-independent formats such as WMF and EMF. The metafile format is an intermediate format. Most applications open metafiles and then save them in their own native format. Page description language refers to formats used to describe the layout of a printed page containing text, objects, and images. Examples are PostScript, PDF, and PCL.
Raster formats (2D)
[edit]Delivery formats
[edit]JPEG
[edit]JPEG (Joint Photographic Experts Group) is a lossy compression method; JPEG-compressed images are usually stored in the JFIF (JPEG File Interchange Format) or the Exif (Exchangeable Image File Format) file format. The JPEG filename extension is JPG or JPEG. Nearly every digital camera can save images in the JPEG format, which supports eight-bit grayscale images and 24-bit color images (eight bits each for red, green, and blue). JPEG applies lossy compression to images, which can result in a significant reduction of the file size. Applications can determine the degree of compression to apply, and the amount of compression affects the visual quality of the result. When not too great, the compression does not noticeably affect or detract from the image's quality, but JPEG files suffer generational degradation when repeatedly edited and saved. (JPEG also provides lossless image storage, but the lossless version is not widely supported.)
GIF
[edit]The GIF (Graphics Interchange Format) is in normal use limited to an 8-bit palette, or 256 colors (while 24-bit color depth is technically possible).[1][2] GIF is most suitable for storing graphics with few colors, such as simple diagrams, shapes, logos, and cartoon-style images, as it uses LZW lossless compression, which is more effective when large areas have a single color and less effective for photographic or dithered images. Due to GIF's simplicity and age, it achieved almost universal software support. Due to its animation capabilities, it is still widely used to provide image animation effects, despite its low compression ratio compared to modern video formats.
PNG
[edit]The PNG (Portable Network Graphics) file format was created as a free, open-source alternative to GIF. The PNG file format supports 8-bit (256 colors) paletted images (with optional transparency for all palette colors) and 24-bit truecolor (16 million colors) or 48-bit truecolor with and without an alpha channel – while GIF supports only 8-bit palettes with a single transparent color.
Compared to JPEG, PNG excels when the image has large, uniformly colored areas. Even for photographs – where JPEG is often the choice for final distribution since its lossy compression typically yields smaller file sizes – PNG is still well-suited to storing images during the editing process because of its lossless compression.
PNG provides a patent-free replacement for GIF (though GIF is itself now patent-free) and can also replace many common uses of TIFF. Indexed-color, grayscale, and truecolor images are supported, plus an optional alpha channel. The Adam7 interlacing allows an early preview, even when only a small percentage of the image data has been transmitted—useful in online viewing applications like web browsers. PNG can store gamma and chromaticity data, as well as ICC profiles, for accurate color matching on heterogeneous platforms.
Animated formats derived from PNG are MNG and APNG, which is backwards compatible with PNG and supported by most browsers.
JPEG 2000
[edit]JPEG 2000 is a compression standard enabling both lossless and lossy storage. The compression methods used are different from the ones in standard JFIF/JPEG; they improve quality and compression ratios, but also require more computational power to process. JPEG 2000 also adds features that are missing in JPEG. It is not nearly as common as JPEG but it is used currently in professional movie editing and distribution (some digital cinemas, for example, use JPEG 2000 for individual movie frames).
WebP
[edit]WebP is an open image format released in 2010 that uses both lossless and lossy compression. It was designed by Google to reduce image file size to speed up web page loading: its principal purpose is to supersede JPEG as the primary format for photographs on the web. WebP is based on VP8's intra-frame coding and uses a container based on RIFF.
In 2011,[3] Google added an "Extended File Format" allowing WebP support for animation, ICC profile, XMP and Exif metadata, and tiling.
The support for animation allowed for converting older animated GIFs to animated WebP.
The WebP container (i.e., RIFF container for WebP) allows feature support over and above the basic use case of WebP (i.e., a file containing a single image encoded as a VP8 key frame). The WebP container provides additional support for:
- Lossless compression – An image can be losslessly compressed, using the WebP Lossless Format.
- Metadata – An image may have metadata stored in EXIF or XMP formats.
- Transparency – An image may have transparency, i.e., an alpha channel.
- Color Profile – An image may have an embedded ICC profile as described by the International Color Consortium.
- Animation – An image may have multiple frames with pauses between them, making it an animation.[4]
HDR raster formats
[edit]Most typical raster formats cannot store HDR data (32 bit floating point values per pixel component), which is why some relatively old or complex formats are still predominant here, and worth mentioning separately. Newer alternatives are showing up, though. RGBE is the format for HDR images originating from Radiance and also supported by Adobe Photoshop. JPEG-HDR is a file format from Dolby Labs similar to RGBE encoding, standardized as JPEG XT Part 2.
JPEG XT Part 7 includes support for encoding floating point HDR images in the base 8-bit JPEG file using enhancement layers encoded with four profiles (A-D); Profile A is based on the RGBE format and Profile B on the XDepth format from Trellis Management.
HEIF
[edit]The High Efficiency Image File Format (HEIF) is an image container format that was standardized by MPEG on the basis of the ISO base media file format. While HEIF can be used with any image compression format, the HEIF standard specifies the storage of HEVC intra-coded images and HEVC-coded image sequences taking advantage of inter-picture prediction.
AVIF
[edit]AVIF is an image container, that is used to store AV1 encoded images. It was created by Alliance for open media (AOMedia) and is completely open source and royalty-free. It supports encoding images in 8, 10 and 12-bit depth.
JPEG XL
[edit]JPEG XL is a royalty-free raster-graphics file format that supports both lossy and lossless compression. It supports reversible recompression of existing JPEG files, as well as high-precision HDR (up to 32-bit floating point values per pixel component). It is designed to be usable for both delivery and authoring use cases.
Authoring and interchange formats
[edit]TIFF
[edit]The TIFF (Tag Image File Format) format is a flexible format usually using either the TIFF or TIF filename extension. The tag structure was designed to be easily extendible, and many vendors have introduced proprietary special-purpose tags – with the result that no one reader handles every flavor of TIFF file. TIFFs can be lossy or lossless, depending on the technique chosen for storing the pixel data. Some offer relatively good lossless compression for bi-level (black&white) images. Some digital cameras can save images in TIFF format, using the LZW compression algorithm for lossless storage. TIFF image format is not widely supported by web browsers, but it remains widely accepted as a photograph file standard in the printing business. TIFF can handle device-specific color spaces, such as the CMYK defined by a particular set of printing press inks. OCR (Optical Character Recognition) software packages commonly generate some form of TIFF image (often monochromatic) for scanned text pages.
BMP
[edit]The BMP file format (Windows bitmap) is a raster-based, device-independent file type designed in the early days of computer graphics. It handles graphic files within the Microsoft Windows OS. Typically, BMP files are uncompressed and therefore large and lossless; their advantage is their simple structure and wide acceptance in Windows programs.
PPM, PGM, PBM, and PNM
[edit]Netpbm format is a family including the portable pixmap file format (PPM), the portable graymap file format (PGM), and the portable bitmap file format (PBM). These are either pure ASCII files or raw binary files with an ASCII header that provide very basic functionality and serve as a lowest common denominator for converting pixmap, graymap, or bitmap files between different platforms. Several applications refer to them collectively as PNM (Portable Any Map).
Container formats of raster graphics editors
[edit]These image formats contain various images, layers and objects, out of which the final image is to be composed by raster graphics editors:
- AFPhoto (Affinity Photo Document)
- CD5 (Chasys Draw Image)
- CLIP (Clip Studio Paint)
- CPT (Corel Photo Paint)
- KRA (Krita)
- MDP (Medibang and FireAlpaca)[5]
- PDN (Paint Dot Net)
- PLD (PhotoLine Document)
- PSD (Adobe PhotoShop Document)
- PSP (Corel Paint Shop Pro)
- SAI (Paint Tool SAI)
- XCF (eXperimental Computing Facility format)—native GIMP format
Other raster formats
[edit]- BPG (Better Portable Graphics)—an image format from 2014. Its purpose is to replace JPEG when quality or file size is an issue. To that end, it features a high data compression ratio, based on a subset of the HEVC video compression standard, including lossless compression. In addition, it supports various meta data (such as EXIF).
- DEEP—IFF-style format used by TVPaint
- DRW (Drawn File)
- ECW (Enhanced Compression Wavelet)
- FITS (Flexible Image Transport System)
- FLIF (Free Lossless Image Format)—a discontinued lossless image format which claims to outperform PNG, lossless WebP, lossless BPG and lossless JPEG 2000 in terms of compression ratio. It uses the MANIAC (Meta-Adaptive Near-zero Integer Arithmetic Coding) entropy encoding algorithm, a variant of the CABAC (context-adaptive binary arithmetic coding) entropy encoding algorithm.
- ICO—container for one or more icons (subsets of BMP and/or PNG)
- ILBM—IFF-style format for up to 32 bit in planar representation, plus optional 64 bit extensions
- IMG (ERDAS IMAGINE Image)
- IMG (Graphics Environment Manager (GEM) image file)—planar, run-length encoded
- JPEG XR—JPEG standard based on Microsoft HD Photo
- Nrrd (Nearly raw raster data)
- PAM (Portable Arbitrary Map)—late addition to the Netpbm family
- PCX (PiCture eXchange)—obsolete
- PGF (Progressive Graphics File)
- SGI (Silicon Graphics Image)—native raster graphics file format for Silicon Graphics workstations
- SID (multiresolution seamless image database, MrSID)
- Sun Raster—obsolete
- TGA (TARGA)—obsolete
- VICAR file format—NASA/JPL image transport format
- XISF (Extensible Image Serialization Format)[6]
Vector formats
[edit]As opposed to the raster image formats above (where the data describes the characteristics of each individual pixel), vector image formats contain a geometric description which can be rendered smoothly at any desired display size.
At some point, all vector graphics must be rasterized in order to be displayed on digital monitors. Vector images may also be displayed with analog CRT technology such as that used in some electronic test equipment, medical monitors, radar displays, laser shows and early video games. Plotters are printers that use vector data rather than pixel data to draw graphics.
CGM
[edit]CGM (Computer Graphics Metafile) is a file format for 2D vector graphics, raster graphics, and text, and is defined by ISO/IEC 8632. All graphical elements can be specified in a textual source file that can be compiled into a binary file or one of two text representations. CGM provides a means of graphics data interchange for computer representation of 2D graphical information independent from any particular application, system, platform, or device. It has been adopted to some extent in the areas of technical illustration and professional design, but has largely been superseded by formats such as SVG and DXF.
Gerber format (RS-274X)
[edit]The Gerber format (aka Extended Gerber, RS-274X) is a 2D bi-level image description format developed by Ucamco. It is the de facto standard format for printed circuit board or PCB software.[7]
SVG
[edit]SVG (Scalable Vector Graphics) is an open standard created and developed by the World Wide Web Consortium to address the need (and attempts of several corporations) for a versatile, scriptable and all-purpose vector format for the web and otherwise. The SVG format does not have a compression scheme of its own, but due to the textual nature of XML, an SVG graphic can be compressed using a program such as gzip. Because of its scripting potential, SVG is a key component in web applications: interactive web pages that look and act like applications.
Other 2D vector formats
[edit]- AFDesign (Affinity Designer document)
- AI (Adobe Illustrator Artwork)— proprietary file format developed by Adobe Systems
- CDR—proprietary format for CorelDRAW vector graphics editor
- !DRAW—a native vector graphic format (in several backward compatible versions) for the RISC-OS computer system begun by Acorn in the mid-1980s and still present on that platform today
- DrawingML—used in Office Open XML documents
- GEM—metafiles interpreted and written by the Graphics Environment Manager VDI subsystem
- GLE (Graphics Layout Engine)—graphics scripting language
- HP-GL (Hewlett-Packard Graphics Language)—introduced on Hewlett-Packard plotters, but generalized into a printer language
- HVIF (Haiku Vector Icon Format)
- Lottie—format for vector graphics animation
- MathML (Mathematical Markup Language)—an application of XML for describing mathematical notations
- NAPLPS (North American Presentation Layer Protocol Syntax)
- ODG (OpenDocument Graphics)
- PGML (Precision Graphics Markup Language)—a W3C submission that was not adopted as a recommendation
- PSTricks and PGF/TikZ are languages for creating graphics in TeX documents
- QCC—used by Quilt Manager (by Quilt EZ) for designing quilts[8]
- ReGIS (Remote Graphic Instruction Set)—used by DEC computer terminals
- Remote imaging protocol—system for sending vector graphics over low-bandwidth links
- TinyVG—binary, simpler alternative to SVG[9]
- VML (Vector Markup Language)—obsolete XML-based format
- Xar—format used in vector applications from Xara
- XPS (XML Paper Specification)—page description language and a fixed-document format
3D vector formats
[edit] | This section may contain material unrelated to the topic of the article and should be moved to List of file formats#Computer-aided design instead. (May 2021) |
- AMF – Additive Manufacturing File Format
- Asymptote – A language that lifts TeX to 3D.
- .blend – Blender
- COLLADA
- DGN
- .dwf
- .dwg
- .dxf
- eDrawings[10]
- .flt – OpenFlight
- FVRML – and FX3D, function-based extensions of VRML and X3D
- glTF – 3D asset delivery format (.glb binary version)
- HSF[11]
- IGES
- JT
- .MA (Maya ASCII format)[12]
- .MB (Maya Binary format)[13]
- .OBJ Wavefront
- OpenGEX – Open Game Engine Exchange
- PLY
- POV-Ray scene description language
- PRC
- STEP
- SKP
- STL – A stereolithography format
- U3D – Universal 3D file format
- VRML – Virtual Reality Modeling Language
- XAML
- XGL[14]
- XVL
- xVRML
- X3D
- 3DF[15]
- .3DM[16]
- .3ds – Autodesk 3D Studio
- 3DXML
- X3D – Vector format used in 3D applications from Xara
Compound formats
[edit]These are formats containing both pixel and vector data, possible other data, e.g. the interactive features of PDF.
- EPS (Encapsulated PostScript)
- MODCA (Mixed Object:Document Content Architecture)
- PDF (Portable Document Format)
- PostScript, a page description language with strong graphics capabilities
- PICT (Classic Macintosh QuickDraw file)
- WMF / EMF (Windows Metafile / Enhanced Metafile)
- SWF (Shockwave Flash)
- XAML User interface language using vector graphics for images.
Stereo formats
[edit]- MPO The Multi Picture Object (.mpo) format consists of multiple JPEG images (Camera & Imaging Products Association) (CIPA).
- PNS The PNG Stereo (.pns) format consists of a side-by-side image based on PNG (Portable Network Graphics).
- JPS The JPEG Stereo (.jps) format consists of a side-by-side image format based on JPEG.
See also
[edit]- Display resolution – Width and height of a display in pixels
- Display aspect ratio – Ratio between a display's width and height
- Display resolution standards – Commonly used display resolutions
- List of common display resolutions
References
[edit]- ^ Andreas Kleinert (2007). "GIF 24 Bit (truecolor) extensions". Archived from the original on 16 March 2012. Retrieved 23 March 2012.
- ^ Philip Howard. "True-Color GIF Example". Archived from the original on 22 February 2015. Retrieved 23 March 2012.
- ^ Arora, Vikas (3 October 2011). "WebP-Mux (RIFF based container) framework". Google Groups. Archived from the original on 13 March 2013. Retrieved 18 November 2011.
- ^ "WebP Container Specification". Google Developers. Archived from the original on 18 May 2022. Retrieved 4 April 2020.
Text was copied from this source, which is available under a Creative Commons Attribution 4.0 International License Archived 2017-10-16 at the Wayback Machine.
- ^ ".MDP File Extension". Retrieved 2025-05-01.
- ^ "XISF". Retrieved 2025-05-01.
- ^ "Gerber File Format Specification". Ucamco. Archived from the original on 2016-03-31. Retrieved 2016-03-21.
- ^ ".QCC File Extension". Retrieved 2025-05-01.
- ^ "TinyVG". Archived from the original on 2023-01-09. Retrieved 2023-01-31.
- ^ "Frequently Asked Questions". 15 January 2019. Retrieved 2025-05-01.
- ^ ".HSF File Extension". Retrieved 2025-05-01.
- ^ "What is an MA file?". 11 October 2019. Retrieved 2025-05-01.
- ^ "What is an MB file?". 7 March 2021. Retrieved 2025-05-01.
- ^ "XGL Guide for CAD Interoperability: Optimal Visualization and Conversion of 3D Models". Retrieved 2025-05-01.
- ^ ".3DF File Extension". Retrieved 2025-05-01.
- ^ "3D Model File Format Family". Library of Congress. Retrieved 2025-05-01.
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Image file format
View on Grokipediafrom Grokipedia
Introduction and History
Definition and Purpose
An image file format is a standardized method for encoding and organizing digital image data, typically consisting of a header that identifies the format and includes essential metadata such as image dimensions and color information, followed by the core image data—either a pixel array for raster images or mathematical path descriptions for vector images—and often concluding with a footer containing end markers or checksums to verify data integrity.[7][8][9][10] The primary purpose of these formats is to facilitate the efficient storage, display, editing, and transmission of visual information across diverse hardware platforms and software applications, ensuring compatibility and preserving image quality where possible.[11][12] For example, they support use cases such as rendering images on websites for quick loading, producing high-fidelity prints in professional workflows, and maintaining archival copies for long-term preservation without degradation.[7][13] Image file formats can be broadly categorized into proprietary ones, such as Adobe's PSD (Photoshop Document), which are designed for specific software ecosystems and retain advanced editing features like layers, and open standards like PNG (Portable Network Graphics), governed by international specifications to promote widespread interoperability.[14][15] This distinction influences their adoption: proprietary formats excel in specialized creative tools but limit cross-platform use, while open formats enable seamless interchange in open-source and web environments.[16][17]Historical Development
The evolution of image file formats traces back to the 1970s, when bitmap graphics emerged as a foundational technology for digital imaging. Early systems like the Xerox Alto, introduced in 1973 by Xerox PARC, utilized bitmapped displays to render graphical interfaces, storing images as simple arrays of pixels in memory, which laid the groundwork for raster-based formats.[18] In the late 1970s and early 1980s, personal computing spurred proprietary bitmap formats, such as Apple's MacPaint format (PNTG), released in 1984 alongside the original Macintosh, which supported monochrome raster images of 576 × 720 pixels for basic drawing and editing.[19] The 1980s marked significant milestones in standardization for broader interchange. Aldus Corporation developed the Tagged Image File Format (TIFF) in 1986 to facilitate high-quality image exchange in desktop publishing workflows, supporting both lossless and multi-page storage.[20] Shortly after, CompuServe introduced the Graphics Interchange Format (GIF) in 1987 as a compact, color-supporting raster format optimized for online transmission, employing LZW compression to reduce file sizes for early internet use.[21] The 1990s saw explosive growth driven by digital photography and web expansion. The Joint Photographic Experts Group (JPEG), standardized in 1992 by ITU-T and ISO/IEC JTC 1/SC 29, introduced lossy compression using discrete cosine transform (DCT) techniques, enabling efficient storage of photographic images and becoming ubiquitous for consumer media.[20] In response to GIF's patent issues, the World Wide Web Consortium (W3C) endorsed the Portable Network Graphics (PNG) format in 1996 as a patent-free alternative, utilizing DEFLATE compression for lossless raster images suitable for web graphics.[22] Entering the 2000s and 2010s, vector formats gained prominence alongside raster advancements for scalable web content. The W3C released Scalable Vector Graphics (SVG) in 1999 as an XML-based standard for 2D vector images, enabling resolution-independent rendering and interactivity in browsers.[23] Google launched WebP in 2010, a raster format based on the VP8 video codec, to enhance web performance with superior compression for both lossy and lossless images.[24] The Moving Picture Experts Group (MPEG) finalized the High Efficiency Image File Format (HEIF) in 2015, leveraging HEVC compression for multi-image containers, which gained traction in mobile devices for efficient photo storage.[25] In the 2020s, formats emphasized royalty-free efficiency amid rising bandwidth demands. The Alliance for Open Media (AOMedia) released AVIF in 2019, building on the AV1 video codec for high-fidelity raster compression, achieving broad browser support by 2025 for web and app deployment. The JPEG Committee standardized JPEG XL in 2022, integrating lossy and lossless modes with animation capabilities to succeed legacy JPEG, though its adoption by 2025 remains niche, primarily in professional software and select platforms like iOS.[26] Standardization efforts have been pivotal, with organizations like ISO/IEC JTC 1/SC 29 overseeing JPEG developments, W3C championing open web formats such as PNG and SVG, and the Internet Engineering Task Force (IETF) formalizing others via RFCs, including WebP in 2024.[27][28][29] Overall, the field has shifted from proprietary, hardware-specific formats to open, royalty-free standards, prioritizing web efficiency, mobile optimization, and seamless cross-platform compatibility.Core Concepts
File Sizes and Storage Requirements
The size of an image file is fundamentally determined by the amount of data required to represent its pixels, plus any additional overhead from file structure elements such as headers and metadata. For uncompressed raster images, the core pixel data size is calculated based on the image's dimensions and color representation. This provides a baseline for understanding storage needs before considering any reduction techniques.[30] The formula for the uncompressed raster image size in bytes is: Here, bits per pixel accounts for the color depth and number of channels; for example, a standard RGB image uses 24 bits per pixel (8 bits each for red, green, and blue channels). Applying this to a full HD image of 1920 × 1080 pixels with 24-bit RGB yields (1920 × 1080 × 24) / 8 = 6,220,800 bytes, or approximately 6.2 MB for the pixel data alone, excluding overhead. Headers and metadata typically add a small fixed amount, often tens to hundreds of bytes, depending on the format.[31][32][30] Several factors influence the overall file size. Resolution, defined by width and height in pixels, directly scales the total pixel count and thus the data volume. Color depth varies from 1 bit for monochrome images, which support only black and white, to 16 bits or more per channel for high dynamic range (HDR) images that capture a wider tonal range. The number of channels also matters: RGB requires three channels, while RGBA adds a fourth for transparency (alpha), increasing bits per pixel to 32 for 8-bit-per-channel depth. Compression ratios further affect final sizes by reducing redundancy, though the uncompressed baseline remains key for planning.[33][31] These sizes have significant implications for storage and transmission. Larger files increase storage costs on devices and servers, where high-resolution images can quickly consume gigabytes; for instance, a single 4K uncompressed RGB image exceeds 24 MB. In terms of bandwidth, transmitting such files over networks demands more data transfer, potentially slowing load times—ideal web images are often kept under 100 KB to ensure fast rendering on varied connections and devices. This creates trade-offs between image quality (higher resolution and depth) and practicality, such as fitting within mobile storage limits or optimizing for low-bandwidth environments.[34][35] File sizes are measured in bytes (B), with kilobytes (KB) equaling 1,024 bytes and megabytes (MB) equaling 1,048,576 bytes, reflecting binary storage conventions. Tools like online image file size calculators allow users to estimate uncompressed sizes by inputting dimensions, bit depth, and channels, aiding in preemptive planning for projects.[31]Compression Techniques
Image compression techniques aim to reduce the size of image data while preserving essential visual information, enabling efficient storage and transmission. These methods exploit redundancies in image data, such as spatial correlations between pixels or statistical patterns in pixel values. Broadly, compression is categorized into lossless and lossy types, with the choice depending on whether exact reconstruction of the original image is required.[36] Lossless compression ensures perfect reversibility, reconstructing the original image without any data loss, making it suitable for applications like medical imaging or archiving where fidelity is critical. It achieves reductions typically between 20% and 50% by encoding redundancies without discarding information. Key algorithms include Run-Length Encoding (RLE), which replaces sequences of identical pixels with a single value and a count of repetitions, effective for images with large uniform areas like icons or scanned text. Huffman coding, introduced in 1952, assigns variable-length codes to symbols based on their frequency of occurrence, using shorter codes for more frequent symbols to minimize average code length.[36][37] The Deflate algorithm, combining LZ77 dictionary-based compression with Huffman coding, is widely used in formats like PNG for its balance of speed and efficiency.[38] Lossy compression, in contrast, discards less perceptually important data to achieve higher ratios, often 10:1 or more, at the cost of irreversible alterations, ideal for web images or photography where minor quality loss is tolerable. Transform-based methods like the Discrete Cosine Transform (DCT) in JPEG convert spatial data into frequency components, concentrating energy in low frequencies for selective quantization. The forward 2D DCT for an 8×8 block is given by: where and for , followed by quantization that rounds coefficients to integers, discarding high-frequency details.[39] Wavelet transforms, as in JPEG 2000, decompose images into multi-resolution subbands using filters, enabling scalable compression with better preservation of edges compared to DCT. Entropy coding further refines both lossless and lossy schemes by assigning codes based on probability models. Huffman coding, as noted, uses prefix-free trees for integer symbols, while arithmetic coding achieves finer granularity by encoding entire sequences into a single fractional number between 0 and 1, potentially using fewer than one bit per symbol on average.[37][40] Compression effectiveness is quantified by the compression ratio, defined as the ratio of the original file size to the compressed size, with higher values indicating better efficiency. For lossy methods, quality is assessed using Peak Signal-to-Noise Ratio (PSNR), calculated as , where is the maximum pixel value and MSE is the mean squared error between original and reconstructed images; values above 30 dB typically indicate good perceptual quality.[41] Hybrid approaches combine techniques for versatility, such as progressive encoding in JPEG, which layers data from low to high frequencies for gradual refinement during decoding, improving perceived loading speed. JPEG XR employs overlapping blocks and dual transforms (integer DCT and wavelet-like) to support both lossless and lossy modes with reduced artifacts. Lossless methods preserve all data but yield modest ratios, while lossy enables dramatic size reductions for photographic content, though at the risk of visible degradation. Common lossy artifacts include blocking, visible grid-like boundaries from independent 8×8 DCT processing, and ringing, oscillatory distortions around edges due to quantization of high frequencies. Mitigation strategies involve optimized quantization tables to smooth transitions and overlap transforms in formats like JPEG XR, which reduce boundary discontinuities without full post-processing.[42][43][44]Color Models and Metadata
Image file formats represent colors using various models to suit different display, printing, and processing needs. The RGB color model, which is additive and combines red, green, and blue light to produce a wide range of colors, serves as the foundation for most digital displays and image formats. The sRGB standard, defined by the International Electrotechnical Commission (IEC), provides a specific RGB color space optimized for typical consumer-grade monitors and web content, ensuring consistent color reproduction across devices. In contrast, the CMYK model operates on a subtractive principle, using cyan, magenta, yellow, and black inks to absorb light for printing applications, making it essential for formats targeted at professional printing workflows. For efficient compression in formats like JPEG, the YCbCr model separates luminance (Y) from chrominance (Cb and Cr) components, leveraging human visual sensitivity to brightness over color details to reduce file sizes without significant perceptual loss. Conversions between these models, such as from RGB to CMYK, often involve linear matrix transformations to approximate the target space, though they can introduce gamut mismatches requiring clipping or perceptual adjustments. Bit depth determines the precision of color representation per channel, with 8-bit depth offering 256 levels per RGB channel for a total of approximately 16.7 million colors, sufficient for standard web and print images but prone to banding in gradients. Higher 16-bit depths enable high dynamic range (HDR) imaging, supporting up to 65,536 levels per channel for smoother transitions and greater detail in shadows and highlights, commonly used in professional photography and editing formats. Color gamuts extend beyond sRGB to encompass wider ranges; Adobe RGB covers about 50% more colors for enhanced print fidelity, while ProPhoto RGB offers an expansive gamut suitable for archival and post-production work to minimize clipping during editing. To ensure device-independent color rendering, many image formats embed ICC profiles developed by the International Color Consortium (ICC). These profiles describe the color characteristics of input, display, or output devices through a structured file format including a header for version and device class information, tag tables for color transformations, and curves or lookup tables for tone reproduction. By embedding such profiles, formats like TIFF and JPEG allow applications to apply accurate color conversions, preserving intended appearance across diverse hardware. Metadata in image files provides auxiliary information beyond pixel data, enhancing management, searchability, and interoperability. The Exchangeable Image File Format (EXIF), standardized by the Camera & Imaging Products Association (CIPA), embeds camera-specific details such as aperture, shutter speed, ISO sensitivity, and capture date, primarily in JPEG and TIFF files from digital cameras. The Extensible Metadata Platform (XMP), developed by Adobe and based on XML, supports a broader schema including rights management, keywords, and integration with IPTC data for editorial use, allowing embedding in formats like PDF and PSD. IPTC metadata, originating from the International Press Telecommunications Council, adds fields for captions, copyrights, and creator information, often carried within XMP packets. GPS tags, commonly included via EXIF or XMP, record geolocation data from device sensors, enabling applications like photo mapping but raising privacy concerns as embedded coordinates can reveal personal locations without user awareness. Tools like ExifTool facilitate viewing, editing, and embedding metadata across formats, supporting batch operations for professionals. However, converting between image formats or editing operations can lead to metadata loss, as not all standards are universally supported, necessitating backups or explicit preservation during workflows.Raster Formats
Delivery and Web-Optimized Formats
Delivery and web-optimized raster formats prioritize small file sizes, broad browser compatibility, and fast loading to enhance user experience on websites and mobile applications. These formats balance compression efficiency with visual quality, supporting features like progressive loading and transparency where needed, while adhering to web standards for seamless integration. Common examples include JPEG for photographs, PNG for graphics, GIF for simple animations, and WebP as a versatile modern option. JPEG (Joint Photographic Experts Group) is a lossy compression format based on the discrete cosine transform (DCT) algorithm, widely used for photographic images due to its ability to achieve high compression ratios while maintaining acceptable quality.[43] It supports baseline mode for sequential decoding and progressive mode for gradual image refinement during loading, improving perceived performance on slow connections.[43] The standard file extension is .jpg, with the MIME type image/jpeg registered by IANA.[45] An extension, JPEG 2000, employs wavelet-based compression for better efficiency and lossless options but has seen limited adoption in web contexts due to compatibility issues and minimal browser support. PNG (Portable Network Graphics) provides lossless compression using the DEFLATE algorithm, making it suitable for images requiring exact reproduction, such as logos and illustrations, without artifacts from lossy methods.[28] It supports full alpha channel transparency for seamless overlays and optional interlacing (Adam7 algorithm) to display low-resolution previews early during download.[28] The file extension is .png, and the MIME type is image/png. PNG excels in web graphics where color fidelity and transparency are essential, though its files are larger than lossy alternatives for complex photos. GIF (Graphics Interchange Format) uses indexed color palettes limited to 256 colors per frame and LZW (Lempel-Ziv-Welch) lossless compression, originally developed for simple icons and line art. It uniquely supports animation through multiple frames with timing delays, enabling short looping sequences common in web memes and banners, though file sizes grow with frame count. Patents on LZW compression, held by Unisys (US expiration 2003; international 2004) and IBM (US 2006), have expired, resolving earlier licensing disputes and boosting adoption.[46] The extension is .gif, with MIME type image/gif. WebP, introduced by Google in 2010 and based on the VP8 video codec from WebM, offers both lossy and lossless compression modes, along with support for animation, alpha transparency, and progressive loading. It achieves 25-34% smaller file sizes than equivalent JPEG images at the same quality level.[47] Lossless WebP files are 26% smaller than PNG.[48] By November 2025, WebP enjoys near-universal browser support across Chrome, Firefox, Safari, and Edge, covering over 96% of global users.[49] The file extension is .webp, and the MIME type is image/webp. AVIF (AV1 Image File Format), built on the AV1 video codec, provides superior compression for web delivery with support for lossy/lossless modes, high dynamic range (HDR), and wide color gamuts, often yielding even smaller files than WebP for high-quality images. While browser support is strong in modern versions of major engines, it remains a transitional format with ongoing optimization for widespread use. To further optimize these formats for the web, tools like mozjpeg enhance JPEG compression by improving Huffman coding and quantization tables, potentially reducing file sizes by 20-30% without visible quality loss. Similarly, PNG optimizers apply advanced filtering and deflation, while WebP encoders benefit from quality tuning to balance speed and size.Authoring and Interchange Formats
Authoring and interchange formats for raster images are designed to facilitate editing, collaboration, and high-fidelity preservation in professional creative workflows, often incorporating features like layers, masks, and embedded metadata to maintain editability without loss of quality. These formats prioritize flexibility for tools such as photo editing software and digital asset management systems, contrasting with delivery formats by supporting complex structures rather than optimized viewing. Common examples include TIFF for versatile storage in printing and scanning applications, PSD as a proprietary editing format, RAW files from camera manufacturers for post-processing, PDF for embedding raster content in mixed documents, and open standards like OpenRaster for cross-application interchange.[50][51][52] The Tagged Image File Format (TIFF), developed in the 1980s by Aldus Corporation (now part of Adobe), serves as a robust container for raster images in professional environments, supporting both lossless and lossy compression methods such as LZW and ZIP to balance file size and quality. It accommodates multi-page documents, various color depths including 16-bit and 32-bit per channel, and extensions for layers and paths in tools like Adobe Photoshop, making it ideal for prepress workflows, scanning, and archiving where high resolution and metadata preservation are essential. TIFF files use the .tif or .tiff extension and the MIME type image/tiff, with widespread adoption due to its flexibility across platforms.[50][53] Adobe Photoshop's native format, PSD, is a proprietary raster format optimized for layered editing, storing non-destructive adjustments, masks, channels, and vector paths alongside pixel data to enable iterative creative processes. It supports high bit depths up to 32 bits per channel for extended dynamic range and color accuracy, but its closed specification and licensing restrictions limit broad interchange, confining primary use to Adobe ecosystems despite partial support in other software. PSD files bear the .psd extension and are essential for graphic designers maintaining complex compositions.[51][54] RAW formats capture unprocessed sensor data from digital cameras, providing maximum latitude for post-production adjustments like exposure and white balance, with embedded metadata such as lens information and camera settings. Canon's CR2 format, used in EOS cameras since 2004, is a TIFF-based structure holding uncompressed or lightly compressed Bayer-pattern data, enabling non-destructive editing while preserving the full 12- or 14-bit tonal range per channel; it uses the .cr2 extension and MIME type image/x-canon-cr2. Similarly, Nikon's NEF format for DSLR and mirrorless models stores raw sensor output with proprietary compression options, including metadata for noise reduction parameters, under the .nef extension, supporting bit depths up to 14 bits for enhanced detail recovery. These camera-specific formats demand specialized software for decoding due to proprietary elements.[55][56] PDF, standardized by ISO 32000, functions as an interchange format for documents containing embedded raster images, allowing high-fidelity transport of mixed content like scanned pages or graphics within a self-contained file. Raster elements in PDF are typically compressed using Flate (deflate) for lossless data or JPEG for lossy efficiency, supporting color spaces such as CMYK and RGB while embedding metadata; this makes it suitable for professional review and printing workflows where raster integrity must be maintained alongside text and vectors.[57] OpenRaster (.ora) addresses the need for an open interchange standard for layered raster images, packaging content in a ZIP archive with an XML manifest describing layers, blends, and opacity, alongside individual PNG files for each layer and a merged composite. Developed collaboratively for applications like GIMP and Inkscape, it promotes vendor-neutral editing workflows without proprietary lock-in, supporting features like layer groups and paths while ensuring backward compatibility through its baseline specification.[52]Legacy and Specialized Raster Formats
Legacy and specialized raster formats encompass older bitmap image standards that originated in the 1980s and 1990s, designed for simplicity and compatibility with early computing environments. These formats often rely on basic compression methods like run-length encoding (RLE) and palette-based color representation, making them suitable for resource-constrained systems but less efficient for modern high-resolution imaging. Despite their age, they remain relevant in niche contexts, such as operating system resources, legacy software compatibility, and portable image processing tools. The BMP (Bitmap) format, developed by Microsoft for Windows operating systems, stores raster images in an uncompressed manner or with optional RLE compression, lacking a standardized compression algorithm beyond basic techniques. It features a straightforward 14-byte file header followed by color table and pixel data, supporting up to 32 bits per pixel including alpha channels in later variants. BMP files use the .bmp extension and the MIME type image/bmp, and they are frequently utilized for simple graphics like desktop icons due to their native integration with Windows.[58][59] Similarly, the PCX format, introduced by ZSoft Corporation in the 1980s for its PC Paintbrush software, employs RLE compression and is primarily palette-based, limiting it to 256 colors or fewer in early versions. Originating as a standard for PC graphics in the MS-DOS era, PCX files use the .pcx extension and are commonly associated with the MIME type image/x-pcx, though not officially registered. Its structure includes a 128-byte header detailing image dimensions, encoding, and a color palette at the file's end, making it efficient for low-color environments but prone to limitations in true-color reproduction.[60][61] The TGA (Truevision Targa) format, created by Truevision Inc. for its graphics adapters, supports RLE compression, alpha channels for transparency, and even stereo image pairs, accommodating bit depths from 8 to 32 bits per pixel. Widely adopted in the 1990s for 3D rendering and video games due to its flexibility in handling uncompressed RGB data, TGA files use the .tga extension and the MIME type image/x-tga. The format's header spans 18 bytes, followed by optional extension and developer areas, enabling features like image origin specification that were advanced for its time.[62][63] Specialized variants include the ICO format for Windows icons, which bundles multiple bitmap images of varying sizes (e.g., 16x16 to 256x256 pixels) and color depths within a single file, using the .ico extension and MIME type image/x-icon. Closely related is the CUR format for mouse cursors, structured similarly to ICO but optimized for pointer graphics with a defined hotspot, employing the .cur extension and MIME type image/x-cur. For portable image manipulation in software tools, the Netpbm formats—PBM (portable bitmap for binary images), PGM (portable graymap for grayscale), and PPM (portable pixmap for color)—offer ASCII or binary encodings with minimal headers, using extensions .pbm, .pgm, and .ppm respectively, along with MIME types image/x-portable-bitmap, image/x-portable-graymap, and image/x-portable-pixmap. These formats prioritize ease of parsing over compression, supporting up to 24 bits per pixel in PPM.[64][65][66][67][68][69] In contemporary applications, these legacy formats persist in digital forensics and emulation efforts to access historical data. For instance, forensic analysts encounter BMP, PCX, and TGA files on legacy storage media during investigations, requiring specialized tools to extract and interpret them without alteration. Emulation environments recreate 1980s-1990s computing setups to render these formats accurately, preserving original visual fidelity for archival purposes. However, converting palette-based formats like PCX or early BMP to modern true-color standards often introduces challenges, such as color loss due to limited palette mappings or inadequate dithering, necessitating careful preservation strategies to avoid irreversible degradation.[70][71][72][73][74][75]Vector Formats
2D Vector Formats
2D vector formats store graphics as mathematical descriptions of shapes, paths, and fills rather than pixels, enabling infinite scalability without quality degradation. These formats are particularly suited for illustrations, logos, and diagrams where sharp edges and precise proportions are essential, as they define geometry using curves and lines that can be rendered at any resolution. Common elements include paths constructed from line segments and curves, along with attributes for strokes, fills, and transformations, allowing for compact representation of complex artwork. The Scalable Vector Graphics (SVG) format, developed as a W3C standard, is an XML-based language for describing two-dimensional vector graphics, supporting elements like paths, gradients, text, and animations via SMIL.[76] SVG files use the .svg extension and the MIME type image/svg+xml, and they are natively supported in web browsers for interactive and responsive designs without loss of fidelity upon scaling.[77] Encapsulated PostScript (EPS) is a file format based on the PostScript page description language, primarily used for high-quality printing, and it can encapsulate both vector data and embedded raster images within a single bounding box.[78] Developed by Adobe and processed via tools like Adobe Distiller, EPS files bear the .eps extension and the MIME type application/postscript, making them a staple for professional print workflows despite their larger file sizes compared to purely vector alternatives.[79] Other notable 2D vector formats include Adobe Illustrator's native AI format, which stores proprietary vector paths, shapes, and effects editable within Illustrator software.[80] Similarly, CorelDRAW's CDR format serves as the native container for vector-based drawings created in that application, supporting layers, effects, and precise path editing.[81] The Computer Graphics Metafile (CGM), an ISO standard, provides a platform-independent method for exchanging 2D vector and mixed vector/raster graphics, available in binary or cleartext encodings and often used for technical illustrations in engineering and documentation. At their core, 2D vector formats represent shapes through paths defined by sequences of commands, including straight lines and Bézier curves, where quadratic Bézier curves use three control points (start, end, and one tangent) and cubic variants employ four (start, two tangents, end) to smoothly interpolate curved segments. Fills and strokes apply colors or patterns to enclosed areas or path outlines, while transformations—such as scaling, rotation, and translation—are handled via affine matrices that modify coordinate systems without altering the underlying geometry. Key advantages of 2D vector formats include their resolution independence, allowing graphics to be rendered crisply at any size or DPI without pixelation or the need for multiple versions.[82] For text-based formats like SVG, additional efficiency comes from compression methods such as gzip, which can reduce file sizes by 50-80% while preserving editability and searchability.[83]3D Vector Formats
3D vector formats represent three-dimensional models through geometric primitives such as vertices, edges, and faces, enabling scalable descriptions of volumetric shapes without pixel-based rasterization. These formats typically store positional data for vertices in Cartesian coordinates (x, y, z), connectivity information for faces or polygons, and optional attributes like normals for surface orientation or materials for rendering properties. Unlike 2D vector formats, which confine data to planar graphics, 3D variants extend to full spatial representations suitable for complex modeling.[84] The core structure of these formats emphasizes vertices as fundamental points defined by floating-point coordinates, often in a right-handed coordinate system where units are application-dependent (e.g., meters or arbitrary). Faces connect these vertices via indices, forming polygons like triangles or quads, while normals—unit vectors perpendicular to surfaces—aid in lighting calculations. Materials, when supported, may reference external files or embed basic properties like diffuse color, but advanced textures are not natively included in simpler formats. Export and import processes frequently encounter challenges, such as unit scale mismatches (e.g., converting between inches and millimeters) or coordinate system orientations, leading to potential distortions or data loss during interoperability.[85] The Wavefront OBJ format, originally developed by Wavefront Technologies in the late 1980s, is a straightforward text-based standard for exporting 3D geometry from modeling software. It defines vertices with thev x y z syntax, texture coordinates via vt u v [w], vertex normals using vn x y z, and faces through f v1[/vt1][/vn1] v2[/vt2][/vn2] ..., supporting polygons beyond triangles. Materials are handled separately in companion .mtl files referenced by mtllib, containing properties like illumination models and colors, though OBJ itself lacks native texture mapping. Files use the .obj extension and are widely supported for interchange due to their simplicity, though they omit scene hierarchies or animations.[84]
STL, or Stereolithography format, was introduced in 1987 by 3D Systems for rapid prototyping and remains a de facto standard for 3D printing. It exclusively represents surfaces as triangular meshes, with no support for colors, textures, or higher-order surfaces, focusing solely on boundary geometry. In ASCII mode, files begin with solid name, followed by facet normal nx ny nz, outer loop with three vertex x y z lines, and end with endfacet and endsolid; binary variants pack data more efficiently with a 80-byte header, a 32-bit triangle count, and 50 bytes per triangle (normal as three floats, vertices as nine floats, and a 16-bit attribute). The .stl extension is conventional, and MIME type is model/stl, but challenges arise from its lack of scale information, often requiring manual unit adjustments during import.[86][87]
The Polygon File Format (PLY), originating from Stanford University in 1994, offers flexibility through a header that declares elements like vertices and faces, along with their properties (e.g., scalar floats for coordinates or list types for indices). The header specifies ASCII or binary encoding, followed by data sections: vertices as sequential (x, y, z) tuples, and faces as tuples starting with polygon size (e.g., 3 i1 i2 i3 for a triangle). Optional elements include edges, colors, or confidence values from scanning, making it suitable for diverse data sources. Files end in .ply and support applications from scanned point clouds to algorithmic meshes, though binary variants enhance loading speed for large models.[88][89]
VRML (Virtual Reality Modeling Language) and its successor X3D provide ISO-standardized scene graph representations for interactive 3D content, with VRML 2.0 (ISO/IEC 14772:1997) introducing nodes for geometry, lighting, and viewpoints, while X3D (ISO/IEC 19775) adds XML encoding alongside classic VRML syntax. Both use vertices for shapes like IndexedFaceSet (with coordIndex for faces) and support normals, materials via Appearance nodes (e.g., diffuseColor), and environmental lighting, enabling hierarchical scenes. Files typically use .wrl for VRML and .x3d for X3D, facilitating web-based delivery since the 1990s. These formats excel in describing complete environments rather than isolated meshes.[90][91]
These formats find primary use in computer-aided design (CAD) for precise engineering models, gaming for asset pipelines where scalability aids level design, and virtual reality (VR) for immersive environments requiring efficient geometry loading. Interoperability remains a key hurdle, as varying support for attributes like normals can degrade rendering fidelity during transfers between tools, often necessitating converters to preserve coordinate integrity and scale.[85]