JPEG XR

JPEG XR[4] (JPEG extended range[5]) is a still-image compression standard and file format for continuous tone photographic images, based on technology originally developed and patented by Microsoft under the name HD Photo (formerly Windows Media Photo).[6] It supports both lossy and lossless compression, and is the preferred image format for Ecma-388 Open XML Paper Specification documents.

Support for the format is available in Adobe Flash Player 11.0, Adobe AIR 3.0, Sumatra PDF 2.1, Windows Imaging Component, .NET Framework 3.0, Windows Vista, Windows 7, Windows 8, Internet Explorer 9, Internet Explorer 10, Internet Explorer 11, Pale Moon 27.2.[7][8][9] As of August 2014, there were still no cameras that shoot photos in the JPEG XR (.JXR) format.

JPEG XR
Filename extension
Internet media type
  • image/vnd.ms-photo
  • image/jxr[3]
Developed byMicrosoft, ITU-T, ISO/IEC
Initial release14 April 2009
Latest release
01/2012 (ITU-T); 2012 edition (ISO/IEC)
(January 2012)
Type of formatGraphics file format
Contained byTIFF
StandardITU-T Rec. T.832 (01/2012),
ISO/IEC 29199-2:2012
Open format?Yes (New BSD license)
WebsiteITU-T T.832 (01/2012),
ISO/IEC 29199-2: 2012

History

Microsoft first announced Windows Media Photo at WinHEC 2006,[10] and then renamed it to HD Photo in November of that year. In July 2007, the Joint Photographic Experts Group and Microsoft announced HD Photo to be under consideration to become a JPEG standard known as JPEG XR.[11][12] On 16 March 2009, JPEG XR was given final approval as ITU-T Recommendation T.832 and starting in April 2009, it became available from the ITU-T in "pre-published" form.[1] On 19 June 2009, it passed an ISO/IEC Final Draft International Standard (FDIS) ballot, resulting in final approval as International Standard ISO/IEC 29199-2.[13][14] The ITU-T updated its publication with a corrigendum approved in December 2009,[1] and ISO/IEC issued a new edition with similar corrections on 30 September 2010.[15]

In 2010, after completion of the image coding specification, the ITU-T and ISO/IEC also published a motion format specification (ITU-T T.833 | ISO/IEC 29199-3), a conformance test set (ITU-T T.834 | ISO/IEC 29199-4), and reference software (ITU-T T.835 | ISO/IEC 29199-5) for JPEG XR. In 2011, they published a technical report describing the workflow architecture for the use of JPEG XR images in applications (ITU-T T.Sup2 | ISO/IEC TR 29199-1).

Description

Capabilities

JPEG XR is an image file format that offers several key improvements over JPEG, including:[16]

Better compression
JPEG XR file format supports higher compression ratios in comparison to JPEG for encoding an image with equivalent quality.
Lossless compression
JPEG XR also supports lossless compression. The signal processing steps in JPEG XR are the same for both lossless and lossy coding. This makes the lossless mode simple to support and enables the "trimming" of some bits from a lossless compressed image to produce a lossy compressed image.
Tile structure support
A JPEG XR coded image can be segmented into tile regions. The data for each region can be decoded separately. This enables rapid access to parts of an image without needing to decode the entire image. When a type of tiling referred to as "soft tiling" is used, the tile region structuring can be changed without fully decoding the image and without introducing additional distortion.
Support for more color accuracy
JPEG XR supports a wide variety of image color representations in addition to the conventional 8-bit-per-sample YUV (formally YCbCr) 4:2:0 encoding that is typically used for the original JPEG standard.
For support of images using an RGB color space, JPEG XR includes an internal conversion to the YCgCo color space, and supports a variety of bit depth and color representation packing schemes. These can be used with and without an accompanying alpha channel for shape masking and semi-transparency support, and some of them have much higher precision than what has typically been used for image coding. They include:
  • Low bit-depth packings of RGB into 16 bits per pixel using 5 bits for each channel or 5 bits for red and blue and 6 bits for green
  • 8 bits per component (sometimes called true color) packed into 24 or 32 bits per pixel
  • 10 bits per component in a 32 bit packed representation (one of several higher-precision varieties of color representation known as deep color)
  • 16 bits per component as integers, fixed-point numbers, or half-precision floating-point numbers packed into 48 or 64 bits
  • 32 bits per component as fixed-point numbers or full-precision floating point numbers packed into 96 or 128 bits (for which lossless coding is not supported due to the excessively high precision)
JPEG XR also supports 16-bit per component (64-bit per pixel) integer CMYK color model.[17]
16-bit and 32-bit fixed point color component codings are also supported in JPEG XR. In such encodings, the most-significant 4 bits of each color channel are treated as providing additional "headroom" and "toe room" beyond the range of values that represents the nominal black-to-white signal range.
Moreover, 16-bit and 32-bit floating point color component codings are supported in JPEG XR. In these cases the image is interpreted as floating point data, although the JPEG XR encoding and decoding steps are all performed using only integer operations (to simplify the compression processing).
The shared-exponent floating point color format known as RGBE (Radiance) is also supported, enabling more faithful storage of High Dynamic Range (HDR) images.
In addition to RGB and CMYK formats, JPEG XR also supports grayscale and multi-channel color encodings with an arbitrary number of channels.
The color representations, in most cases, are transformed to an internal color representation. The transformation is entirely reversible, so that this color transformation step does not introduce distortion and thus lossless coding modes can be supported.
Transparency map support
An alpha channel may be present to represent transparency, so that alpha blending overlay capability is enabled.
Compressed-domain image modification
In JPEG XR, full decoding of the image is unnecessary for converting an image from a lossless to lossy encoding, reducing the fidelity of a lossy encoding, or reducing the encoded image resolution.
Full decoding is also unnecessary for certain editing operations such as cropping, horizontal or vertical flips, or cardinal rotations.
The tile structure for access to image regions can also be changed without full decoding and without introducing distortion.
Metadata support
A JPEG XR image file may optionally contain an embedded ICC color profile, to achieve consistent color representation across multiple devices.
Exif and XMP metadata formats are also supported.

Container format

One file container format that can be used to store JPEG XR image data is specified in Annex A of the JPEG XR standard. It is a TIFF-like format using a table of Image File Directory (IFD) tags. A JPEG XR file contains image data, optional alpha channel data, metadata, optional XMP metadata stored as RDF/XML, and optional Exif metadata, in IFD tags. The image data is a contiguous self-contained chunk of data. The optional alpha channel, if present, can be compressed as a separate image record, enabling decoding of the image data independently of transparency data in applications which do not support transparency. (Alternatively, JPEG XR also supports an "interleaved" alpha channel format in which the alpha channel data is encoded together with the other image data in a single compressed codestream.)

Being TIFF-based, this format inherits all of the limitations of the TIFF format including the 4 GB file-size limit, which according to the HD Photo specification "will be addressed in a future update".[18]

New work has been started in the JPEG committee to enable the use of JPEG XR image coding within the JPX file storage format — enabling use of the JPIP protocol, which allows interactive browsing of networked images.[13] Additionally, a Motion JPEG XR specification was approved as an ISO standard for motion (video) compression in March 2010.[19]

Compression algorithm

Comparison between JPEG, JPEG 2000 and JPEG XR
Comparison between JPEG 2000, JPEG XR, and JPEG.

JPEG XR's design[1][20] is conceptually very similar to JPEG: the source image is optionally converted to a luma-chroma colorspace, the chroma planes are optionally subsampled, each plane is divided into fixed-size blocks, the blocks are transformed into the frequency domain, and the frequency coefficients are quantized and entropy coded. Major differences include the following:

  • JPEG supports bit depths of 8 and 12 bits; JPEG XR supports bit depths of up to 32 bits. JPEG XR also supports lossless and lossy compression of floating-point image data (by representing the floating-point values in an IEEE 754-like format, and encoding them as though they were integers) and RGBE imagery.
  • JFIF and other typical image encoding practices specify a linear transformation from RGB to YCbCr, which is slightly lossy in practice because of roundoff error. JPEG XR specifies a lossless colorspace transformation, given (for RGB) by
  • While JPEG uses 8 × 8 blocks for its frequency transformation, JPEG XR primarily uses 4 × 4 block transforms. (2 × 4 and 2 × 2 transformations are also defined for special cases involving chroma subsampling; encoder options include YUV_444, YUV_422, YUV_420, and a monochrome Y_only.)[21]
  • While JPEG uses a single transformation stage, JPEG XR applies its 4 × 4 core transform in a two-level hierarchical fashion within 16 × 16 macroblock regions. This gives the transform a wavelet-like multi-resolution hierarchy and improves its compression capability.
  • The DCT, the frequency transformation used by JPEG, is slightly lossy because of roundoff error. JPEG XR uses a type of integer transform employing a lifting scheme.[22] The required transform, called the Photo Core Transform (PCT), resembles a 4 × 4 DCT but is lossless (exactly invertible). In fact, it is a particular realization of a larger family of binary-friendly multiplier-less transforms called the binDCT.[23]
  • JPEG XR allows an optional overlap prefiltering step, called the Photo Overlap Transform (POT), before each of its 4 × 4 core transform PCT stages.[22] The filter operates on 4 × 4 blocks which are offset by 2 samples in each direction from the 4 × 4 core transform blocks. Its purpose is to improve compression capability and reduce block-boundary artifacts at low bitrates. At high bitrates, where such artifacts are typically not a problem, the prefiltering can be omitted to reduce encoding and decoding time. The overlap filtering is constructed using integer operations following a lifting scheme, so that it is also lossless. When appropriately combined, the POT and the PCT in JPEG-XR form a lapped transform.[24]
  • In JPEG, the image DC coefficients of the DCT blocks are predicted by applying DC prediction from the left neighbor transform block, and no other coeffients are predicted. In JPEG XR, 4 × 4 blocks are grouped into macroblocks of 16 × 16 samples, and the 16 DC coefficients from the 4 × 4 blocks of each macroblock are passed through another level of frequency transformation, leaving three types of coefficients to be entropy coded: the macroblock DC coefficients (called DC), macroblock-level AC coefficients (called "lowpass"), and lower-level AC coefficients (called AC). Prediction of coefficient values across transform blocks is applied to the DC coefficients and to an additional row or column of AC coefficients as well.
  • JPEG XR supports the encoding of an image by decomposing it into smaller individual rectangular tile area regions. Each tile area can be decoded independently from the other areas of the picture. This allows fast access to spatial areas of pictures without decoding the entire picture.
  • JPEG XR's entropy coding phase is more adaptive and complex than JPEG's, involving a DC and AC coefficient prediction scheme, adaptive coefficient reordering (in contrast to JPEG's fixed zigzag ordering), and a form of adaptive Huffman coding for the coefficients themselves.
  • JPEG uses a single quantization step size per DC/AC component per color plane per image. JPEG XR allows a selection of DC quantization step sizes on a tile region basis, and allows lowpass and AC quantization step sizes to vary from macroblock to macroblock.
  • Because all encoding phases except quantization are lossless, JPEG XR is lossless when all quantization coefficients are equal to 1. This is not true of JPEG. JPEG defines a separate lossless mode which does not use the DCT, but it is not implemented by libjpeg and therefore not widely supported.

The HD Photo bitstream specification claims that "HD Photo offers image quality comparable to JPEG-2000 with computational and memory performance more closely comparable to JPEG", that it "delivers a lossy compressed image of better perceptive quality than JPEG at less than half the file size", and that "lossless compressed images … are typically 2.5 times smaller than the original uncompressed data".

Software support

A reference software implementation of JPEG XR has been published as ITU-T Recommendation T.835 and ISO/IEC International Standard 29199-5.

The following notable software products natively support JPEG XR:

Product Name Publisher Read support Write support
Capture One 7 or later Phase One Yes Yes
Corel Paint Shop Pro X2 or later Corel Yes Yes [25]
Fast Picture Viewer Axel Rietschin Software Developments Yes N/A [26]
ImageMagick ImageMagick Studio LLC Yes Yes [27]
Internet Explorer 9 Microsoft Yes N/A [28][29]
Microsoft Expression Design Microsoft Yes Yes [30]
Microsoft Expression Media Microsoft Yes No
Microsoft Image Composite Editor Microsoft Yes Yes [31]
Pale Moon (web browser) Moonchild productions Yes N/A [32]
PhotoLine Computerinsel Yes Yes
Serif PhotoPlus X7 Serif Europe Yes Yes
Windows Live Photo Gallery Microsoft Yes Yes
Windows Photo Gallery Microsoft Yes Yes
Windows Photo Viewer Microsoft Yes N/A
Xara Designer Pro Xara Group Limited Yes No [33]
XnView Pierre-Emmanuel Gougelet Yes Yes [34][35]
Zoner Photo Studio 13 or later Zoner Software Yes Yes

The following notable software support JPEG XR through a Plug-in:

Product name Publisher Plug-in name Plug-in publisher Read support Write support
Adobe Photoshop (CS2,CS5-CS6) Adobe Systems JPEG XR File Format Plug-in for Photoshop Microsoft Corporation Yes Yes [36][37]
GIMP The GIMP Development Team JPEG XR plugin for GIMP C. Hausner Yes Yes [38]
IrfanView 4.25 and later Irfan Skiljan HDP version 4.26 Irfan Skiljan Yes No [39]
Paint.NET Rick Brewster JPEG XR plugin for Paint.NET C. Hausner Yes Yes [40]
Quick Look Apple Inc. JPEG XR plugin for Quick Look B. Hoary Yes N/A [41]

The following APIs and software frameworks support JPEG XR and may be used in other software to provide JPEG XR support to end users:

Product Name Publisher Read support Write support
Adobe Integrated Runtime 3.3 Adobe Systems Yes Yes [42]
Adobe Flash Player 11.3 Adobe Systems Yes Yes [42]
Integrated Performance Primitives (IPP) Intel Yes Yes [43][44]
LEADTOOLS LEAD Technologies Yes Yes [45]
Windows Imaging Component (WIC) Microsoft Yes Yes

The 2011 video game Rage employs JPEG XR compression to compress its textures.[46]

Licensing

Microsoft has patents on the technology in JPEG XR. A Microsoft representative stated in a January 2007 interview that in order to encourage the adoption and use of HD Photo, the specification is made available under the Microsoft Open Specification Promise, which asserts that Microsoft allows implementation of the specification for free, and will not file suits on the patented technology for its implementation,[47] as reportedly stated by Josh Weisberg, director of Microsoft's Rich Media Group. As of 15 August 2010, Microsoft made the resulting JPEG XR standard available under its Community Promise.[48]

In July 2010, reference software to implement the JPEG XR standard was published as ITU-T Recommendation T.835 and International Standard ISO/IEC 29199-5. Microsoft included these publications in the list of specifications covered by its Community Promise.[48]

In April 2013, Microsoft released an open source JPEG XR library under the BSD licence.[49][50] This resolved any licensing issues with the library being implemented in software packages distributed under popular open source licences such as the GNU General Public License, with which the previously released "HD Photo Device Porting Kit"[51] was incompatible.

See also

  • JPEG, an image format used for lossy compression (JPEG XR lossy is comparable with it.)
  • JPEG 2000, an improvement intended to replace JPEG by the JPEG committee as of 2000
  • JPEG XS, format for image and video with very low latency, more efficient for streaming high quality video
  • PNG, a format for lossless compression, which JPEG XR lossless is comparable with
  • WebP, a format with lossy or lossless compression, proposed by Google in 2010
  • Better Portable Graphics, a proposal by Fabrice Bellard in 2014 based on HEVC
  • HEIF, a 2015 format based on MPEG-H Part 12 (ISO/IEC 23008-12) and HEVC. Implemented by Apple as the basis for their single-image format .HEIC on iPhone 7.
  • AV1, a compression format under development by Google, Mozilla and others in a group called the Alliance for Open Media[52]

References

  1. ^ a b c d "Recommendation T.832 (01/2012): Information technology - JPEG XR image coding system - Part 2: Image coding specification". International Telecommunication Union - Standardization sector (ITU-T). January 2012. Retrieved 15 May 2014.
  2. ^ a b "Microsoft Device Porting Kit Specification". Microsoft Corporation. 7 November 2006. Retrieved 8 November 2009.
  3. ^ "Provisional Standard Media Type Registry". IANA. 12 December 2014. Retrieved 12 January 2015.
  4. ^ Bill, Crow (1 November 2006). "Introducing". Microsoft Developer Network blogs, Bill Crow's blog. Microsoft Corporation. Retrieved 24 October 2009.
  5. ^ Bill, Crow (31 July 2007). "Industry Standardization for HD Photo". Microsoft Developer Network blogs, Bill Crow's blog. Microsoft Corporation. Retrieved 14 August 2011.
  6. ^ "HD Photo, Version 1.0 (Windows Media Photo)". Digital Preservation. Library of Congress. 2008-02-19. Retrieved 2014-03-13.
  7. ^ matthewu (2014-01-31). "jxrlib". CodePlex. Retrieved 2014-03-15. The JPEG XR format replaces the HD Photo/Windows Media™ Photo format in both Windows 8 and the Windows Image Component (WIC). WIC accompanies the Internet Explorer 10 redistributable packages for down-level versions of Windows.
  8. ^ "Platform update for Windows 7 Service Pack 1 (SP1) and Windows Server 2008 R2 SP1". Microsoft Knowledge Base. 2013-02-02. KB 2670838. Retrieved 2014-03-16.
  9. ^ "Pale Moon Release Notes". Moonchild Productions.
  10. ^ Microsoft shows off JPEG rival
  11. ^ "Microsoft's HD Photo Technology Is Considered for Standardization by JPEG". Microsoft Corporation. 31 July 2007. Archived from the original on 8 August 2010. Retrieved 31 July 2007.
  12. ^ "JPEG 2000 Digital Cinema Successes and Proposed Standardization of JPEG XR". Join Photographic Experts Group. 6 July 2007. Archived from the original on 17 March 2009. Retrieved 31 July 2009.
  13. ^ a b Sharpe, Louis (17 July 2009). "Press Release – 49th WG1 Sardinia Meeting". Joint Photographic Experts Group. Archived from the original on 1 September 2009. Retrieved 24 October 2009.
  14. ^ "ISO/IEC 29199-2:2009 Information technology - JPEG XR image coding system - Part 2: Image coding specification". International Organization for Standardization (ISO) and International Electrotechnical Commission (IEC). 14 August 2009. Retrieved 18 December 2009.
  15. ^ "ISO/IEC 29199-2:2010 Information technology - JPEG XR image coding system - Part 2: Image coding specification". International Organization for Standardization (ISO) and International Electrotechnical Commission (IEC). 30 September 2010. Retrieved 18 December 2010.
  16. ^ Bill, Crow (30 July 2009). "JPEG XR is Now an International Standard". Microsoft Developer Network blogs, Bill Crow's blog. Microsoft Corporation. Retrieved 24 October 2009.
  17. ^ Crow, Bill (1 June 2006). "Pixel Formats (Part 1: Unsigned Integers)". Bill Crow's Digital Imaging & Photography Blog. Microsoft Developer Network. Retrieved 26 October 2009.
  18. ^ "Windows Media Photo Specification". Retrieved 2016-10-05.
  19. ^ "JPEG launches Innovations group, new book " JPEG 2000 Suite " published". jpeg.org. 19 March 2010. Archived from the original on 25 September 2010.
  20. ^ S. Srinivasan, C. Tu, S. L. Regunathan, and G. J. Sullivan, "HD Photo: A New Image Coding Technology for Digital Photography", SPIE Applications of Digital Image Processing XXX, SPIE Proceedings, volume 6696, paper 66960A, September 2007.
  21. ^ "JPEG XR Device Porting Kit Specification". JPEGXR_DPK_Spec_1.0.doc. Microsoft. 2013. Retrieved 2014-03-15.
  22. ^ a b C. Tu, S. Srinivasan, G. J. Sullivan, S. Regunathan, and H. S. Malvar, "Low-complexity Hierarchical Lapped Transform for Lossy-to-Lossless Image Coding in JPEG XR / HD Photo", SPIE Applications of Digital Image Processing XXXI, SPIE Proceedings, volume 7073, paper 70730C, August 2008.
  23. ^ Liang, Jie; Trac D. Tran (2001). "Fast multiplierless approximations of the DCT with the lifting scheme". IEEE Transactions on Signal Processing. 49 (12): 3032–3044. CiteSeerX 10.1.1.7.4480. doi:10.1109/78.969511.
  24. ^ Tran, Trac D.; Jie Liang; Chengjie Tu (2003). "Lapped transform via time-domain pre- and post-filtering". IEEE Transactions on Signal Processing. 51 (6): 1557–1571. CiteSeerX 10.1.1.7.8314. doi:10.1109/TSP.2003.811222.
  25. ^ "Corel Paint Shop Pro® Photo X2 Introduces Integrated Support for the Microsoft HD Photo Format". 20 November 2007. Retrieved 14 July 2011.
  26. ^ "FastPictureViewer's format compatibility chart".
  27. ^ "ImageMagick Image Formatssite". ImageMagick Studio LLC. Retrieved 6 May 2013.
  28. ^ "Image Support". Microsoft Corporation. 2010. Archived from the original on 12 April 2010. Retrieved 29 May 2010.
  29. ^ Olivier, Frank (9 April 2010). "Benefits of GPU-powered HTML5". Microsoft Corporation. Retrieved 29 May 2010.
  30. ^ Crow, Bill (27 March 2007). "Expression Design Includes HD Photo Support". Microsoft Corporation. Retrieved 1 June 2010.
  31. ^ "Microsoft Research Image Composite Editor". Microsoft Research. Retrieved 9 March 2011.
  32. ^ "Pale Moon 27.2 released!". Retrieved 18 March 2017.
  33. ^ "Advanced Features: HD Photo import". Xara Group. Retrieved 10 September 2010.
  34. ^ Gougelet, Pierre E. "Formats". Retrieved 10 September 2010.
  35. ^ Gougelet, Pierre E. "Added/Changed Features to XnView". Retrieved 11 May 2011.
  36. ^ "HD Photo Plug-ins for Photoshop are Released". Bill Crow's Digital Imaging & Photography Blog. MSDN Blogs. 6 December 2007. Retrieved 6 December 2007.
  37. ^ "JPEG XR File Format Plug-in for Photoshop". Microsoft Research. 30 January 2013. Retrieved 14 April 2013.
  38. ^ "chausner/gimp-jxr". GitHub. Retrieved 29 March 2018.
  39. ^ "IrfanView PlugIns". www.irfanview.com. Retrieved 29 March 2018.
  40. ^ "CodePlex Archive". CodePlex Archive. Retrieved 29 March 2018.
  41. ^ "CodePlex Archive". CodePlex Archive. Retrieved 29 March 2018.
  42. ^ a b "Flash Player 11 and AIR 3 Release Notes for Adobe Labs" (PDF). 12 July 2011. Archived from the original (PDF) on 14 July 2011. Retrieved 14 July 2011.
  43. ^ Product Brief: Intel Integrated Performance Primitives 7.0, 2010.
  44. ^ JPEG XR Codec support in Intel IPP - an Introduction, features and advantages, 23 August 2010.
  45. ^ "LEADTOOLS JPEG-XR Image Compression SDK". LEADTOOLS. Retrieved 29 July 2011.
  46. ^ Carmack, John (29 October 2010). "John Carmack discusses RAGE on iPhone/iPad/iPod". Bethesda Blog. ZeniMax Media Inc. Retrieved 8 March 2011.
  47. ^ Stephen Shankland (23 January 2007). "Vista to give HD Photo format more exposure". CNET. Retrieved 9 March 2007.
  48. ^ a b "Microsoft Community Promise". Retrieved 16 July 2011.
  49. ^ "JPEG XR Photoshop Plugin and Source Code". Microsoft. 11 April 2013. Retrieved 6 July 2013.
  50. ^ "jxrlib JPEG-XR library". Microsoft. 1 April 2013. Retrieved 16 April 2013.
  51. ^ "HD Photo Device Porting Kit 1.0". Microsoft. 21 December 2006. Archived from the original on 7 February 2013. Retrieved 9 August 2007.
  52. ^ "Apple wants to shrink your photos, but a new format from Google and Mozilla could go even farther". CNET. 2018-01-19. Retrieved 2018-02-01.

External links

Links to standardization publication pages
Links to information from Microsoft
Links to information from others
Better Portable Graphics

Better Portable Graphics (BPG) is a file format for coding digital images, which was created by programmer Fabrice Bellard in 2014. He has proposed it as a replacement for the JPEG image format as the more compression-efficient alternative in terms of image quality or file size.It is based on the intra-frame encoding of the High Efficiency Video Coding (HEVC) video compression standard. Tests on photographic images in July 2014 found that BPG produced smaller files for a given quality than JPEG, JPEG XR and WebP.Thanks to its portability, high quality, and low memory requirements, BPG has potential applications in portable handheld and IoT devices, where those properties are particularly important. Current research works on designing and developing more energy-efficient BPG hardware which can then be integrated in portable devices such as digital cameras.While there is no built-in native support for BPG in any mainstream browsers, websites can still deliver BPG images to all browsers by including a JavaScript library written by Bellard.

CPT (file format)

The CPT file format is a graphics file format used by some versions of Corel Photo Paint.

It is also possible to open CPT version 6 files with IrfanView, but not with Paint Shop Pro (although it is from Corel). CPT version 6 is an almost identical copy of the TIFF format, whereas since Corel Photo-Paint 7.0 (released in 1997), this was deprecated for a new proprietary format (known as CPT7), however the user can still export the older TIFF-based CPT6 files. Chasys Draw IES can open CPT7 files as well as CPT8 and the latest CPT9; this support is available as from Chasys Draw IES version 4.58.01 [1].

Corel Photo Paint is not released as a standalone program. It is part of the Corel Draw Graphics Suite, available only for Windows.

The .cpt extension is also used for files encrypted using ccrypt, and also for screen captures in the video game Tekken Tag Tournament (PlayStation 2), which are saved to the Memory Card.

Comparison of browser engines (graphics support)

This article compares graphics support for several browser engines.

Comparison of graphics file formats

This is a comparison of image file formats.

Comparison of image viewers

This article presents a comparison of image viewers and image organizers which can be used for image viewing.

G.723

G.723 is an ITU-T standard speech codec using extensions of G.721 providing voice quality covering 300 Hz to 3400 Hz using Adaptive Differential Pulse Code Modulation (ADPCM) to 24 and 40 kbit/s for digital circuit multiplication equipment (DCME) applications. The standard G.723 is obsolete and has been superseded by G.726.

Note that this is a completely different codec from G.723.1.

Gary Sullivan (engineer)

Gary Joseph Sullivan (born 1960) is an American electrical engineer who led the development of the H.264/MPEG-4 AVC and HEVC video coding standards and created the DirectX Video Acceleration (DXVA) API/DDI video decoding feature of the Microsoft Windows operating system.

He was the chairman of the Joint Video Team (JVT) standardization committee that developed the H.264/AVC standard, and he personally edited large portions of it. Since January 2010, he has been a co-chairman of the Joint Collaborative Team on Video Coding (JCT-VC) and an editor for developing the High Efficiency Video Coding (HEVC) standard. He has also led and contributed to a number of other video and image related standardization projects such as extensions of ITU-T H.263 video coding, multiview and 3D video coding for AVC and HEVC, and JPEG XR image coding. Since October 2015, he has been a co-chairman of the Joint Video Exploration Team (JVET) for exploration of video coding beyond the capability of HEVC. He has also published research work on various topics relating to video and image compression.

Half-precision floating-point format

In computing, half precision is a binary floating-point computer number format that occupies 16 bits (two bytes in modern computers) in computer memory.

In the IEEE 754-2008 standard, the 16-bit base-2 format is referred to as binary16. It is intended for storage of floating-point values in applications where higher precision is not essential for performing arithmetic computations.

Although implementations of the IEEE Half-precision floating point are relatively new, several earlier 16-bit floating point formats have existed including that of Hitachi's HD61810 DSP of 1982, Scott's WIF and the 3dfx Voodoo Graphics processor.Nvidia and Microsoft defined the half datatype in the Cg language, released in early 2002, and implemented it in silicon in the GeForce FX, released in late 2002. ILM was searching for an image format that could handle a wide dynamic range, but without the hard drive and memory cost of floating-point representations that are commonly used for floating-point computation (single and double precision). The hardware-accelerated programmable shading group led by John Airey at SGI (Silicon Graphics) invented the s10e5 data type in 1997 as part of the 'bali' design effort. This is described in a SIGGRAPH 2000 paper (see section 4.3) and further documented in US patent 7518615.This format is used in several computer graphics environments including OpenEXR, JPEG XR, GIMP, OpenGL, Cg, and D3DX. The advantage over 8-bit or 16-bit binary integers is that the increased dynamic range allows for more detail to be preserved in highlights and shadows for images. The advantage over 32-bit single-precision binary formats is that it requires half the storage and bandwidth (at the expense of precision and range).The F16C extension allows x86 processors to convert half-precision floats to and from single-precision floats.

ISO/IEC JTC 1/SC 29

ISO/IEC JTC 1/SC 29 Coding of audio, picture, multimedia and hypermedia information is a standardization subcommittee of the Joint Technical Committee ISO/IEC JTC 1 of the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC), that develops and facilitates international standards, technical reports, and technical specifications within the field of audio, picture, multimedia, and hypermedia information coding. The international secretariat of ISO/IEC JTC 1/SC 29 is the Japanese Industrial Standards Committee (JISC) located in Japan.

Image compression

Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.

Integrated Performance Primitives

Intel Integrated Performance Primitives (Intel IPP) is a multi-threaded software library of functions for multimedia and data processing applications, produced by Intel.The library supports Intel and compatible processors and is available for Linux, macOS, Windows and Android operating systems. It is available separately or as a part of Intel Parallel Studio.

Interlacing (bitmaps)

Interlacing (also known as interleaving) is a method of encoding a bitmap image such that a person who has partially received it sees a degraded copy of the entire image. When communicating over a slow communications link, this is often preferable to seeing a perfectly clear copy of one part of the image, as it helps the viewer decide more quickly whether to abort or continue the transmission.

Interlacing is supported by the following formats, where it is optional:

GIF interlacing stores the lines in the order 0, 8, 16, ...(8n), 4, 12, ...(8n+4), 2, 6, 10, 14, ...(4n+2), 1, 3, 5, 7, 9, ...(2n+1).

PNG uses the Adam7 algorithm, which interlaces in both the vertical and horizontal direction.

TGA uses two optional interlacing algorithms, two-way: 0, 2, 4, ...(2n), 1, 3, ...(2n+1) and four-way: 0, 4, 8, ...(4n), 1, 5, ...(4n+1), 2, 6, ...(4n+2), 3, 7, ...(4n+3).

JPEG, JPEG 2000, and JPEG XR (actually using a frequency decomposition hierarchy rather than interlacing of pixel values)

PGF (also using a frequency decomposition)Interlacing is a form of incremental decoding, because the image can be loaded incrementally. Another form of incremental decoding is progressive scan. In progressive scan the loaded image is decoded line for line, so instead of becoming incrementally clearer it becomes incrementally larger. The main difference between the interlace concept in bitmaps and in video is that even progressive bitmaps can be loaded over multiple frames.

For example: Interlaced GIF is a GIF image that seems to arrive on your display like an image coming through a slowly opening Venetian blind. A fuzzy outline of an image is gradually replaced by seven successive waves of bit streams that fill in the missing lines until the image arrives at its full resolution.

Interlaced graphics were once widely used in web design and before that in the distribution of graphics files over bulletin board systems and other low-speed communications methods. The practice is much less common today, as common broadband internet connections allow most images to be downloaded to the user's screen nearly instantaneously, and interlacing is usually an inefficient method of encoding images.Interlacing has been criticized because it may not be clear to viewers when the image has finished rendering, unlike non-interlaced rendering, where progress is apparent (remaining data appears as blank). Also, the benefits of interlacing to those on low-speed connections may be outweighed by having to download a larger file, as interlaced images typically do not compress as well.

Joint Photographic Experts Group

The Joint Photographic Experts Group is the joint committee between ISO/IEC JTC 1 and ITU-T (formerly CCITT) that created and maintains the JPEG, JPEG 2000, and JPEG XR standards. It is one of two sub-groups of ISO/IEC Joint Technical Committee 1, Subcommittee 29, Working Group 1 (ISO/IEC JTC 1/SC 29/WG 1) – titled as Coding of still pictures. In the ITU-T, its work falls in the domain of the ITU-T Visual Coding Experts Group (VCEG). ISO/IEC JTC1 SC29 Working Group 1 (working together with ITU-T Study Group 16 – SG16 and previously also with Study Group 8 – SG8) is responsible for the JPEG and JBIG standards. The scope of the organization includes the work of both the Joint Photographic Experts Group and Joint Bi-level Image Experts Group.In April 1983, ISO started to work to add photo quality graphics to text terminals. In the mid-1980s, both CCITT (now ITU-T) and ISO had standardization groups for image coding: CCITT Study Group VIII (SG8) – Telematic Services and ISO TC97 SC2 WG8 – Coding of Audio and Picture Information. They were historically targeted on image communication. In 1986, it was decided to create the Joint (CCITT/ISO) Photographic Expert Group. The JPEG committee was created in 1986. In 1988, it was decided to create the Joint (CCITT/ISO) Bi-level Image Group (JBIG). The group typically meets three times annually in North America, Asia and Europe. The group often meets jointly with the JBIG committee.

Lapped transform

In signal processing, a lapped transform is a type of linear discrete block transformation where the basis functions of the transformation overlap the block boundaries, yet the number of coefficients overall resulting from a series of overlapping block transforms remains the same as if a non-overlapping block transform had been used.Lapped transforms substantially reduce the blocking artifacts that otherwise occur with block transform coding techniques, in particular those using the discrete cosine transform. The best known example is the modified discrete cosine transform used in the MP3, Vorbis, AAC, and Opus audio codecs.Although the best-known application of lapped transforms has been for audio coding, they have also been used for video and image coding and various other applications. They are used in video coding for coding I-frames in VC-1 and for image coding in the JPEG XR format. More recently, a form of lapped transform has also been used in the development of the Daala video coding format.

Rico Malvar

Henrique "Rico" S. Malvar (born 1957) is a distinguished Brazilian engineer and a senior signal processing researcher at Microsoft Research's largest laboratory in Redmond, Washington, United States. He was the Managing Director of the lab following the departure of long-time Managing Director Dan Ling in 2007, and oversaw about 350 researchers. Currently, he is the Chief Scientist of Microsoft Research.

Windows Media

Windows Media is a discontinued multimedia framework for media creation and distribution for Microsoft Windows. It consists of a software development kit (SDK) with several application programming interfaces (API) and a number of prebuilt technologies, and is the replacement of NetShow technologies.

The Windows Media SDK is replaced by Media Foundation.

Windows Photo Viewer

Windows Photo Viewer (formerly Windows Picture and Fax Viewer) is an image viewer included with the Windows NT family of operating systems. It was first included with Windows XP and Windows Server 2003 under its former name. It was temporarily replaced with Windows Photo Gallery in Windows Vista, but has been reinstated in Windows 7. This program succeeds Imaging for Windows. In Windows 10, it is deprecated in favor of a Universal Windows Platform app called Photos, although it can be brought back with a registry tweak.Windows Photo Viewer can show individual pictures, display all pictures in a folder as a slide show, reorient them in 90° increments, print them either directly or via an online print service, send them in e-mail or burn them to a disc. Windows Photo Viewer supports images in BMP, JPEG, JPEG XR (formerly HD Photo), PNG, ICO, GIF and TIFF file formats.

YCoCg

The YCoCg color model is the color space formed from a simple transformation of an associated RGB color space into a luma value (denoted as Y) and two chroma values called chrominance green (Cg) and chrominance orange (Co). It is supported in video and image compression designs such as H.264/MPEG-4 AVC, HEVC, JPEG XR, and Dirac. It is simple to compute, has good transform coding gain, and can be losslessly converted to and from RGB with fewer bits than are needed with other color models. A reversible scaled version, YCoCg-R, is used in Display Stream Compression.

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