Lossy compression

In information technology, lossy compression or irreversible compression is the class of data encoding methods that uses inexact approximations and partial data discarding to represent the content.

Compression can be either lossy or lossless.

Basic information theory says that there is an absolute limit in reducing the size of this data.

Applications of fundamental topics of information theory include lossless data compression (e.g. ZIP files), lossy data compression (e.g. MP3s and JPEGs), and channel coding (e.g. for DSL).

While data reduction (compression, be it lossy or lossless) is a main goal of transform coding, it also allows other goals: one may represent data more accurately for the original amount of space – for example, in principle, if one starts with an analog or high-resolution digital master, an MP3 file of a given size should provide a better representation than a raw uncompressed audio in WAV or AIFF file of the same size.

In the aspects of MP3 pertaining to audio compression—the aspect of the standard most apparent to end-users (and for which is it best known)—MP3 uses lossy data-compression to encode data using inexact approximations and the partial discarding of data.

Or lossy compressed images may be 'visually lossless', or in the case of medical images, so-called Diagnostically Acceptable Irreversible Compression (DAIC) may have been applied.

In medical imaging applications, Diagnostically Acceptable Irreversible Compression, abbreviated DAIC, is the application of irreversible compression in medical imaging to produce a result that has no negative impact on the ability of the user to perform a particular diagnostic task (contribute to making a medical diagnosis using the image).

This is opposed to lossless data compression (reversible data compression) which does not degrade the data.

By contrast, lossy compression permits reconstruction only of an approximation of the original data, though usually with improved compression rates (and therefore reduced file sizes).

More generally, some forms of lossy compression can be thought of as an application of transform coding – in the case of multimedia data, perceptual coding: it transforms the raw data to a domain that more accurately reflects the information content.

The transformation is typically lossless (perfectly reversible) on its own but is used to enable better (more targeted) quantization, which then results in a lower quality copy of the original input (lossy compression).

While data reduction (compression, be it lossy or lossless) is a main goal of transform coding, it also allows other goals: one may represent data more accurately for the original amount of space – for example, in principle, if one starts with an analog or high-resolution digital master, an MP3 file of a given size should provide a better representation than a raw uncompressed audio in WAV or AIFF file of the same size.

This type of AIFF file uses much more disk space than lossy formats like MP3—about 10 MB for one minute of stereo audio at a sample rate of 44.1 kHz and a bit depth of 16 bits.

In lossy transform codecs, samples of picture or sound are taken, chopped into small segments, transformed into a new basis space, and quantized. The resulting quantized values are then entropy coded.

Quantization also forms the core of essentially all lossy compression algorithms.

This can be avoided by only producing lossy files from (lossless) originals and only editing (copies of) original files, such as images in raw image format instead of JPEG. Such schemes have also been standardized for older designs as well, such as JPEG images with progressive encoding, and MPEG-2 and MPEG-4 Part 2 video, although those prior schemes had limited success in terms of adoption into real-world common usage.

JPEG is a commonly used method of lossy compression for digital images, particularly for those images produced by digital photography.

Flaws caused by lossy compression that are noticeable to the human eye or ear are known as compression artifacts.

A compression artifact (or artefact) is a noticeable distortion of media (including images, audio, and video) caused by the application of lossy compression.

This is because these types of data are intended for human interpretation where the mind can easily "fill in the blanks" or see past very minor errors or inconsistencies – ideally lossy compression is transparent (imperceptible), which can be verified via an ABX test.

In data compression and psychoacoustics, transparency is the result of lossy data compression accurate enough that the compressed result is perceptually indistinguishable from the uncompressed input.

In lossy transform codecs, samples of picture or sound are taken, chopped into small segments, transformed into a new basis space, and quantized. The resulting quantized values are then entropy coded.

Many popular codecs are lossy.

Such schemes have also been standardized for older designs as well, such as JPEG images with progressive encoding, and MPEG-2 and MPEG-4 Part 2 video, although those prior schemes had limited success in terms of adoption into real-world common usage.

It describes a combination of lossy video compression and lossy audio data compression methods, which permit storage and transmission of movies using currently available storage media and transmission bandwidth.

Some well-known designs that have this capability include JPEG 2000 for still images and H.264/MPEG-4 AVC based Scalable Video Coding for video.

The codestream obtained after compression of an image with JPEG 2000 is scalable in nature, meaning that it can be decoded in a number of ways; for instance, by truncating the codestream at any point, one may obtain a representation of the image at a lower resolution, or signal-to-noise ratio – see scalable compression.

Some well-known designs that have this capability include JPEG 2000 for still images and H.264/MPEG-4 AVC based Scalable Video Coding for video.

H.264 is typically used for lossy compression, although it is also possible to create truly lossless-coded regions within lossy-coded pictures or to support rare use cases for which the entire encoding is lossless.

Fractal compression

Fractal compression is a lossy compression method for digital images, based on fractals.

The psychoacoustic model describes how sound can be highly compressed without degrading perceived quality.

The psychoacoustic model provides for high quality lossy signal compression by describing which parts of a given digital audio signal can be removed (or aggressively compressed) safely—that is, without significant losses in the (consciously) perceived quality of the sound.

Another use is for backward compatibility and graceful degradation: in color television, encoding color via a luminance-chrominance transform domain (such as YUV) means that black-and-white sets display the luminance, while ignoring the color information.

However, this color space conversion is lossy, particularly obvious in crosstalk from the luma to the chroma-carrying wire, and vice versa, in analogue equipment (including RCA connectors to transfer a digital signal, as all they carry is analogue composite video, which is either YUV, YIQ, or even CVBS).

JPEG XR, another successor of JPEG with support for high dynamic range, wide gamut pixel formats (lossless or lossy compression)

JPEG XR (JPEG extended range ) 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). It supports both lossy and lossless compression, and is the preferred image format for Ecma-388 Open XML Paper Specification documents.

Without this capacity, which is often the case in practice, to produce a representation with lower resolution or lower fidelity than a given one, one needs to start with the original source signal and encode, or start with a compressed representation and then decompress and re-encode it (transcoding), though the latter tends to cause digital generation loss.

Transcoding is commonly a lossy process, introducing generation loss; however, transcoding can be lossless if the output is either losslessly compressed or uncompressed.

S3TC texture compression for 3D computer graphics hardware

S3 Texture Compression (S3TC) (sometimes also called DXTn or DXTC) is a group of related lossy texture compression algorithms originally developed by Iourcha et al. of S3 Graphics, Ltd. for use in their Savage 3D computer graphics accelerator.

Such formats include MPEG-4 SLS (Scalable to Lossless), WavPack, OptimFROG DualStream, and DTS-HD Master Audio in lossless (XLL) mode

DTS-HD Master Audio (DTS-HD MA) is a combined lossless/lossy audio codec created by DTS (formerly Digital Theater Systems), commonly used for surround-sound movie soundtracks on Blu-ray Disc.

DjVu

It uses technologies such as image layer separation of text and background/images, progressive loading, arithmetic coding, and lossy compression for bitonal (monochrome) images.

MPEG-1 Part 2

MPEG-1 is a standard for lossy compression of video and audio.

Without this capacity, which is often the case in practice, to produce a representation with lower resolution or lower fidelity than a given one, one needs to start with the original source signal and encode, or start with a compressed representation and then decompress and re-encode it (transcoding), though the latter tends to cause digital generation loss. Lossy compression formats suffer from generation loss: repeatedly compressing and decompressing the file will cause it to progressively lose quality.

Lossless compression is, by definition, fully reversible, while lossy compression throws away some data which cannot be restored.