Image compression is the application of Data compression on digital images. A digital image is a representation of a two-dimensional Image using ones and zeros (binary In effect, the objective is to reduce redundancy of the image data in order to be able to store or transmit data in an efficient form. Data transmission is the transfer of Data from point-to-point often represented as an Electro-magnetic Signal over a physical point-to-point or point-to-multipoint

A chart showing the relative quality of various jpg settings and also compares saving a file as a jpg normally and using a "save for web" technique

Image compression can be lossy or lossless. A lossy compression method is one where compressing data and then decompressing it retrieves data that may well be different from the original but is close enough to be useful Lossless data compression is a class of Data compression Algorithms that allows the exact original data to be reconstructed from the compressed data Lossless compression is sometimes preferred for artificial images such as technical drawings, icons or comics. This is because lossy compression methods, especially when used at low bit rates, introduce compression artifacts. In Telecommunications and Computing, bitrate (sometimes written bit rate, data rate or as a Variable R or f b A compression artifact (or artefact) is the result of an aggressive Data compression scheme applied to an Image, audio, or Video Lossless compression methods may also be preferred for high value content, such as medical imagery or image scans made for archival purposes. Lossy methods are especially suitable for natural images such as photos in applications where minor (sometimes imperceptible) loss of fidelity is acceptable to achieve a substantial reduction in bit rate.

Methods for lossless image compression are:

• Run-length encoding – used as default method in PCX and as one of possible in BMP, TGA, TIFF
• Entropy coding
• Adaptive dictionary algorithms such as LZW – used in GIF and TIFF
• Deflation – used in PNG, MNG and TIFF

Methods for lossy compression:

• Reducing the color space to the most common colors in the image. Run-length encoding ( RLE) is a very simple form of Data compression in which runs of data (that is sequences in which the same data value occurs in many PCX is an image file format developed by the ZSoft Corporation of Marietta Georgia USA The BMP file format, sometimes called bitmap or DIB file format (for device-independent bitmap) is an Image file format used to store Truevision's (now AVID) TGA File Format, often referred to as TARGA File Format, is a raster graphics file format. In Information theory an entropy encoding is a lossless Data compression scheme that is independent of the specific characteristics of the medium Lempel-Ziv-Welch ( LZW) is a universal Lossless data compression Algorithm created by Abraham Lempel, Jacob Ziv, and Terry Portable Network Graphics ( PNG) is a bitmapped image format that employs Lossless data compression. Multiple-image Network Graphics ( MNG, ˈmɪŋ is a public Graphics file format for animated images A Color model is an abstract mathematical model describing the way Colors can be represented as Tuples of numbers typically as three or four values or color components The selected colors are specified in the color palette in the header of the compressed image. Each pixel just references the index of a color in the color palette. This method can be combined with dithering to avoid posterization. Dither is an intentionally applied form of Noise, used to randomize Quantization error, thereby preventing large-scale patterns such as contouring that are more objectionable Posterization (pronounced Poe-ster-ize-ation of an image occurs when a region of an image with a continuous gradation of tone is replaced with several regions of fewer tones resulting
• Chroma subsampling. Chroma subsampling is the practice of encoding images by implementing less resolution for chroma Information than for luma information This takes advantage of the fact that the eye perceives brightness more sharply than color, by dropping half or more of the chrominance information in the image.
• Transform coding. Transform coding is a type of Data compression for "natural" data like audio signals or photographic Images The transformation is typically This is the most commonly used method. A Fourier-related transform such as DCT or the wavelet transform are applied, followed by quantization and entropy coding. This is a list of Linear transformations of functions related to Fourier analysis. A discrete cosine transform ( DCT) expresses a sequence of finitely many data points in terms of a sum of Cosine functions oscillating at different frequencies In Mathematics, a wavelet series is a representation of a Square-integrable ( real - or complex -valued function by a certain Orthonormal In Information theory an entropy encoding is a lossless Data compression scheme that is independent of the specific characteristics of the medium
• Fractal compression. Fractal compression is a lossy image compression method using Fractals to achieve high levels of compression

The best image quality at a given bit-rate (or compression rate) is the main goal of image compression. In Telecommunications and Computing, bitrate (sometimes written bit rate, data rate or as a Variable R or f b However, there are other important properties of image compression schemes:

Scalability generally refers to a quality reduction achieved by manipulation of the bitstream or file (without decompression and re-compression). Other names for scalability are progressive coding or embedded bitstreams. Despite its contrary nature, scalability can also be found in lossless codecs, usually in form of coarse-to-fine pixel scans. Scalability is especially useful for previewing images while downloading them (e. g. in a web browser) or for providing variable quality access to e. g. databases. There are several types of scalability:

• Quality progressive or layer progressive: The bitstream successively refines the reconstructed image.
• Resolution progressive: First encode a lower image resolution; then encode the difference to higher resolutions.
• Component progressive: First encode grey; then color.

Region of interest coding. Certain parts of the image are encoded with higher quality than others. This can be combined with scalability (encode these parts first, others later).

Meta information. Compressed data can contain information about the image which can be used to categorize, search or browse images. Such information can include color and texture statistics, small preview images and author/copyright information. In Computing, preview is a function to display a document page film etc

Processing power. Compression algorithms require different amounts of processing power to encode and decode. Instructions per second (IPS is a measure of a Computer 's processor speed Some high compression algorithms require high processing power.

The quality of a compression method is often measured by the Peak signal-to-noise ratio. The phrase peak signal-to-noise ratio, often abbreviated PSNR, is an engineering term for the ratio between the maximum possible power of a signal and the power It measures the amount of noise introduced through a lossy compression of the image. However, the subjective judgement of the viewer is also regarded as an important, perhaps the most important, measure.

See also

• Graphics file formats
• Digital signal processing
• Image processing
• Computer graphics
• Lenna
• Standard test image
• Image Quality
  • PSNR
  • SSIM

External links

• MIT Linear Algebra Lecture on Image Compression at Google Video, from MIT OpenCourseWare
• Image Coding Fundamentals
• A study about image compression (Image compression basics and comparing different compression methods like JPEG2000, JPEG and JPEG XR / HD Photo)
• Data Compression Basics (includes comparison of PNG, JPEG and JPEG-2000 formats)
• FAQ:What is the state of the art in lossless image compression? from comp.compression