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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. Lossy and lossless image compression Image compression may be lossy or lossless. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, clip art, or comics. Lossy compression methods, especially when used at low bit rates, introduce compression artifacts. Lossy methods are especially suitable for natural images such as photographs in applications where minor (sometimes imperceptible) loss of fidelity is acceptable to achieve a substantial reduction in bit rate. Lossy compression that produces negligible differences may be called visually lossless. Methods for lossy compression: * Tran ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Compression
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder. The process of reducing the size of a data file is often referred to as data compression. In the context of data transmission, it is called source coding; encoding done at the source of the data before it is stored or transmitted. Source coding should not be confused with channel coding, for error detection and correction or line coding, the means for mapping data onto a signa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
JPEG
JPEG ( ) is a commonly used method of lossy compression for digital images, particularly for those images produced by digital photography. The degree of compression can be adjusted, allowing a selectable tradeoff between storage size and image quality. JPEG typically achieves 10:1 compression with little perceptible loss in image quality. Since its introduction in 1992, JPEG has been the most widely used image compression standard in the world, and the most widely used digital image format, with several billion JPEG images produced every day as of 2015. The term "JPEG" is an acronym for the Joint Photographic Experts Group, which created the standard in 1992. JPEG was largely responsible for the proliferation of digital images and digital photos across the Internet, and later social media. JPEG compression is used in a number of image file formats. JPEG/ Exif is the most common image format used by digital cameras and other photographic image capture devices; along with ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
S3 Texture Compression
S3 Texture Compression (S3TC) (sometimes also called DXTn, DXTC, or BCn) 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. The method of compression is strikingly similar to the previously published Color Cell Compression, which is in turn an adaptation of Block Truncation Coding published in the late 1970s. Unlike some image compression algorithms (e.g. JPEG), S3TC's fixed-rate data compression coupled with the single memory access (cf. Color Cell Compression and some VQ-based schemes) made it well-suited for use in compressing textures in hardware-accelerated 3D computer graphics. Its subsequent inclusion in Microsoft's DirectX 6.0 and OpenGL 1.3 (via the GL_EXT_texture_compression_s3tc extension) led to widespread adoption of the technology among hardware and software makers. While S3 Graphics is no longer a competitor in the graphics accelerator ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
S2TC
S2TC (short for Super Simple Texture Compression) is a texture compression algorithm based on Color Cell Compression. It is designed to be compatible with existing patented S3TC decompressors while avoiding any need for patent licensing fees. According to the authors, compressed textures produced by a good S2TC implementation are similar in quality to compressed textures produced by a bad S3TC implementation. The S2TC reference implementation is also capable of decompressing S3TC compressed textures, but instead of implementing the patented aspects of the algorithm, the S2TC decompressor picks colors at random. S2TC was created to provide an alternative to S3TC for open source OpenGL OpenGL (Open Graphics Library) is a cross-language, cross-platform application programming interface (API) for rendering 2D and 3D vector graphics. The API is typically used to interact with a graphics processing unit (GPU), to achieve ha ... implementations which were legally constrained f ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Color Cell Compression
Color Cell Compression is a lossy image compression algorithm developed by Campbell et al., in 1986, which can be considered an early forerunner of modern texture compression algorithms, such as S3 Texture Compression and Adaptive Scalable Texture Compression. It is closely related to Block Truncation Coding, another lossy image compression algorithm, which predates Color Cell Compression, in that it uses the dominant luminance of a block of pixels to partition said pixels into two representative colors. The primary difference between Block Truncation Coding and Color Cell Compression is that the former was designed to compress grayscale images and the latter was designed to compress color images. Also, Block Truncation Coding requires that the standard deviation of the colors of pixels in a block be computed in order to compress an image, whereas Color Cell Compression does not use the standard deviation. Both algorithms, though, can compress an image down to effectively 2 bits p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Block Truncation Coding
Block Truncation Coding (BTC) is a type of lossy image compression technique for greyscale images. It divides the original images into blocks and then uses a quantizer to reduce the number of grey levels in each block whilst maintaining the same mean and standard deviation. It is an early predecessor of the popular hardware DXTC technique, although BTC compression method was first adapted to color long before DXTC using a very similar approach called Color Cell Compression. BTC has also been adapted to video compression. BTC was first proposed by Professors Mitchell and Delp at Purdue University. Another variation of BTC is Absolute Moment Block Truncation Coding or AMBTC, in which instead of using the standard deviation the first absolute moment is preserved along with the mean. AMBTC is computationally simpler than BTC and also typically results in a lower Mean Squared Error (MSE). AMBTC was proposed by Maximo Lema and Robert Mitchell. Using sub-blocks of 4×4 pixels gives a com ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Posterization
Posterization or posterisation of an image is the conversion of a continuous gradation of tone to several regions of fewer tones, causing abrupt changes from one tone to another. This was originally done with photographic processes to create posters. It can now be done photographically or with digital image processing, and may be deliberate or an unintended artifact of color quantization. Cause The effect may be created deliberately, or happen accidentally. For artistic effect, most image editing programs provide a posterization feature, or photographic processes may be used. Unwanted posterization, also known as banding, may occur when the color depth, sometimes called bit depth, is insufficient to accurately sample a continuous gradation of color tone. As a result, a continuous gradient appears as a series of discrete steps or bands of color — hence the name. When discussing fixed pixel displays, such as LCD and plasma televisions, this effect is referred to as false c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dithering
Dither is an intentionally applied form of noise used to randomize quantization error, preventing large-scale patterns such as color banding in images. Dither is routinely used in processing of both digital audio and video data, and is often one of the last stages of mastering audio to a CD. A common use of dither is converting a grayscale image to black and white, such that the density of black dots in the new image approximates the average gray level in the original. Etymology The term ''dither'' was published in books on analog computation and hydraulically controlled guns shortly after World War II. Though he did not use the term ''dither'', the concept of dithering to reduce quantization patterns was first applied by Lawrence G. Roberts in his 1961 MIT master's thesis and 1962 article. By 1964 dither was being used in the modern sense described in this article. The technique was in use at least as early as 1915, though not under the name ''dither''. In digita ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Palette (computing)
In computer graphics, a palette is the set of available colors from which an image can be made. In some systems, the palette is fixed by the hardware design, and in others it is dynamic, typically implemented via a color lookup table (CLUT), a correspondence table in which selected colors from a certain color space's color reproduction range are assigned an index, by which they can be referenced. By referencing the colors via an index, which takes less information than needed to describe the actual colors in the color space, this technique aims to reduce data usage, including processing, transfer bandwidth, RAM usage, and storage. Images in which colors are indicated by references to a CLUT are called indexed color images. Description As of 2019, the most common image colorspace in graphics cards is the RGB color model with 8 bits per pixel color depth. Using this technique, 8 bits per pixel are used to describe the luminance level in each of the RGB channels, therefore 24 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Color Space Encoding
A color space is a specific organization of colors. In combination with color profiling supported by various physical devices, it supports reproducible representations of colorwhether such representation entails an analog or a digital representation. A color space may be arbitrary, i.e. with physically realized colors assigned to a set of physical color swatches with corresponding assigned color names (including discrete numbers infor examplethe Pantone collection), or structured with mathematical rigor (as with the NCS System, Adobe RGB and sRGB). A "color space" is a useful conceptual tool for understanding the color capabilities of a particular device or digital file. When trying to reproduce color on another device, color spaces can show whether shadow/highlight detail and color saturation can be retained, and by how much either will be compromised. A " color model" is an abstract mathematical model describing the way colors can be represented as tuples of numbers (e.g. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Color Quantization
In computer graphics, color quantization or color image quantization is quantization applied to color spaces; it is a process that reduces the number of distinct colors used in an image, usually with the intention that the new image should be as visually similar as possible to the original image. Computer algorithms to perform color quantization on bitmaps have been studied since the 1970s. Color quantization is critical for displaying images with many colors on devices that can only display a limited number of colors, usually due to memory limitations, and enables efficient compression of certain types of images. The name "color quantization" is primarily used in computer graphics research literature; in applications, terms such as ''optimized palette generation'', ''optimal palette generation'', or ''decreasing color depth'' are used. Some of these are misleading, as the palettes generated by standard algorithms are not necessarily the best possible. Algorithms Most standard ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Entropy Coding
In information theory, an entropy coding (or entropy encoding) is any lossless data compression method that attempts to approach the lower bound declared by Shannon's source coding theorem, which states that any lossless data compression method must have expected code length greater or equal to the entropy of the source. More precisely, the source coding theorem states that for any source distribution, the expected code length satisfies \mathbb E_ (d(x))\geq \mathbb E_ \log_b(P(x))/math>, where l is the number of symbols in a code word, d is the coding function, b is the number of symbols used to make output codes and P is the probability of the source symbol. An entropy coding attempts to approach this lower bound. Two of the most common entropy coding techniques are Huffman coding and arithmetic coding. If the approximate entropy characteristics of a data stream are known in advance (especially for signal compression), a simpler static code may be useful. These static codes in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
