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Color Cell Compression
Color Cell Compression is a lossy compression, 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 ef ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lossy Compression
In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size for storing, handling, and transmitting content. Higher degrees of approximation create coarser images as more details are removed. This is opposed to lossless data compression (reversible data compression) which does not degrade the data. The amount of data reduction possible using lossy compression is much higher than using lossless techniques. Well-designed lossy compression technology often reduces file sizes significantly before degradation is noticed by the end-user. Even when noticeable by the user, further data reduction may be desirable (e.g., for real-time communication or to reduce transmission times or storage needs). The most widely used lossy compression algorithm is the discrete cosine transform (DCT), first published by N ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bitmap
In computing, a bitmap (also called raster) graphic is an image formed from rows of different colored pixels. A GIF is an example of a graphics image file that uses a bitmap. As a noun, the term "bitmap" is very often used to refer to a particular bitmapping application: the pix-map, which refers to a map of pixels, where each pixel may store more than two colors, thus using more than one bit per pixel. In such a case, the domain in question is the array of pixels which constitute a digital graphic output device (a screen or monitor). In some contexts, the term ''bitmap'' implies one bit per pixel, whereas ''pixmap'' is used for images with multiple bits per pixel. A bitmap is a type of memory organization or image file format used to store digital images. The term ''bitmap'' comes from the computer programming terminology, meaning just a ''map of bits'', a spatially mapped array of bits. Now, along with ''pixmap'', it commonly refers to the similar concept of a spatially mapp ... [...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 Language-independent specification, cross-language, cross-platform application programming interface (API) for rendering 2D computer graphics, 2D and 3D computer graphics, 3D vector graphics. The API is typic ... implementations which were legally constrained ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apple Video
Apple Video is a lossy video compression and decompression algorithm (codec) developed by Apple Inc. and first released as part of QuickTime 1.0 in 1991. The codec is also known as QuickTime Video, by its FourCC RPZA and the name Road Pizza. (The codename "Road Pizza" is a reference to the idea that "when you run over an animal, you're basically compressing it on the freeway".) When used in the AVI container, the FourCC AZPR is also used. The bit-stream format of Apple Video has been reverse-engineered and a decoder has been implemented in the projects XAnim and Libavcodec. Technical Details The codec operates on 4×4 blocks of pixels in the RGB colorspace. Each frame is segmented into 4×4 blocks in raster-scan order. Each block is coded in one of four coding modes: skip, single color, four color, or 16 color. Colors are represented by 16 bits with a bit-depth of 5 bit for each of the three components red, green, and blue, a format known as RGB555. Because Apple Video op ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
JPEG
JPEG ( , short for Joint Photographic Experts Group and sometimes retroactively referred to as JPEG 1) 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 trade off between storage size and image quality. JPEG typically achieves 10:1 compression with noticeable, but widely agreed to be acceptable 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 Joint Photographic Experts Group created the standard in 1992, based on the discrete cosine transform (DCT) algorithm. 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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Compression Ratio
Data compression ratio, also known as compression power, is a measurement of the relative reduction in size of data representation produced by a data compression algorithm. It is typically expressed as the division of uncompressed size by compressed size. Definition Data compression ratio is defined as the ratio between the ''uncompressed size'' and ''compressed size'': : = \frac Thus, a representation that compresses a file's storage size from 10 MB to 2 MB has a compression ratio of 10/2 = 5, often notated as an explicit ratio, 5:1 (read "five" to "one"), or as an implicit ratio, 5/1. This formulation applies equally for compression, where the uncompressed size is that of the original; and for decompression, where the uncompressed size is that of the reproduction. Sometimes the ''space saving'' is given instead, which is defined as the reduction in size relative to the uncompressed size: : = 1 - \frac Thus, a representation that compresses the storage size of a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dereference
In computer science, a pointer is an object (computer science), object in many programming languages that stores a memory address. This can be that of another value located in computer memory, or in some cases, that of memory-mapped I/O, memory-mapped computer hardware. A pointer ''references'' a location in memory, and obtaining the value stored at that location is known as ''dereferencing'' the pointer. As an analogy, a page number in a book's index could be considered a pointer to the corresponding page; dereferencing such a pointer would be done by flipping to the page with the given page number and reading the text found on that page. The actual format and content of a pointer variable is dependent on the underlying computer architecture. Using pointers significantly improves Computer performance, performance for repetitive operations, like traversing Collection (abstract data type)#Linear collections, iterable data Data structure, structures (e.g. String algorithms, stri ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lookup Table
In computer science, a lookup table (LUT) is an array data structure, array that replaces runtime (program lifecycle phase), runtime computation of a mathematical function (mathematics), function with a simpler array indexing operation, in a process termed as ''direct addressing''. The savings in processing time can be significant, because retrieving a value from memory is often faster than carrying out an "expensive" computation or input/output operation. The tables may be precomputation, precalculated and stored in static memory allocation, static program storage, calculated (or prefetcher, "pre-fetched") as part of a program's initialization phase (''memoization''), or even stored in hardware in application-specific platforms. Lookup tables are also used extensively to validate input values by matching against a list of valid (or invalid) items in an array and, in some programming languages, may include pointer functions (or offsets to labels) to process the matching input. Fiel ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
K-means Clustering
''k''-means clustering is a method of vector quantization, originally from signal processing, that aims to partition of a set, partition ''n'' observations into ''k'' clusters in which each observation belongs to the cluster (statistics), cluster with the nearest mean (cluster centers or cluster centroid), serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells. ''k''-means clustering minimizes within-cluster variances (squared Euclidean distances), but not regular Euclidean distances, which would be the more difficult Weber problem: the mean optimizes squared errors, whereas only the geometric median minimizes Euclidean distances. For instance, better Euclidean solutions can be found using k-medians clustering, ''k''-medians and k-medoids, ''k''-medoids. The problem is computationally difficult (NP-hardness, NP-hard); however, efficient heuristic algorithms converge quickly to a local optimum. These are usually similar to the ex ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Median Cut
Median cut is an algorithm to sort data of an arbitrary number of dimensions into series of sets by recursively cutting each set of data at the median point along the longest dimension. Median cut is typically used for color quantization. For example, to reduce a 64k-colour image to 256 colours, median cut is used to find 256 colours that match the original data well. Implementation of color quantization Suppose we have an image with an arbitrary number of pixels and want to generate a palette of 16 colors. Put all the pixels of the image (that is, their RGB values) in a bucket. Find out which color channel (red, green, or blue) among the pixels in the bucket has the greatest range, then sort the pixels according to that channel's values. For example, if the blue channel has the greatest range, then a pixel with an RGB value of is less than a pixel with an RGB value of , because . After the bucket has been sorted, move the upper half of the pixels into a new bucket. (It is thi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Truncate
In mathematics and computer science, truncation is limiting the number of digits right of the decimal point. Truncation and floor function Truncation of positive real numbers can be done using the floor function. Given a number x \in \mathbb_+ to be truncated and n \in \mathbb_0, the number of elements to be kept behind the decimal point, the truncated value of x is :\operatorname(x,n) = \frac. However, for negative numbers truncation does not round in the same direction as the floor function: truncation always rounds toward zero, the \operatorname function rounds towards negative infinity. For a given number x \in \mathbb_-, the function \operatorname is used instead :\operatorname(x,n) = \frac. Causes of truncation With computers, truncation can occur when a decimal number is typecast as an integer; it is truncated to zero decimal digits because integers cannot store non-integer real numbers. In algebra An analogue of truncation can be applied to polynomials. In ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Arithmetic Mean
In mathematics and statistics, the arithmetic mean ( ), arithmetic average, or just the ''mean'' or ''average'' is the sum of a collection of numbers divided by the count of numbers in the collection. The collection is often a set of results from an experiment, an observational study, or a Survey (statistics), survey. The term "arithmetic mean" is preferred in some contexts in mathematics and statistics because it helps to distinguish it from other types of means, such as geometric mean, geometric and harmonic mean, harmonic. Arithmetic means are also frequently used in economics, anthropology, history, and almost every other academic field to some extent. For example, per capita income is the arithmetic average of the income of a nation's Human population, population. While the arithmetic mean is often used to report central tendency, central tendencies, it is not a robust statistic: it is greatly influenced by outliers (Value (mathematics), values much larger or smaller than ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
