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Modified Huffman Coding
Modified Huffman coding is used in fax machines to encode black-on-white images (bitmaps). It combines the variable-length codes of Huffman coding with the coding of repetitive data in run-length encoding. The basic Huffman coding provides a way to compress files with much repeating data, like a file containing text, where the alphabet letters are the repeating objects. However, a single scan line contains only two kinds of elements white pixels and black pixels which can be represented directly as 0 and 1. This "alphabet" of only two symbols is too small to apply the Huffman coding directly. But if we first use run-length encoding, we can have more objects to encode. Here is an example taken from the article on run-length encoding Run-length encoding (RLE) is a form of lossless data compression in which ''runs'' of data (consecutive occurrences of the same data value) are stored as a single occurrence of that data value and a count of its consecutive occurrences, rather th ...: ... [...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] |
Huffman Coding
In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is commonly used for lossless data compression. The process of finding or using such a code is Huffman coding, an algorithm developed by David A. Huffman while he was a Doctor of Science, Sc.D. student at Massachusetts Institute of Technology, MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes". The output from Huffman's algorithm can be viewed as a variable-length code table for encoding a source symbol (such as a character in a file). The algorithm derives this table from the estimated probability or frequency of occurrence (''weight'') for each possible value of the source symbol. As in other entropy encoding methods, more common symbols are generally represented using fewer bits than less common symbols. Huffman's method can be efficiently implemented, finding a code in time linear time, linear to the number of input weigh ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Run-length Encoding
Run-length encoding (RLE) is a form of lossless data compression in which ''runs'' of data (consecutive occurrences of the same data value) are stored as a single occurrence of that data value and a count of its consecutive occurrences, rather than as the original run. As an imaginary example of the concept, when encoding an image built up from colored dots, the sequence "green green green green green green green green green" is shortened to "green x 9". This is most efficient on data that contains many such runs, for example, simple graphic images such as icons, line drawings, games, and animations. For files that do not have many runs, encoding them with RLE could increase the file size. RLE may also refer in particular to an early graphics file format supported by CompuServe for compressing black and white images, that was widely supplanted by their later Graphics Interchange Format (GIF). RLE also refers to a little-used image format in Windows 3.x that is saved with the fil ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Symbols
A symbol is a mark, sign, or word that indicates, signifies, or is understood as representing an idea, object, or relationship. Symbols allow people to go beyond what is known or seen by creating linkages between otherwise different concepts and experiences. All communication is achieved through the use of symbols: for example, a red octagon is a common symbol for " STOP"; on maps, blue lines often represent rivers; and a red rose often symbolizes love and compassion. Numerals are symbols for numbers; letters of an alphabet may be symbols for certain phonemes; and personal names are symbols representing individuals. The academic study of symbols is called semiotics. In the arts, symbolism is the use of a concrete element to represent a more abstract idea. In cartography, an organized collection of symbols forms a legend for a map. Etymology The word ''symbol'' derives from the late Middle French masculine noun , which appeared around 1380 in a theological sense sign ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lossless Compression Algorithms
Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. Lossless compression is possible because most real-world data exhibits statistical redundancy. By contrast, lossy compression permits reconstruction only of an approximation of the original data, though usually with greatly improved compression rates (and therefore reduced media sizes). By operation of the pigeonhole principle, no lossless compression algorithm can shrink the size of all possible data: Some data will get longer by at least one symbol or bit. Compression algorithms are usually effective for human- and machine-readable documents and cannot shrink the size of random data that contain no redundancy. Different algorithms exist that are designed either with a specific type of input data in mind or with specific assumptions about what kinds of redundancy the uncompressed data are likely to contain. Lo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
