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JPEG2000
JPEG
JPEG
2000 (JP2) is an image compression standard and coding system. It was created by the Joint Photographic Experts Group committee in 2000 with the intention of superseding their original discrete cosine transform -based JPEG
JPEG
standard (created in 1992) with a newly designed, wavelet -based method. The standardized filename extension is .JP2 for ISO /IEC 15444-1 conforming files and .JPX for the extended part-2 specifications, published as ISO/IEC 15444-2. The registered MIME types are defined in RFC 3745 . For ISO/IEC 15444-1 it is IMAGE/JP2. JPEG
JPEG
2000 code streams are regions of interest that offer several mechanisms to support spatial random access or region of interest access at varying degrees of granularity. It is possible to store different parts of the same picture using different quality
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Convolution
In mathematics (and, in particular, functional analysis ) CONVOLUTION is a mathematical operation on two functions (f and g); it produces a third function, that is typically viewed as a modified version of one of the original functions, giving the integral of the pointwise multiplication of the two functions as a function of the amount that one of the original functions is translated . Convolution
Convolution
is similar to cross-correlation . It has applications that include probability , statistics , computer vision , natural language processing , image and signal processing , engineering , and differential equations . The convolution can be defined for functions on groups other than Euclidean space
Euclidean space
. For example, periodic functions , such as the discrete-time Fourier transform
Fourier transform
, can be defined on a circle and convolved by periodic convolution
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Quantization (image Processing)
QUANTIZATION, involved in image processing , is a lossy compression technique achieved by compressing a range of values to a single quantum value. When the number of discrete symbols in a given stream is reduced, the stream becomes more compressible. For example, reducing the number of colors required to represent a digital image makes it possible to reduce its file size. Specific applications include DCT data quantization in JPEG and DWT data quantization in JPEG 2000 . CONTENTS * 1 Color quantization * 2 Frequency quantization for image compression * 2.1 Quantization matrices * 3 See also * 4 References COLOR QUANTIZATION Main article: Color quantization Color quantization reduces the number of colors used in an image; this is important for displaying images on devices that support a limited number of colors and for efficiently compressing certain kinds of images
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Real Numbers
In mathematics , a REAL NUMBER is a value that represents a quantity along a line . The adjective real in this context was introduced in the 17th century by René Descartes , who distinguished between real and imaginary roots of polynomials . The real numbers include all the rational numbers , such as the integer −5 and the fraction 4/3, and all the irrational numbers , such as √2 (1.41421356..., the square root of 2 , an irrational algebraic number ). Included within the irrationals are the transcendental numbers , such as π (3.14159265...). Real numbers can be thought of as points on an infinitely long line called the number line or real line , where the points corresponding to integers are equally spaced. Any real number can be determined by a possibly infinite decimal representation , such as that of 8.632, where each consecutive digit is measured in units one tenth the size of the previous one
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Bit Plane
A BIT PLANE of a digital discrete signal (such as image or sound) is a set of bits corresponding to a given bit position in each of the binary numbers representing the signal. For example, for 16-bit data representation there are 16 bit planes: the first bit plane contains the set of the most significant bit, and the 16th contains the least significant bit. It is possible to see that the first bit plane gives the roughest but the most critical approximation of values of a medium, and the higher the number of the bit plane, the less is its contribution to the final stage. Thus, adding a bit plane gives a better approximation. If a bit on the nth bit plane on an m-bit dataset is set to 1, it contributes a value of 2(m-n), otherwise it contributes nothing. Therefore, bit planes can contribute half of the value of the previous bit plane
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Lifting Scheme
The LIFTING SCHEME is a technique for both designing wavelets and performing the discrete wavelet transform (DWT). In an implementation, it is often worthwhile to merge these steps and design the wavelet filters while performing the wavelet transform. This is then called the second-generation wavelet transform . The technique was introduced by Wim Sweldens . The lifting scheme factorizes any discrete wavelet transform with finite filters into a series of elementary convolution operators, so-called lifting steps, which reduces the number of arithmetic operations by nearly a factor two. Treatment of signal boundaries is also simplified. The discrete wavelet transform applies several filters separately to the same signal. In contrast to that, for the lifting scheme, the signal is divided like a zipper. Then a series of convolution-accumulate operations across the divided signals is applied
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RGB Color Model
The RGB COLOR MODEL is an additive color model in which red , green and blue light are added together in various ways to reproduce a broad array of colors . The name of the model comes from the initials of the three additive primary colors , red, green and blue. The main purpose of the RGB color model
RGB color model
is for the sensing, representation and display of images in electronic systems, such as televisions and computers, though it has also been used in conventional photography . Before the electronic age , the RGB color model already had a solid theory behind it, based in human perception of colors . RGB is a device-dependent color model: different devices detect or reproduce a given RGB value differently, since the color elements (such as phosphors or dyes ) and their response to the individual R, G and B levels vary from manufacturer to manufacturer, or even in the same device over time
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Media Type
A MEDIA TYPE (also MIME TYPE and CONTENT TYPE) is a two-part identifier for file formats and format contents transmitted on the Internet
Internet
. The Internet
Internet
Assigned Numbers Authority (IANA) is the official authority for the standardization and publication of these classifications. Media types were originally defined in Request for Comments 2045 in November 1996 as a part of MIME (Multipurpose Internet
Internet
Mail Extensions) specification, for denoting type of email message content and attachments; hence the name MIME type. Media types are also used by other internet protocols such as HTTP
HTTP
and document file formats such as HTML
HTML
, for similar purpose
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YCbCr
YCBCR, Y′CBCR, or Y PB/CB PR/CR, also written as YCBCR or Y\'CBCR, is a family of color spaces used as a part of the color image pipeline in video and digital photography systems. Y′ is the luma component and CB and CR are the blue-difference and red-difference chroma components. Y′ (with prime) is distinguished from Y, which is luminance , meaning that light intensity is nonlinearly encoded based on gamma corrected RGB
RGB
primaries. Y′CbCr color spaces are defined by a mathematical coordinate transformation from an associated RGB
RGB
color space. If the underlying RGB
RGB
color space is absolute, the Y′CbCr color space is an absolute color space as well; conversely, if the RGB
RGB
space is ill-defined, so is Y′CbCr
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Chrominance
CHROMINANCE (chroma or C for short) is the signal used in video systems to convey the color information of the picture, separately from the accompanying luma signal (or Y for short). Chrominance is usually represented as two color-difference components: U = B′ − Y′ (blue − luma) and V = R′ − Y′ (red − luma). Each of these difference components may have scale factors and offsets applied to it, as specified by the applicable video standard. In composite video signals, the U and V signals modulate a color subcarrier signal, and the result is referred to as the chrominance signal; the phase and amplitude of this modulated chrominance signal correspond approximately to the hue and saturation of the color. In digital-video and still-image color spaces such as Y′CbCr , the luma and chrominance components are digital sample values
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Arithmetic Coding
ARITHMETIC CODING is a form of entropy encoding used in lossless data compression . Normally, a string of characters such as the words "hello there" is represented using a fixed number of bits per character, as in the ASCII code. When a string is converted to arithmetic encoding, frequently used characters will be stored with fewer bits and not-so-frequently occurring characters will be stored with more bits, resulting in fewer bits used in total. Arithmetic coding differs from other forms of entropy encoding, such as Huffman coding , in that rather than separating the input into component symbols and replacing each with a code, arithmetic coding encodes the entire message into a single number, an arbitrary-precision fraction q where 0.0 ≤ q < 1.0. It represents the current information as a range, defined by two numbers. Recent Asymmetric Numeral Systems family of entropy coders allows for faster implementations thanks to directly operating on a single natural number representing the current information. An arithmetic coding example assuming a fixed probability distribution of three Symbols "A", "B", and "C". Probability of "A" is 50%, probability of "B" is 33% and probability of "C" is 17%. Furthermore we assume that the recursion depth is known in each step. In step one we code "B" which is inside the interval Encoding the message "WIKI" with arithmetic coding 1. The letter frequencies are found. 2. The interval In the simplest case, the probability of each symbol occurring is equal
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Rate–distortion Optimization
RATE-DISTORTION OPTIMIZATION (RDO) is a method of improving video quality in video compression . The name refers to the optimization of the amount of distortion (loss of video quality) against the amount of data required to encode the video, the rate. While it is primarily used by video encoders, rate-distortion optimization can be used to improve quality in any encoding situation (image, video, audio, or otherwise) where decisions have to be made that affect both file size and quality simultaneously. CONTENTS * 1 Background * 2 How it works * 3 List of encoders that support RDO * 4 References BACKGROUNDThe classical method of making encoding decisions is for the video encoder to choose the result which yields the highest quality output image. However, this has the disadvantage that the choice it makes might require more bits while giving comparatively little quality benefit
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Remote Sensing
REMOTE SENSING is the acquisition of information about an object or phenomenon without making physical contact with the object and thus in contrast to on-site observation. Remote sensing
Remote sensing
is used in numerous fields, including geography , land surveying and most Earth Science disciplines (for example, hydrology, ecology , oceanography, glaciology, geology); it also has military, intelligence, commercial, economic, planning, and humanitarian applications. In current usage, the term "remote sensing" generally refers to the use of satellite- or aircraft-based sensor technologies to detect and classify objects on Earth, including on the surface and in the atmosphere and oceans , based on propagated signals (e.g. electromagnetic radiation )
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Mars
7006339620000000000♠3,396.2±0.1 km   0.533 Earths POLAR RADIUS 7006337620000000000♠3,376.2±0.1 km   0.531 Earths FLATTENING 6997589000000000000♠0.00589±0.00015 SURFACE AREA 7014144798500000000♠144,798,500 km2 0.284 Earths VOLUME 7020163180000000000♠1.6318×1011 km3 0.151 Earths MASS 7023641710000000000♠6.4171×1023 kg 0.107 Earths MEAN DENSITY 7000393350000000000♠3.9335±0.0004 g/cm³ SURFACE GRAVITY 7000371100000000000♠3.711 m/s² 0.376 g MOMENT OF INERTIA FACTOR 6999366200000000000♠0.3662±0.0017 ESCAPE VELOCITY 5.027 km/s SIDEREAL ROTATION PERIOD 7004886426848000000♠1.025957 d 24h 37m 22s EQUATORIAL ROTATION VELOCITY 868.22 km/h (241.17 m/s) AXIAL TILT 25.19° to its orbital plane NORTH POLE RIGHT ASCENSION 21h 10m 44s 7000554458692594390♠317.68143°


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Digital Preservation
In library and archival science , DIGITAL PRESERVATION is a formal endeavor to ensure that digital information of continuing value remains accessible and usable. It involves planning, resource allocation, and application of preservation methods and technologies, and it combines policies, strategies and actions to ensure access to reformatted and "born-digital " content, regardless of the challenges of media failure and technological change. The goal of digital preservation is the accurate rendering of authenticated content over time. According to the Harrod's Librarian Glossary, digital preservation is the method of keeping digital material alive so that they remain usable as technological advances render original hardware and software specification obsolete
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World Meteorological Organization
The WORLD METEOROLOGICAL ORGANIZATION (WMO) is an intergovernmental organization with a membership of 191 Member States and Territories. It originated from the International Meteorological Organization (IMO), which was founded in 1873. Established by the ratification of the WMO Convention on 23 March 1950, WMO became the specialised agency of the United Nations
United Nations
for meteorology (weather and climate ), operational hydrology and related geophysical sciences a year later. Its current Secretary-General is Petteri Taalas and the President of the World Meteorological Congress, its supreme body, is David Grimes. The Organization is headquartered in Geneva, Switzerland
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