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Bitplanes
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 2m−n, otherwise it contributes nothing. Therefore, bit planes can contribute half of the value of the previous bit plane. For example, in the 8-bit value 10110101 (181 in decimal) the bit planes work as follows: Bit plane is sometimes used as synonymous to Bitmap ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Planar (computer Graphics)
In computer graphics, planar is the method of arranging pixel data into several ''bitplanes'' of RAM. Each bit in a bitplane is related to one pixel on the screen. Unlike packed, high color, or true color graphics, the whole dataset for an individual pixel isn't in one specific location in RAM, but spread across the bitplanes that make up the display. Planar arrangement determines how pixel data is laid out in memory, not how the data for a pixel is interpreted; pixel data in a planar arrangement could encode either indexed or direct color. This scheme originated in the early days of computer graphics. The memory chips of this era can not supply data fast enough on their own to generate a picture on a TV screen or monitor from a large framebuffer. By splitting the data up into multiple planes, each plane can be stored on a separate memory chip. These chips can then be read in parallel at a slower rate, allowing graphical display on modest hardware, like game consoles of the third ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lichtenstein Bitplanes
Liechtenstein is a country in Europe. Lichtenstein or Liechtenstein may also refer to: * House of Liechtenstein, the ruling family of Liechtenstein Places * Lichtenstein, Saxony, a town in Saxony, Germany. * Lichtenstein, Baden-Württemberg, a municipality in Baden-Württemberg, Germany. * Lichtenstein Castle (Greifenstein), castle in Hesse, Germany. * Lichtenstein Castle (Lower Franconia), castle in Bavaria, Germany. * Lichtenstein Castle (Württemberg), in Baden-Württemberg, Germany. * Liechtenstein Castle, in Lower Austria (after which the family and the country are named). * Lichtenstein (Osterode am Harz), a hill in Lower Saxony. Other uses * ''Lichtenstein'' (novel), an 1826 novel by Wilhelm Hauff * Lichtenstein (surname), shared by several notable people * Liechtenstein Museum or Liechtenstein collection, of the princely family * Lichtenstein radar The Lichtenstein radar was among the earliest airborne radars available to the Luftwaffe in World War II and the f ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Atari ST
The Atari ST is a line of personal computers from Atari Corporation and the successor to the Atari 8-bit family. The initial model, the Atari 520ST, had limited release in April–June 1985 and was widely available in July. It was the first personal computer with a bitmapped color GUI, using a version of Digital Research's GEM (desktop environment), GEM from February 1985. The Atari 1040ST, released in 1986 with 1 MB of RAM, was the first home computer with a cost-per-kilobyte of less than US$1. "ST" officially stands for "Sixteen/Thirty-two", referring to the Motorola 68000's 16-bit computing, 16-bit external bus and 32-bit computing, 32-bit internals. The system was designed by a small team led by Shiraz Shivji. Alongside the Macintosh, Amiga, Apple IIGS, and Acorn Archimedes, the ST is part of a mid-1980s generation of computers with 16- or 32-bit processors, 256 Kilobyte, KB or more of RAM, and computer mouse, mouse-controlled graphical user interfaces. The ST was ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Color Depth
Color depth or colour depth (see spelling differences), also known as bit depth, is either the number of bits used to indicate the color of a single pixel, or the number of bits used for each color component of a single pixel. When referring to a pixel, the concept can be defined as bits per pixel (bpp). When referring to a color component, the concept can be defined as bits per component, bits per channel, bits per color (all three abbreviated bpc), and also bits per pixel component, bits per color channel or bits per sample (bps). Modern standards tend to use bits per component, but historical lower-depth systems used bits per pixel more often. Color depth is only one aspect of color representation, expressing the precision with which the amount of each primary can be expressed; the other aspect is how broad a range of colors can be expressed (the gamut). The definition of both color precision and gamut is accomplished with a color encoding specification which assigns a digita ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ImageMagick
ImageMagick, invoked from the command line as magick, is a free and open-source cross-platform software suite for displaying, creating, converting, modifying, and editing raster images. Created in 1987 by John Cristy, it can read and write over 200 image file formats. It is widely used in open-source applications. History ImageMagick was created in 1987 by John Cristy when working at DuPont, to convert 24-bit images (16 million colors) to 8-bit images (256 colors), so they could be displayed on most screens at the time. It was freely released in 1990 when DuPont agreed to transfer copyright to ''ImageMagick Studio LLC'', still currently the project maintainer organization. In May 2016, it was reported that ImageMagick had a vulnerability through which an attacker can execute arbitrary code on servers that use the application to edit user-uploaded images. Security experts including CloudFlare researchers observed actual use of the vulnerability in active hacking attempts. The s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Netpbm
Netpbm (formerly Pbmplus) is an open-source package of graphics programs and a programming library. It is used mainly in the Unix world, where one can find it included in all major open-source operating system distributions, but also works on Microsoft Windows, macOS, and other operating systems. File formats Several graphics formats are used and defined by the Netpbm project. The portable pixmap format (PPM), the portable graymap format (PGM) and the portable bitmap format (PBM) are image file formats designed to be easily exchanged between platforms. They are also sometimes referred to collectively as the portable anymap format (PNM), not to be confused with the related portable arbitrary map format (PAM). The "magic number" (Px) at the beginning of a file determines the type, not the file extension, although it is best practice to use the right extension if possible. The PBM format was invented by Jef Poskanzer in the 1980s as a format that allowed monochrome bitmaps to be ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Convolutional Neural Networks
In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of artificial neural network (ANN), most commonly applied to analyze visual imagery. CNNs are also known as Shift Invariant or Space Invariant Artificial Neural Networks (SIANN), based on the shared-weight architecture of the convolution kernels or filters that slide along input features and provide translation-equivariant responses known as feature maps. Counter-intuitively, most convolutional neural networks are not invariant to translation, due to the downsampling operation they apply to the input. They have applications in image and video recognition, recommender systems, image classification, image segmentation, medical image analysis, natural language processing, brain–computer interfaces, and financial time series. CNNs are regularized versions of multilayer perceptrons. Multilayer perceptrons usually mean fully connected networks, that is, each neuron in one layer is connected to all neuron ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neural Networks
A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning resulting from e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Spiking Neural Networks
Spiking neural networks (SNNs) are artificial neural networks that more closely mimic natural neural networks. In addition to neuronal A neuron, neurone, or nerve cell is an electrically excitable cell that communicates with other cells via specialized connections called synapses. The neuron is the main component of nervous tissue in all animals except sponges and placozoa. No ... and Electrical synapse, synaptic state, SNNs incorporate the concept of time into their Operating Model, operating model. The idea is that Artificial neuron, neurons in the SNN do not transmit information at each propagation cycle (as it happens with typical multi-layer perceptron, perceptron networks), but rather transmit information only when a membrane potential – an intrinsic quality of the neuron related to its membrane electrical charge – reaches a specific value, called the threshold. When the membrane potential reaches the threshold, the neuron fires, and generates a signal th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Popcount
The Hamming weight of a string is the number of symbols that are different from the zero-symbol of the alphabet used. It is thus equivalent to the Hamming distance from the all-zero string of the same length. For the most typical case, a string of bits, this is the number of 1's in the string, or the digit sum of the binary representation of a given number and the ''ℓ''₁ norm of a bit vector. In this binary case, it is also called the population count, popcount, sideways sum, or bit summation. History and usage The Hamming weight is named after Richard Hamming although he did not originate the notion. The Hamming weight of binary numbers was already used in 1899 by James W. L. Glaisher to give a formula for the number of odd binomial coefficients in a single row of Pascal's triangle. Irving S. Reed introduced a concept, equivalent to Hamming weight in the binary case, in 1954. Hamming weight is used in several disciplines including information theory, coding theory, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bit Shift
In computer programming, a bitwise operation operates on a bit string, a bit array or a binary numeral (considered as a bit string) at the level of its individual bits. It is a fast and simple action, basic to the higher-level arithmetic operations and directly supported by the processor. Most bitwise operations are presented as two-operand instructions where the result replaces one of the input operands. On simple low-cost processors, typically, bitwise operations are substantially faster than division, several times faster than multiplication, and sometimes significantly faster than addition. While modern processors usually perform addition and multiplication just as fast as bitwise operations due to their longer instruction pipelines and other architectural design choices, bitwise operations do commonly use less power because of the reduced use of resources. Bitwise operators In the explanations below, any indication of a bit's position is counted from the right (least signi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Motion Estimation
Motion estimation is the process of determining ''motion vectors'' that describe the transformation from one 2D image to another; usually from adjacent frames in a video sequence. It is an ill-posed problem as the motion is in three dimensions but the images are a projection of the 3D scene onto a 2D plane. The motion vectors may relate to the whole image (global motion estimation) or specific parts, such as rectangular blocks, arbitrary shaped patches or even per pixel. The motion vectors may be represented by a translational model or many other models that can approximate the motion of a real video camera, such as rotation and translation in all three dimensions and zoom. Related terms More often than not, the term motion estimation and the term ''optical flow'' are used interchangeably. It is also related in concept to ''image registration'' and '' stereo correspondence''. In fact all of these terms refer to the process of finding corresponding points between two images or vi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
