1.
Pinhole camera model
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The model does not include, for example, geometric distortions or blurring of unfocused objects caused by lenses and finite sized apertures. It also does not take account that most practical cameras have only discrete image coordinates. This means that the camera model can only be used as a first order approximation of the mapping from a 3D scene to a 2D image. Its validity depends on the quality of the camera and, in general and this means that the pinhole camera model often can be used as a reasonable description of how a camera depicts a 3D scene, for example in computer vision and computer graphics. NOTE, The x1x2x3 coordinate system in the figure is left-handed, the geometry related to the mapping of a pinhole camera is illustrated in the figure. The figure contains the basic objects, A 3D orthogonal coordinate system with its origin at O. This is also where the aperture is located. The three axes of the system are referred to as X1, X2, X3. Axis X3 is pointing in the direction of the camera and is referred to as the optical axis, principal axis. The 3D plane which intersects with axes X1 and X2 is the front side of the camera, an image plane where the 3D world is projected through the aperture of the camera. The image plane is parallel to axes X1 and X2 and is located at distance f from the origin O in the direction of the X3 axis. A practical implementation of a pinhole camera implies that the plane is located such that it intersects the X3 axis at coordinate -f where f >0. F is also referred to as the length of the pinhole camera. A point R at the intersection of the axis and the image plane. This point is referred to as the point or image center. A point P somewhere in the world at coordinate relative to the axes X1, X2, the projection line of point P into the camera. This is the line which passes through point P and the point O. The projection of point P onto the plane, denoted Q
2.
JPEG
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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 size and image quality. JPEG typically achieves 10,1 compression with little loss in image quality. JPEG compression is used in a number of file formats. These format variations are not distinguished, and are simply called JPEG. The term JPEG is an initialism/acronym for the Joint Photographic Experts Group, the MIME media type for JPEG is image/jpeg, except in older Internet Explorer versions, which provides a MIME type of image/pjpeg when uploading JPEG images. JPEG files usually have an extension of. jpg or. jpeg. JPEG/JFIF supports a maximum size of 65, 535×65,535 pixels. JPEG stands for Joint Photographic Experts Group, the name of the committee created the JPEG standard. The Joint stood for ISO TC97 WG8 and CCITT SGVIII, in 1987 ISO TC97 became ISO/IEC JTC1 and in 1992 CCITT became ITU-T. Currently on the JTC1 side JPEG is one of two sub-groups of ISO/IEC Joint Technical Committee 1, Subcommittee 29, Working Group 1 – titled as Coding of still pictures, on the ITU-T side ITU-T SG16 is the respective body. The original JPEG group was organized in 1986, issuing the first JPEG standard in 1992, which was approved in September 1992 as ITU-T Recommendation T.81 and in 1994 as ISO/IEC 10918-1. The JPEG standard specifies the codec, which defines how an image is compressed into a stream of bytes and decompressed back into an image, the Exif and JFIF standards define the commonly used file formats for interchange of JPEG-compressed images. JPEG standards are formally named as Information technology – Digital compression, ISO/IEC10918 consists of the following parts, Ecma International TR/98 specifies the JPEG File Interchange Format, the first edition was published in June 2009. The JPEG compression algorithm is at its best on photographs and paintings of scenes with smooth variations of tone. For web usage, where the amount of used for an image is important. JPEG/Exif is also the most common format saved by digital cameras, on the other hand, JPEG may not be as well suited for line drawings and other textual or iconic graphics, where the sharp contrasts between adjacent pixels can cause noticeable artifacts. Such images may be saved in a lossless graphics format such as TIFF, GIF, PNG
3.
Black and white
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Black and white, often abbreviated B/W or B&W, and hyphenated black-and-white when used as an adjective, is any of several monochrome forms in visual arts. Black-and-white images are not usually starkly contrasted black and white and they combine black and white in a continuum producing a range of shades of gray. Even when most studios had the capability to make color films they were not heavily utilized as using the Technicolor process was expensive, for the years 1940–1966, a separate Academy Award for Best Art Direction was given for black-and-white movies along with one for color. Television, Television program was first transmitted in black-and-white, scottish inventor John Logie Baird demonstrated the worlds first color television transmission on July 3,1928 using a mechanical process. Some color broadcasts in the US began in the 1950s, with color becoming common in industrialized nations during the late 1960s. In the United States, the Federal Communications Commission settled on a color NTSC standard in 1953, color television became more widespread in the U. S. between 1963 and 1967, when the CBS and ABC networks joined NBC in broadcasting full color schedules. Canada began airing color television in 1966 while the United Kingdom began to use a different color system from July 1967 known as PAL. The Republic Of Ireland followed in 1970, in China, black and white television sets were the norm until as late as the 1990s, color TVs not outselling them until about 1989. While seldom used now, many consumer camcorders have the ability to record in black-and-white. Photography, Photographs were either black-and-white or shades of sepia, color photography was originally rare and expensive and again often containing inaccurate hues. Color photography became more common from the mid-20th century, Today, black-and-white is a niche market for photographers who use the medium for artistic purposes. This can take the form of film or digital conversion to grayscale. For amateur use certain companies such as Kodak manufactured black-and-white disposable cameras until 2009, also, certain films are produced today which give black-and-white images using the ubiquitous C41 color process. Printing press, Most American newspapers were black-and-white until the early 1980s, The New York Times, some claim that USA Today was the major impetus for the change to color. In the UK, color was only introduced from the mid-1980s. Even today, many newspapers restrict color photographs to the front, similarly, daily comic strips in newspapers were traditionally black-and-white with color reserved for Sunday strips. Sometimes color is reserved for the cover, magazines such as Jet magazine were either all or mostly black-and-white until the end of the 2000s when it became all-color. Manga are typically published in black-and-white although now it is part of its image, many school yearbooks are still entirely or mostly in black-and-white
4.
Night vision
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Night vision is the ability to see in low light conditions. Whether by biological or technological means, night vision is possible by a combination of two approaches, sufficient spectral range, and sufficient intensity range. Humans have poor night vision compared to animals, in part because the human eye lacks a tapetum lucidum. Night-useful spectral range techniques can sense radiation that is invisible to a human observer, human vision is confined to a small portion of the electromagnetic spectrum called visible light. Enhanced spectral range allows the viewer to take advantage of sources of electromagnetic radiation. Some animals such as the shrimp can see using much more of the infrared and/or ultraviolet spectrum than humans. Sufficient intensity range is simply the ability to see with very small quantities of light, many animals have better night vision than humans do, the result of one or more differences in the morphology and anatomy of their eyes. These include having a larger eyeball, a lens, a larger optical aperture, more rods than cones in the retina. Enhanced intensity range is achieved via technological means through the use of an image intensifier, gain multiplication CCD, or other very low-noise and high-sensitivity array of photodetectors. All photoreceptor cells in the eye contain molecules of photoreceptor protein which is a combination of the protein photopsin in color vision cells, rhodopsin in night vision cells, and retinal. The retinal must diffuse from the cell, out of the eye. In bright light conditions, most of the retinal is not in the photoreceptors and it takes about 45 minutes of dark for all of the photoreceptor proteins to be recharged with active retinal, but most of the night vision adaptation occurs within the first five minutes in the dark. Adaptation results in sensitivity to light. In dark conditions only the rod cells have enough sensitivity to respond, rhodopsin in the human rods is insensitive to the longer red wavelengths, so traditionally many people use red light to help preserve night vision. Red light only slowly depletes the rhodopsin stores in the rods, another theory posits that since stars typically emit light with shorter wavelengths, the light from stars will be in the blue-green color spectrum. Therefore, using red light to navigate would not desensitize the receptors used to detect star light, using red light for night vision is less effective for people with red–green color blindness, due to their insensitivity to red light. This is found in nocturnal animals and some deep sea animals. Humans, and monkeys, lack a tapetum lucidum, nocturnal mammals have rods with unique properties that make enhanced night vision possible
5.
Gaussian blur
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In image processing, a Gaussian blur is the result of blurring an image by a Gaussian function. It is a widely used effect in graphics software, typically to reduce image noise, mathematically, applying a Gaussian blur to an image is the same as convolving the image with a Gaussian function. This is also known as a two-dimensional Weierstrass transform, by contrast, convolving by a circle would more accurately reproduce the bokeh effect. Since the Fourier transform of a Gaussian is another Gaussian, applying a Gaussian blur has the effect of reducing the images high-frequency components, the Gaussian blur is a type of image-blurring filter that uses a Gaussian function for calculating the transformation to apply to each pixel in the image. When applied in two dimensions, this produces a surface whose contours are concentric circles with a Gaussian distribution from the center point. Values from this distribution are used to build a convolution matrix which is applied to the original image and this convolution process is illustrated visually in the figure on the right. Each pixels new value is set to an average of that pixels neighborhood. The original pixels value receives the heaviest weight and neighboring pixels receive smaller weights as their distance to the original pixel increases and this results in a blur that preserves boundaries and edges better than other, more uniform blurring filters, see also scale space implementation. In theory, the Gaussian function at every point on the image will be non-zero, in practice, when computing a discrete approximation of the Gaussian function, pixels at a distance of more than 3σ are small enough to be considered effectively zero. Thus contributions from pixels outside that range can be ignored, typically, an image processing program need only calculate a matrix with dimensions ⌈6 σ ⌉ × ⌈6 σ ⌉ to ensure a result sufficiently close to that obtained by the entire Gaussian distribution. In addition to being circularly symmetric, the Gaussian blur can be applied to an image as two independent one-dimensional calculations, and so is termed separable filter. In computational terms, this is a property, since the calculation can be performed in O + O time. For example, applying successive gaussian blurs with radii of 6 and 8 gives the results as applying a single gaussian blur of radius 10. Gaussian blurring is commonly used when reducing the size of an image, when downsampling an image, it is common to apply a low-pass filter to the image prior to resampling. This is to ensure that spurious high-frequency information does not appear in the downsampled image, Gaussian blurs have nice properties, such as having no sharp edges, and thus do not introduce ringing into the filtered image. Gaussian blur is a filter, attenuating high frequency signals. Its amplitude Bode plot is a parabola, how much does a Gaussian filter with standard deviation σ f smooth the picture. In other words, how much does it reduce the standard deviation of pixel values in the picture
6.
Peak signal-to-noise ratio
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Because many signals have a very wide dynamic range, PSNR is usually expressed in terms of the logarithmic decibel scale. PSNR is most commonly used to measure the quality of reconstruction of lossy compression codecs, the signal in this case is the original data, and the noise is the error introduced by compression. When comparing compression codecs, PSNR is an approximation to human perception of reconstruction quality, although a higher PSNR generally indicates that the reconstruction is of higher quality, in some cases it may not. One has to be careful with the range of validity of this metric, it is only conclusively valid when it is used to compare results from the same codec. PSNR is most easily defined via the mean squared error, when the pixels are represented using 8 bits per sample, this is 255. More generally, when samples are represented using linear PCM with B bits per sample, for color images with three RGB values per pixel, the definition of PSNR is the same except the MSE is the sum over all squared value differences divided by image size and by three. Alternately, for color images the image is converted to a different color space and PSNR is reported against each channel of that color space, e. g. YCbCr or HSL. Typical values for the PSNR in lossy image and video compression are between 30 and 50 dB, provided the bit depth is 8 bits, where higher is better, for 16-bit data typical values for the PSNR are between 60 and 80 dB. Acceptable values for wireless transmission quality loss are considered to be about 20 dB to 25 dB, in the absence of noise, the two images I and K are identical, and thus the MSE is zero. In this case the PSNR is infinite, data compression ratio Perceptual Evaluation of Video Quality Signal-to-noise ratio Structural similarity index Subjective video quality Video quality
7.
Netflix
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Netflix is an American entertainment company founded by Reed Hastings and Marc Randolph on August 29,1997, in Scotts Valley, California. It specializes in and provides streaming media and video-on-demand online and DVD by mail, in 2013, Netflix expanded into film and television production, as well as online distribution. As of 2017 the company has its headquarters in Los Gatos, Netflixs initial business model included DVD sales and rental, although Hastings jettisoned DVD sales about a year after Netflixs founding to focus on the DVD rental by mail business. In 2007, Netflix expanded its business with the introduction of streaming media, while retaining the DVD, Netflix entered the content-production industry in 2013, debuting its first series, House of Cards. It has greatly expanded the production of film and television series since then, offering Netflix Original content through its online library of films. Netflix released an estimated 126 original series or films in 2016, in January 2017, Netflix reported having over 93 million subscribers worldwide, including more than 49 million in the United States. Netflix was founded on August 29,1997, in Scotts Valley, California, by Marc Randolph, Randolph worked as marketing director for Hastings company, Pure Atria Corporation. Randolph was a co-founder of MicroWarehouse, a mail order company. Hastings, a computer scientist and mathematician, sold Pure Atria to Rational Software Corporation in 1997 for $700 million in what was then the richest acquisition in Silicon Valley history. Hastings, Randolphs mother and Integrity QA founder Steve Kahn invested $2.5 million in cash for Netflix. Randolph admired the fledgling e-commerce company Amazon and wanted to find a category of portable items to sell over the internet using a similar model. He and Hastings considered and rejected VHS tapes as too expensive to stock and too delicate to ship. When they heard about DVDs, which were available in only a few markets in 1997, when the disc arrived intact, they decided to take on the $16 billion home video sales and rental industry. Netflix introduced the monthly subscription concept in September 1999, and then dropped the model in early 2000. Since that time, the company has built its reputation on the model of flat-fee unlimited rentals without due dates, late fees, shipping and handling fees. In 2000, Netflix offered to be acquired by Blockbuster for $50 million, Netflix initiated an initial public offering on May 29,2002, selling 5.5 million shares of common stock at the price of US$15.00 per share. On June 14,2002, the company sold an additional 825,000 shares of stock at the same price. After incurring substantial losses during its first few years, Netflix posted its first profit during fiscal year 2003, in 2005,35,000 different films were available, and Netflix shipped 1 million DVDs out every day
8.
Sharpness (visual)
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In photography, the term acutance describes a subjective perception of sharpness that is related to the edge contrast of an image. Acutance is related to the amplitude of the derivative of brightness with respect to space, due to the nature of the human visual system, an image with higher acutance appears sharper even though an increase in acutance does not increase real resolution. Historically, acutance was enhanced chemically during development of a negative, in the example image, two light gray lines were drawn on a gray background. As the transition is instantaneous, the line is as sharp as can be represented at this resolution, acutance in the left line was artificially increased by adding a one-pixel-wide darker border on the outside of the line and a one-pixel-wide brighter border on the inside of the line. The actual sharpness of the image is unchanged, but the apparent sharpness is increased because of the greater acutance. In this somewhat overdone example most viewers will also be able to see the borders separately from the line, several image processing techniques, such as unsharp masking, can increase the acutance in real images. Low-pass filtering and resampling often cause overshoot, which increases acutance, but can also reduce absolute gradient, filtering and resampling can also cause clipping and ringing artifacts. An example is bicubic interpolation, widely used in processing for resizing images. Thus the acutance of an image is a vector field, coarse grain or noise can, like sharpening filters, increase acutance, hence increasing the perception of sharpness, even though they degrade the signal-to-noise ratio
9.
Image noise
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Image noise is random variation of brightness or color information in images, and is usually an aspect of electronic noise. It can be produced by the sensor and circuitry of a scanner or digital camera, image noise can also originate in film grain and in the unavoidable shot noise of an ideal photon detector. Image noise is an undesirable by-product of image capture that adds spurious and extraneous information, the original meaning of noise was and remains unwanted signal, unwanted electrical fluctuations in signals received by AM radios caused audible acoustic noise. By analogy unwanted electrical fluctuations themselves came to be known as noise, image noise is, of course, inaudible. Principal sources of Gaussian noise in digital images arise during acquisition e. g. sensor noise caused by poor illumination and/or high temperature, and/or transmission e. g. electronic circuit noise. Amplifier noise is a part of the read noise of an image sensor. In color cameras where more amplification is used in the blue color channel than in the green or red channel, at higher exposures, however, image sensor noise is dominated by shot noise, which is not Gaussian and not independent of signal intensity. Fat-tail distributed or impulsive noise is sometimes called salt-and-pepper noise or spike noise, an image containing salt-and-pepper noise will have dark pixels in bright regions and bright pixels in dark regions. This type of noise can be caused by analog-to-digital converter errors, bit errors in transmission and it can be mostly eliminated by using dark frame subtraction, median filtering and interpolating around dark/bright pixels. Dead pixels in an LCD monitor produce a similar, but non-random and this noise is known as photon shot noise. Shot noise has a value proportional to the square root of the image intensity. Shot noise follows a Poisson distribution, which except at low intensity levels approximates a Gaussian distribution. In addition to shot noise, there can be additional shot noise from the dark leakage current in the image sensor. Dark current is greatest at hot pixels within the image sensor, the variable dark charge of normal and hot pixels can be subtracted off, leaving only the shot noise, or random component, of the leakage. The noise caused by quantizing the pixels of an image to a number of discrete levels is known as quantization noise. It has a uniform distribution. Though it can be dependent, it will be signal independent if other noise sources are big enough to cause dithering. The grain of film is a signal-dependent noise, with similar statistical distribution to shot noise
10.
Dynamic range
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Dynamic range, abbreviated DR, DNR, or DYR is the ratio between the largest and smallest values that a certain quantity can assume. It is often used in the context of signals, like sound and it is measured either as a ratio or as a base-10 or base-2 logarithmic value of the difference between the smallest and largest signal values, in parallel to the common usage for audio signals. The human senses of sight and hearing have a high dynamic range. A human is capable of hearing anything from a quiet murmur in a room to the sound of the loudest heavy metal concert. Such a difference can exceed 100 dB which represents a factor of 100,000 in amplitude, a human cannot perform these feats of perception at both extremes of the scale at the same time. The eyes take time to adjust to different light levels, the instantaneous dynamic range of human audio perception is similarly subject to masking so that, for example, a whisper cannot be heard in loud surroundings. In practice, it is difficult to achieve the full dynamic range experienced by humans using electronic equipment. For example, a good quality LCD has a range of around 1000,1. Paper reflectance can achieve a range of about 100,1. A professional ENG camcorder such as the Sony Digital Betacam achieves a range of greater than 90 dB in audio recording. A nighttime scene will usually contain duller colours and will often be lit with blue lighting, the dynamic range of human hearing is roughly 140 dB, varying with frequency, from the threshold of hearing to the threshold of pain. The dynamic range of music as normally perceived in a concert hall doesnt exceed 80 dB, the dynamic range differs from the ratio of the maximum to minimum amplitude a given device can record, as a properly dithered recording device can record signals well below the noise RMS amplitude. Digital audio with undithered 20-bit digitization is theoretically capable of 120 dB dynamic range, 24-bit digital audio calculates to 144 dB dynamic range. Multiple noise processes determine the noise floor of a system, noise can be picked up from microphone self-noise, preamp noise, wiring and interconnection noise, media noise, etc. Early 78 rpm phonograph discs had a range of up to 40 dB, soon reduced to 30 dB. Ampex tape recorders in the 1950s achieved 60 dB in practical usage, the peak of professional analog magnetic recording tape technology reached 90 dB dynamic range in the midband frequencies at 3% distortion, or about 80 dB in practical broadband applications. The Dolby SR noise reduction gave a 20 dB further increased range resulting in 110 dB in the midband frequencies at 3% distortion. Specialized bias and record head improvements by Nakamichi and Tandberg combined with Dolby C noise reduction yielded 72 dB dynamic range for the cassette
11.
Luminance
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Luminance is a photometric measure of the luminous intensity per unit area of light travelling in a given direction. It describes the amount of light passes through, is emitted or reflected from a particular area. The SI unit for luminance is candela per square metre, a non-SI term for the same unit is the nit. The CGS unit of luminance is the stilb, which is equal to one candela per square centimetre or 10 kcd/m2, luminance is often used to characterize emission or reflection from flat, diffuse surfaces. The luminance indicates how much power will be detected by an eye looking at the surface from a particular angle of view. Luminance is thus an indicator of how bright the surface will appear, in this case, the solid angle of interest is the solid angle subtended by the eyes pupil. Luminance is used in the industry to characterize the brightness of displays. A typical computer display emits between 50 and 300 cd/m2, the sun has luminance of about 1. 6×109 cd/m2 at noon. Luminance is invariant in geometric optics and this means that for an ideal optical system, the luminance at the output is the same as the input luminance. For real, passive, optical systems, the luminance is at most equal to the input. As an example, if one uses a lens to form an image that is smaller than the source object, the luminous power is concentrated into a smaller area, meaning that the illuminance is higher at the image. The light at the plane, however, fills a larger solid angle so the luminance comes out to be the same assuming there is no loss at the lens. The image can never be brighter than the source, if light travels through a lossless medium, the luminance does not change along a given light ray. In the case of a perfectly diffuse reflector, the luminance is isotropic, then the relationship is simply L v = E v R / π A variety of units have been used for luminance, besides the candela per square metre. One candela per square metre is equal to, 10−4 stilbs π apostilbs π×10−4 lamberts 0.292 foot-lamberts Retinal damage can occur when the eye is exposed to high luminance, damage can occur due to local heating of the retina. Photochemical effects can cause damage, especially at short wavelengths. Also available in PDF form and Google Docs online version Autodesk Design Academy Measuring Light Levels
12.
Contrast (vision)
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Contrast is the difference in luminance or colour that makes an object distinguishable. In visual perception of the world, contrast is determined by the difference in the color and brightness of the object. The human visual system is sensitive to contrast than absolute luminance. The maximum contrast of an image is the contrast ratio or dynamic range, the human contrast sensitivity function shows a typical band-pass filter shape peaking at around 4 cycles per degree with sensitivity dropping off either side of the peak. The high-frequency cut-off represents the optical limitations of the systems ability to resolve detail and is typically about 60 cycles per degree. The high-frequency cut-off is related to the density of the retinal photoreceptor cells. The low frequency drop-off is due to lateral inhibition within the ganglion cells. A typical retinal ganglion cell presents a centre region with either excitation or inhibition, one experimental phenomenon is the inhibition of blue in the periphery if blue light is displayed against white, leading to a yellow surrounding. The yellow is derived from the inhibition of blue on the surroundings by the center, since white minus blue is red and green, this mixes to become yellow. For example, in the case of computer displays, contrast depends on the properties of the picture source or file. For some screens the angle between the surface and the observers line of sight is also important. There are many definitions of contrast. Some include color, others do not, travnikova laments, Such a multiplicity of notions of contrast is extremely inconvenient. It complicates the solution of many applied problems and makes it difficult to compare the results published by different authors, various definitions of contrast are used in different situations. Here, luminance contrast is used as an example, but the formulas can also be applied to other physical quantities, in many cases, the definitions of contrast represent a ratio of the type Luminance difference Average luminance. The rationale behind this is that a difference is negligible if the average luminance is high. Below, some definitions are given. Weber contrast is defined as I − I b I b, with I and I b representing the luminance of the features, the measure is also referred to as Weber fraction, since it is the term that is constant in Webers Law
13.
Gamma correction
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Gamma correction, or often simply gamma, is the name of a nonlinear operation used to encode and decode luminance or tristimulus values in video or still image systems. In the common case of A =1, inputs and outputs are typically in the range 0–1, Gamma encoding of floating-point images is not required, because the floating-point format already provides a piecewise linear approximation of a logarithmic curve. Although gamma encoding was developed originally to compensate for the characteristic of cathode ray tube displays. In CRT displays, the intensity varies nonlinearly with the electron-gun voltage. Altering the input signal by gamma compression can cancel this nonlinearity, the similarity of CRT physics to the inverse of gamma encoding needed for video transmission was a combination of luck and engineering, which simplified the electronics in early television sets. The concept of gamma can be applied to any nonlinear relationship, for a power-law curve, this slope is constant, but the idea can be extended to any type of curve, in which case gamma is defined as the slope of the curve in any particular region. For a given film formulation and processing method, this curve is its characteristic or Hurter–Driffield curve, since both axes use logarithmic units, the slope of the linear section of the curve is called the gamma of the film. Negative film typically has a less than 1, positive film typically has a gamma greater than 1. Photographic film has a greater ability to record fine differences in shade than can be reproduced on photographic paper. Similarly, most video screens are not capable of displaying the range of brightnesses that can be captured by typical electronic cameras, for this reason, considerable artistic effort is invested in choosing the reduced form in which the original image should be presented. The gamma correction, or contrast selection, is part of the repertoire used to adjust the reproduced image. Analogously, digital cameras record light using electronic sensors that usually respond linearly, in the process of rendering linear raw data to conventional RGB data, color space transformations and rendering transformations will be performed. In most computer systems, images are encoded with a gamma of about 0.45. A notable exception, until the release of Mac OS X10.6 in September 2009, were Macintosh computers, in any case, binary data in still image files are explicitly encoded, as are motion picture files. The system can optionally further manage both cases, through management, if a better match to the output device gamma is required. Below a compressed value of 0.04045 or a linear intensity of 0.00313, the dashed black curve behind the red curve is a standard γ =2.2 power-law curve, for comparison. For television signals, the actual values are defined by the video standards. A gamma characteristic is a relationship that approximates the relationship between the encoded luma in a television system and the actual desired image luminance
14.
Color
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Color or colour is the characteristic of human visual perception described through color categories, with names such as red, yellow, purple, or blue. This perception of color derives from the stimulation of cells in the human eye by electromagnetic radiation in the spectrum of light. Color categories and physical specifications of color are associated with objects through the wavelength of the light that is reflected from them and this reflection is governed by the objects physical properties such as light absorption, emission spectra, etc. By defining a color space, colors can be identified numerically by coordinates, there may also be more than three color dimensions in other color spaces, such as in the CMYK color model, wherein one of the dimensions relates to a colours colorfulness). The photo-receptivity of the eyes of species also varies considerably from our own. Honeybees and bumblebees for instance have trichromatic color vision sensitive to ultraviolet but is insensitive to red, papilio butterflies possess six types of photoreceptors and may have pentachromatic vision. The most complex color vision system in the kingdom has been found in stomatopods with up to 12 spectral receptor types thought to work as multiple dichromatic units. The science of color is sometimes called chromatics, colorimetry, or simply color science and it includes the perception of color by the human eye and brain, the origin of color in materials, color theory in art, and the physics of electromagnetic radiation in the visible range. Electromagnetic radiation is characterized by its wavelength and its intensity, when the wavelength is within the visible spectrum, it is known as visible light. Most light sources emit light at different wavelengths, a sources spectrum is a distribution giving its intensity at each wavelength. Although the spectrum of light arriving at the eye from a given direction determines the color sensation in that direction, in each such class the members are called metamers of the color in question. The table at right shows approximate frequencies and wavelengths for various pure spectral colors, the wavelengths listed are as measured in air or vacuum. A common list identifies six main bands, red, orange, yellow, green, blue, Newtons conception included a seventh color, indigo, between blue and violet. It is possible that what Newton referred to as blue is nearer to what today is known as cyan, the color of an object depends on both the physics of the object in its environment and the characteristics of the perceiving eye and brain. Some objects not only light, but also transmit light or emit light themselves. This effect is known as color constancy, opaque objects that do not reflect specularly have their color determined by which wavelengths of light they scatter strongly. If objects scatter all wavelengths with roughly equal strength, they appear white, if they absorb all wavelengths, they appear black. Opaque objects that reflect light of different wavelengths with different efficiencies look like mirrors tinted with colors determined by those differences
15.
Distortion (optics)
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In geometric optics, distortion is a deviation from rectilinear projection, a projection in which straight lines in a scene remain straight in an image. It is a form of optical aberration, although distortion can be irregular or follow many patterns, the most commonly encountered distortions are radially symmetric, or approximately so, arising from the symmetry of a photographic lens. These radial distortions can usually be classified as either barrel distortions or pincushion distortions, mathematically, barrel and pincushion distortion are quadratic, meaning they increase as the square of distance from the center. Barrel distortion may be found in wide-angle lenses, and is seen at the wide-angle end of zoom lenses. Mustache distortion is observed particularly on the end of zooms, with certain retrofocus lenses. A certain amount of distortion is often found with visual optical instruments, e. g. binoculars. A graph showing radius transformations will be steeper in the upper end, conversely, barrel distortion is actually a diminished radius mapping for large radii in comparison with small radii. A graph showing radius transformations will be less steep in the upper end, radial distortion that depends on wavelength is called lateral chromatic aberration – lateral because radial, chromatic because dependent on color. This can cause colored fringes in high-contrast areas in the parts of the image. This should not be confused with axial chromatic aberration, which causes aberrations throughout the field, the names for these distortions come from familiar objects which are visually similar. Radial distortion, whilst primarily dominated by low order radial components, can be corrected using Browns distortion model, the Brown–Conrady model corrects both for radial distortion and for tangential distortion caused by physical elements in a lens not being perfectly aligned. The latter is known as decentering distortion. See Zhang for radial distortion discussion, barrel distortion typically will have a negative term for K1 whereas pincushion distortion will have a positive value. Moustache distortion will have a non-monotonic radial geometric series where for some r the sequence will change sign, software can correct those distortions by warping the image with a reverse distortion. This involves determining which distorted pixel corresponds to each undistorted pixel, lateral chromatic aberration can be significantly reduced by applying such warping for red, green and blue separately. An alternative method iteratively computes the undistorted pixel position, calibrated systems work from a table of lens/camera transfer functions, Adobe Photoshop Lightroom and Photoshop CS5 can correct complex distortion. PTlens is a Photoshop plugin or standalone application which corrects complex distortion and it not only corrects for linear distortion, but also second degree and higher nonlinear components. Lensfun is a free to use database and library for correcting lens distortion, dxO Labs Optics Pro can correct complex distortion, and takes into account the focus distance
16.
Lenses for SLR and DSLR cameras
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This article is about photographic lenses for single-lens reflex film cameras and digital single-lens reflex cameras. Emphasis is on modern lenses for 35 mm film SLRs and for DSLRs with sensor sizes less than or equal to 35 mm, most SLR and DSLR cameras provide the option of changing the lens. This enables the use of lens that are best suited for the current photographic need, DSLRs became affordable around the mid-1990s, and have become extremely popular in recent years. Others, for example Olympus, chose to create a new lens mount. The Pentax SLR camera K-mount system is compatible to all previous lens generations from Pentax, including the latest digital SLRs like the K-3. A Pentax K-mount lens from the early 70s can be used on the newest Pentax DSLR although it may not provide features that are included in newer lenses. There are a few exceptions from the MZ and ZX series of Pentax film cameras that do not work with some of the older lenses, as implied by the above, lenses are only directly interchangeable within the mount system for which they are built. Mixing mounting systems requires an adapter, and most often results in such as loss of functionality. Further, in cases the adapter will require an additional optical element to correct for varied registration distances. Adapters may not be available to every combination of lens mount. The aperture of a lens is the opening that regulates the amount of light passes through the lens. It is controlled by a diaphragm inside the lens, which is in turn controlled either manually or by the circuitry in the camera body. The relative aperture is specified as an f-number, the ratio of the focal length to its effective aperture diameter. A small f-number like f/2.0 indicates a large aperture, aperture settings are usually not continuously variable, instead the diaphragm has typically 5–10 discrete settings. The normal full-stop f-number scale for modern lenses is as follows,1,1.4,2,2.8,4,5.6,8,11,16,22,32, but many lenses also allow setting to half-stop or third-stop increments. A slow lens might have an aperture from 5.6 to 11. Fast lenses are by definition larger than slow lenses, and typically cost more, the focal length of a lens, together with the size of the image sensor in the camera, determines the angle of view. A lens is considered to be a lens, in terms of its angle of view on a camera
17.
Vignetting
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In photography and optics, vignetting is a reduction of an images brightness or saturation at the periphery compared to the image center. The word vignette, from the root as vine, originally referred to a decorative border in a book. Later, the word came to be used for a portrait which is clear in the center. A similar effect occurs when photographing projected images or movies off a projection screen, vignetting is often an unintended and undesired effect caused by camera settings or lens limitations. However, it is deliberately introduced for creative effect, such as to draw attention to the center of the frame. A photographer may deliberately choose a lens which is known to produce vignetting to obtain the effect, when using superzoom lenses, vignetting may occur all along the zoom range, depending on the aperture and the focal length. However, it may not always be visible, except at the widest end, in these cases, vignetting may cause an exposure value difference of up to 0. 75EV. There are several causes of vignetting and this has the effect of changing the entrance pupil shape as a function of angle. Darkening can be gradual or abrupt – the smaller the aperture, when some points on an image receives no light at all due to mechanical vignetting, then this results in an restriction of the field of view – parts of the image are then completely black. This type of vignetting is caused by the dimensions of a multiple element lens. Rear elements are shaded by elements in front of them, which reduces the lens opening for off-axis incident light. The result is a decrease in light intensity towards the image periphery. Optical vignetting is sensitive to the aperture and can often be cured by a reduction in aperture of 2–3 stops. Unlike the previous types, natural vignetting is not due to the blocking of light rays, the falloff is approximated by the cos4 or cosine fourth law of illumination falloff. Here, the light falloff is proportional to the power of the cosine of the angle at which the light impinges on the film or sensor array. Wideangle rangefinder designs and the designs used in compact cameras are particularly prone to natural vignetting. Telephoto lenses, retrofocus wideangle lenses used on SLR cameras, a gradual grey filter or postprocessing techniques may be used to compensate for natural vignetting, as it cannot be cured by stopping down the lens. Some modern lenses are designed so that the light strikes the image parallel or nearly so
18.
Exposure (photography)
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In photography, exposure is the amount of light per unit area reaching a photographic film or electronic image sensor, as determined by shutter speed, lens aperture and scene luminance. Exposure is measured in lux seconds, and can be computed from exposure value, in photographic jargon, an exposure generally refers to a single shutter cycle. For the same speed, the accumulated photometric exposure should be similar in both cases. A photograph may be described as underexposed when it has a loss of detail, that is. As the adjacent image shows, these terms are technical ones, there are three types of settings, manual, automatic and exposure compensation. Radiant exposure of a surface, denoted He and measured in J/m2, is given by H e = E e t, where Ee is the irradiance of the surface, measured in W/m2, t is the exposure duration, measured in s. Luminous exposure of a surface, denoted Hv and measured in lx⋅s, is given by H v = E v t, many photographic materials are also sensitive to invisible light, which can be a nuisance, or a benefit. The use of units is appropriate to characterize such sensitivity to invisible light. In sensitometric data, such as curves, the log exposure is conventionally expressed as log10. Photographers more familiar with base-2 logarithmic scales can convert using log2 ≈3.32 log10, correct exposure may be defined as an exposure that achieves the effect the photographer intended. A more technical approach recognises that a film has a physically limited useful exposure range. If, for any part of the photograph, the exposure is outside this range. In a very simple model, for example, out-of-range values would be recorded as black or white rather than the precisely graduated shades of colour and this ensures that no significant information is lost during capture. However, it is much easier to discard recorded information during post processing than to try to re-create unrecorded information. In a scene with strong or harsh lighting, the ratio between highlight and shadow luminance values may well be larger than the ratio between the maximum and minimum useful exposure values. A photograph may be described as underexposed when it has a loss of detail, that is. In manual mode, the photographer adjusts the lens aperture and/or shutter speed to achieve the desired exposure, manual exposure calculations may be based on some method of light metering with a working knowledge of exposure values, the APEX system and/or the Zone System. A camera in automatic exposure mode automatically calculates and adjusts exposure settings to match the subjects mid-tone to the mid-tone of the photograph, for most cameras this means using an on-board TTL exposure meter
19.
Chromatic aberration
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In optics, chromatic aberration is an effect resulting from dispersion in which there is a failure of a lens to focus all colors to the same convergence point. It occurs because lenses have different refractive indices for different wavelengths of light, the refractive index of transparent materials decreases with increasing wavelength in degrees unique to each. Since the focal length f of a lens is dependent on the index n. There are two types of aberration, axial, and transverse. Axial aberration occurs when different wavelengths of light are focused at different distances from the lens, transverse aberration occurs when different wavelengths are focused at different positions in the focal plane. The acronym LCA is used, but ambiguous, and may refer to either longitudinal or lateral CA, for clarity and these two types have different characteristics, and may occur together. Axial CA occurs throughout the image and is specified by optical engineers, optometrists, and vision scientists in the unit of focus known widely as diopters, transverse CA does not occur in the center, and increases towards the edge, but is not affected by stopping down. In the earliest uses of lenses, chromatic aberration was reduced by increasing the length of the lens where possible. For example, this could result in extremely long telescopes such as the very long aerial telescopes of the 17th century, isaac Newtons theories about white light being composed of a spectrum of colors led him to the conclusion that uneven refraction of light caused chromatic aberration. There exists a point called the circle of least confusion, where chromatic aberration can be minimized and it can be further minimized by using an achromatic lens or achromat, in which materials with differing dispersion are assembled together to form a compound lens. The most common type is a doublet, with elements made of crown. This reduces the amount of chromatic aberration over a range of wavelengths. By combining more than two lenses of different composition, the degree of correction can be increased, as seen in an apochromatic lens or apochromat. Similarly, the benefit of apochromats is not simply that they focus 3 wavelengths sharply, many types of glass have been developed to reduce chromatic aberration. These are low dispersion glass, most notably, glasses containing fluorite and these hybridized glasses have a very low level of optical dispersion, only two compiled lenses made of these substances can yield a high level of correction. The use of achromats was an important step in the development of the optical microscope, an alternative to achromatic doublets is the use of diffractive optical elements. Diffractive optical elements are able to generate arbitrary complex wave fronts from a sample of material which is essentially flat. Diffractive optical elements have negative characteristics, complementary to the positive Abbe numbers of optical glasses
20.
Purple fringing
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In photography, and particularly in digital photography, purple fringing is the term for an out-of-focus purple or magenta ghost image on a photograph. This defect is generally most visible as a coloring and lightening of dark edges adjacent to areas of broad-spectrum illumination. Lenses in general exhibit axial chromatic aberration in which different colors of light do not focus in the same plane, normally, lens designs are optimized so that two or more wavelengths of light in the visible range focus at the same plane. Lens performance may be poor for such wavelengths in other ways too, most film has relatively low sensitivity to colors outside the visible range, so light spread in the near ultraviolet or near infrared rarely has a significant impact on the image recorded. However, sensors used in digital cameras commonly are sensitive to a range of wavelengths. Bright cloudy or hazy skies are strong sources of scattered violet and UV light, the term purple fringe used to describe one aspect of chromatic aberration dates back to at least 1833. However, Brewsters description with a fringe on one edge. A general defocus of the shortest wavelengths resulting in a fringe on all sides of a bright object is the result of an axial or longitudinal chromatic aberration. Quite often these effects are mixed in an image, purple fringing is usually attributed to chromatic aberration as described above, although it is not clear that all purple fringing can be explained this way. Shoot with a Haze-2A or other strong UV-cut filter, post-processing to remove purple fringing usually involves scaling the fringed colour channel, or subtracting some of a scaled version of the blue channel, or other blue-channel tricks
21.
Demosaicing
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A demosaicing algorithm is a digital image process used to reconstruct a full color image from the incomplete color samples output from an image sensor overlaid with a color filter array. It is also known as CFA interpolation or color reconstruction, most modern digital cameras acquire images using a single image sensor overlaid with a CFA, so demosaicing is part of the processing pipeline required to render these images into a viewable format. Many modern digital cameras can save images in a raw format allowing the user to demosaic them using software, the aim of a demosaicing algorithm is to reconstruct a full color image from the spatially undersampled color channels output from the CFA. Commercially, the most commonly used CFA configuration is the Bayer filter illustrated here and this has alternating red and green filters for odd rows and alternating green and blue filters for even rows. There are twice as many green filters as red or blue ones, since each pixel of the sensor is behind a color filter, the output is an array of pixel values, each indicating a raw intensity of one of the three filter colors. Thus, an algorithm is needed to estimate for each pixel the color levels for all color components, to reconstruct a full color image from the data collected by the color filtering array, a form of interpolation is needed to fill in the blanks. The mathematics here is subject to implementation, and is called demosaicing. In this example, we use Adobe Photoshops bicubic interpolation to simulate the circuitry of a Bayer filter device such as a digital camera, the image below simulates the output from a Bayer filtered image sensor, each pixel has only a red, green or blue component. The corresponding original image is shown alongside the demosaiced reconstruction at the end of this section, a digital camera typically has means to reconstruct a whole RGB image using the above information. The resulting image could be something like this, The reconstructed image is accurate in uniform-colored areas. These algorithms are examples of multivariate interpolation on a uniform grid, the simplest method is nearest-neighbor interpolation which simply copies an adjacent pixel of the same color channel. It is unsuitable for any application where quality matters, but can be useful for generating previews given limited computational resources. Another simple method is bilinear interpolation, whereby the red value of a pixel is computed as the average of the two or four adjacent red pixels, and similarly for blue and green. More complex methods that interpolate independently within each color plane include bicubic interpolation, spline interpolation, although these methods can obtain good results in homogenous image regions, they are prone to severe demosaicing artifacts in regions with edges and details when used with pure-color CFAs. However, linear interpolation can obtain good results when combined with a spatio-spectral CFA. One could exploit simple formation models of images for demosaicing, in natural images within the same segment, the ratio of colors should be preserved. This fact was exploited in an image sensitive interpolation for demosaicing, more sophisticated demosaicing algorithms exploit the spatial and/or spectral correlation of pixels within a color image. Spatial correlation is the tendency of pixels to assume similar color values within a small region of an image
22.
Lens flare
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Lens flare refers to a phenomenon wherein light is scattered or flared in a lens system, often in response to a bright light, producing a desirable effect on the image. This happens through unintentional image formation mechanisms, such as internal reflection, lenses with large numbers of elements such as zooms tend to exhibit greater lens flare, as they contain multiple surfaces at which unwanted internal scattering occurs. These mechanisms differ from the image formation mechanism, which depends on rays from the refraction of the image itself. Flare manifests itself in two ways, as visible artifacts, and as a haze across the image, the haze makes the image look washed out by reducing contrast and color saturation. Visible artifacts, usually in the shape of the iris, are formed when light follows a pathway through the lens that contains one or more reflections from the lens surfaces. Flare is particularly caused by bright light sources. Most commonly, this occurs when shooting into the sun, and is reduced by using a hood or other shade. For good-quality optical systems, and for most images, flare is an effect that is widely distributed across the image and thus not visible. The spatial distribution of the lens flare typically manifests as several starbursts, rings, the specific spatial distribution of the flare depends on the shape of the aperture of the image formation elements. For example, if the lens has a 6-bladed aperture, the flare may have a hexagonal pattern, such internal scattering is also present in the human eye, and manifests in an unwanted veiling glare most obvious when viewing very bright lights or highly reflective surfaces. In some situations, eyelashes can also create flare-like irregularities, although these are technically diffraction artifacts, when a bright light source is shining on the lens but not in its field of view, lens flare appears as a haze that washes out the image and reduces contrast. This can be avoided by shading the lens using a lens hoods, in a studio, a gobo or set of barn doors can be attached to the lighting to keep it from shining on the camera. Filters can be attached to the lens which will also minimise lens flare. When using a lens, as is common in analog cinematography. This is most commonly seen in car headlights in a dark scene, a lens flare is often deliberately used to invoke a sense of drama. For both of these reasons artificial lens flare is an effect in various graphics editing programs. Lens flare was one of the first special effects developed for computer graphics because it can be imitated using relatively simple means, more sophisticated rendering techniques have been developed based on ray tracing or photon mapping. S. Costume designer Rita Riggs purposefully would sometimes dress Bea Arthur in Maude in a red that would flare to make a statement, director J. J. Abrams added numerous lens flares to the 2009 film Star Trek by aiming powerful off-camera light sources at the lens
23.
Compression artifact
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A compression artifact is a noticeable distortion of media caused by the application of lossy compression. Lossy data compression involves discarding some of the data so that it becomes simplified enough to be stored within the desired disk space or be transmitted within the bandwidth limitations. If the compressor could not reproduce enough data in the version to reproduce the original. Alternatively, the algorithm may not be intelligent enough to discriminate between distortions of little subjective importance and those objectionable to the viewer. Compression artifacts occur in common media such as DVDs, common computer file formats such as JPEG, MP3, or MPEG files. Uncompressed media or losslessly compressed media do not suffer from compression artifacts, the minimization of perceivable artifacts is a key goal in implementing a lossy compression algorithm. However, artifacts are occasionally intentionally produced for artistic purposes, a known as glitch art or datamoshing. Technically speaking, an artifact is a particular class of data error that is usually the consequence of quantization in lossy data compression. Where transform coding is used, they assume the form of one of the basis functions of the coders transform space. When performing block-based coding for quantization, as in JPEG-compressed images, for example, the numbers 6 and 8 may get replaced. This has been observed to happen with JBIG2 in certain photocopier machines, at low bit rates, any lossy block-based coding scheme introduces visible artifacts in pixel blocks and at block boundaries. These boundaries can be transform block boundaries, prediction block boundaries, the term macroblocking is commonly used regardless of the artifacts cause. Other names include tiling, mosaicing, pixelating, quilting, block-artifacts are a result of the very principle of block transform coding. The transform is applied to a block of pixels, and to achieve lossy compression, the lower the bit rate, the more coarsely the coefficients are represented and the more coefficients are quantized to zero. Statistically, images have more low-frequency than high-frequency content, so it is the content that remains after quantization. Because this quantization process is applied individually in each block, neighboring blocks quantize coefficients differently and this leads to discontinuities at the block boundaries. These are most visible in areas, where there is little detail to mask the effect. Many photo editing programs, for instance, have proprietary JPEG artifact reduction algorithms built-in, consumer equipment often calls this post-processing MPEG Noise Reduction
24.
International Standard Serial Number
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An International Standard Serial Number is an eight-digit serial number used to uniquely identify a serial publication. The ISSN is especially helpful in distinguishing between serials with the same title, ISSN are used in ordering, cataloging, interlibrary loans, and other practices in connection with serial literature. The ISSN system was first drafted as an International Organization for Standardization international standard in 1971, ISO subcommittee TC 46/SC9 is responsible for maintaining the standard. When a serial with the content is published in more than one media type. For example, many serials are published both in print and electronic media, the ISSN system refers to these types as print ISSN and electronic ISSN, respectively. The format of the ISSN is an eight digit code, divided by a hyphen into two four-digit numbers, as an integer number, it can be represented by the first seven digits. The last code digit, which may be 0-9 or an X, is a check digit. Formally, the form of the ISSN code can be expressed as follows, NNNN-NNNC where N is in the set, a digit character. The ISSN of the journal Hearing Research, for example, is 0378-5955, where the final 5 is the check digit, for calculations, an upper case X in the check digit position indicates a check digit of 10. To confirm the check digit, calculate the sum of all eight digits of the ISSN multiplied by its position in the number, the modulus 11 of the sum must be 0. There is an online ISSN checker that can validate an ISSN, ISSN codes are assigned by a network of ISSN National Centres, usually located at national libraries and coordinated by the ISSN International Centre based in Paris. The International Centre is an organization created in 1974 through an agreement between UNESCO and the French government. The International Centre maintains a database of all ISSNs assigned worldwide, at the end of 2016, the ISSN Register contained records for 1,943,572 items. ISSN and ISBN codes are similar in concept, where ISBNs are assigned to individual books, an ISBN might be assigned for particular issues of a serial, in addition to the ISSN code for the serial as a whole. An ISSN, unlike the ISBN code, is an identifier associated with a serial title. For this reason a new ISSN is assigned to a serial each time it undergoes a major title change, separate ISSNs are needed for serials in different media. Thus, the print and electronic versions of a serial need separate ISSNs. Also, a CD-ROM version and a web version of a serial require different ISSNs since two different media are involved, however, the same ISSN can be used for different file formats of the same online serial
25.
Omnidirectional camera
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In photography, an omnidirectional camera is a camera with a 360-degree field of view in the horizontal plane, or with a visual field that covers the entire sphere. Omnidirectional cameras are important in areas where large visual field coverage is needed, such as in panoramic photography, a camera normally has a field of view that ranges from a few degrees to, at most, 180°. This means that it captures, at most, light falling onto the focal point through a hemisphere. In contrast, an omnidirectional camera captures light from all directions falling onto the focal point. In the case that they cover the sphere, the captured light rays do not intersect exactly in a single focal point. Traditional approaches to panoramic photography mainly consists of stitching shots taken separately into a single, in contrast, an omnidirectional camera can be used to create panoramic art in real time, without the need for post processing, and will typically give much better quality products. In 2015 Facebook began rolling out omnidirectional videos where the user can view the video at any arbitrary camera angle around a 360-degree radius, in robotics, omnidirectional cameras are frequently used for visual odometry and to solve the simultaneous localization and mapping problems visually. Due to its ability to capture a 360-degree view, better results can be obtained for optical flow and feature selection, applications of omnidirectional cameras also include surveillance, when it is important to cover an as large visual field as possible. Microsoft RoundTable was introduced in 2007 for videoconferencing, where all participants on one location can be in the same image,360 photography Immersive video Light-field camera Multiple-camera setup Stereo camera VR photography Whole sky camera UPenn Omnidirectional Vision page Wired introduction
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