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Color Mapping
Color mapping is a function that maps (transforms) the colors of one (source) image to the colors of another (target) image. A color mapping may be referred to as the algorithm that results in the mapping function or the algorithm that transforms the image colors. Color mapping is also sometimes called ''color transfer'' or, when grayscale images are involved, ''brightness transfer function (BTF)''; it may also be called ''photometric camera calibration'' or ''radiometric camera calibration''. Algorithms There are two types of color mapping algorithms: those that employ the statistics of the colors of two images, and those that rely on a given pixel correspondence between the images. An example of an algorithm that employs the statistical properties of the images is histogram matching. This is a classic algorithm for color mapping, suffering from the problem of sensitivity to image content differences. Newer statistic-based algorithms deal with this problem. An example of such ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Function (mathematics)
In mathematics, a function from a set to a set assigns to each element of exactly one element of .; the words map, mapping, transformation, correspondence, and operator are often used synonymously. The set is called the domain of the function and the set is called the codomain of the function.Codomain ''Encyclopedia of Mathematics'Codomain. ''Encyclopedia of Mathematics''/ref> The earliest known approach to the notion of function can be traced back to works of Persian mathematicians Al-Biruni and Sharaf al-Din al-Tusi. Functions were originally the idealization of how a varying quantity depends on another quantity. For example, the position of a planet is a ''function'' of time. Historically, the concept was elaborated with the infinitesimal calculus at the end of the 17th century, and, until the 19th century, the functions that were considered were differentiable (that is, they had a high degree of regularity). The concept of a function was formalized at the end of the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer Vision
Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do. Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. Understanding in this context means the transformation of visual images (the input of the retina) into descriptions of the world that make sense to thought processes and can elicit appropriate action. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory. The scientific discipline of computer vision is concerned with the theory ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Image Processing
An image is a visual representation of something. It can be two-dimensional, three-dimensional, or somehow otherwise feed into the visual system to convey information. An image can be an artifact, such as a photograph or other two-dimensional picture, that resembles a subject. In the context of signal processing, an image is a distributed amplitude of color(s). In optics, the term “image” may refer specifically to a 2D image. An image does not have to use the entire visual system to be a visual representation. A popular example of this is of a greyscale image, which uses the visual system's sensitivity to brightness across all wavelengths, without taking into account different colors. A black and white visual representation of something is still an image, even though it does not make full use of the visual system's capabilities. Images are typically still, but in some cases can be moving or animated. Characteristics Images may be two or three-dimensional, such as a pho ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Optical Transfer Function
The optical transfer function (OTF) of an optical system such as a camera, microscope, human eye, or projector specifies how different spatial frequencies are captured or transmitted. It is used by optical engineers to describe how the optics project light from the object or scene onto a photographic film, detector array, retina, screen, or simply the next item in the optical transmission chain. A variant, the modulation transfer function (MTF), neglects phase effects, but is equivalent to the OTF in many situations. Either transfer function specifies the response to a periodic sine-wave pattern passing through the lens system, as a function of its spatial frequency or period, and its orientation. Formally, the OTF is defined as the Fourier transform of the point spread function (PSF, that is, the impulse response of the optics, the image of a point source). As a Fourier transform, the OTF is complex-valued; but it will be real-valued in the common case of a PSF that is symmet ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ICC Profile
In color management, an ICC profile is a set of data that characterizes a color input or output device, or a color space, according to standards promulgated by the International Color Consortium (ICC). Profiles describe the color attributes of a particular device or viewing requirement by defining a mapping between the device source or target color space and a ''profile connection space'' (PCS). This PCS is either CIELAB (L*a*b*) or CIEXYZ. Mappings may be specified using tables, to which interpolation is applied, or through a series of parameters for transformations. Every device that captures or displays color can be profiled. Some manufacturers provide profiles for their products, and there are several products that allow an end-user to generate their own color profiles, typically through the use of a tristimulus colorimeter or a spectrophotometer (sometimes called a spectrocolorimeter). The ICC defines the format precisely but does not define algorithms or processing deta ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Color Management
In digital imaging systems, color management (or colour management) is the controlled conversion between the color representations of various devices, such as image scanners, digital cameras, monitors, TV screens, film printers, computer printers, offset presses, and corresponding media. The primary goal of color management is to obtain a good match across color devices; for example, the colors of one frame of a video should appear the same on a computer LCD monitor, on a plasma TV screen, and as a printed poster. Color management helps to achieve the same appearance on all of these devices, provided the devices are capable of delivering the needed color intensities. With photography, it is often critical that prints or online galleries appear how they were intended. Color management cannot guarantee identical color reproduction, as this is rarely possible, but it can at least give more control over any changes which may occur. Parts of this technology are implemented in the ope ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Color Chart
A color chart or color reference card is a flat, physical object that has many different color samples present. They can be available as a single-page chart, or in the form of swatchbooks or color-matching fans. Typically there are two different types of color charts: * Color reference charts are intended for color comparisons and measurements. Typical tasks for such charts are checking the color reproduction of an imaging system, aiding in color management or visually determining the hue of color. Examples are the IT8 and ColorChecker charts. * Color selection charts present a palette of available colors to aid the selection of spot colors, process colors, paints, pens, crayons, and so on – usually the colors are from a manufacturers product range. Examples are the Pantone and RAL systems. Color reference charts Color reference charts are used for color comparisons and measurements such as checking the color reproduction of an imaging system, and calibration and/or prof ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
List Of Colors By Shade
Colors with shades and tints of that hue Black Black is the darkest shade, and the result of the absence or complete absorption of light. Like white and gray, it is an achromatic color, literally a color without hue. Blue Blue is a color, the perception of which is evoked by light having a spectrum dominated by energy with a wavelength of roughly 440–490 nm. It is considered one of the additive primary colors. Brown Brown colors are dark or muted shades of reds, oranges, and yellows on the RGB and CMYK color schemes. In practice, browns are created by mixing two complementary colors from the RYB color scheme (combining all three primary colors). In theory, such combinations should produce black, but produce brown because most commercially available blue pigments tend to be comparatively weaker; the stronger red and yellow colors prevail, thus creating the following tones. The color brown can also be made if multiple paint colors are added to each other. Cyan Cyan ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Correspondence Problem
The correspondence problem refers to the problem of ascertaining which parts of one image correspond to which parts of another image, where differences are due to movement of the camera, the elapse of time, and/or movement of objects in the photos. Correspondence is a fundamental problem in computer vision — influential computer vision researcher Takeo Kanade famously once said that the three fundamental problems of computer vision are: “Correspondence, correspondence, and correspondence!” Indeed, correspondence is arguably the key building block in many related applications: optical flow (in which the two images are subsequent in time), dense stereo vision (in which two images are from a stereo camera pair), structure from motion (SfM) and visual SLAM (in which images are from different but partially overlapping views of a scene), and cross-scene correspondence (in which images are from different scenes entirely). Overview Given two or more images of the same 3D scene, t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Segmentation (image Processing)
In digital image processing and computer vision, image segmentation is the process of partitioning a digital image into multiple image segments, also known as image regions or image objects ( sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Linda G. Shapiro and George C. Stockman (2001): “Computer Vision”, pp 279–325, New Jersey, Prentice-Hall, Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics. The result of image segmentation is a set of segments that collectively cover the entire image, or a set of contours extracted from the image (see edge detection). Each of the pixels in a region are similar with respect to some characteristic or computed ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Video Tracking
Video tracking is the process of locating a moving object (or multiple objects) over time using a camera. It has a variety of uses, some of which are: human-computer interaction, security and surveillance, video communication and compression, augmented reality, traffic control, medical imaging and video editing. Video tracking can be a time-consuming process due to the amount of data that is contained in video. Adding further to the complexity is the possible need to use object recognition techniques for tracking, a challenging problem in its own right. Objective The objective of video tracking is to associate target objects in consecutive video frames. The association can be especially difficult when the objects are moving fast relative to the frame rate. Another situation that increases the complexity of the problem is when the tracked object changes orientation over time. For these situations video tracking systems usually employ a motion model which describes how the image o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Object Recognition
Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different view points, in many different sizes and scales or even when they are translated or rotated. Objects can even be recognized when they are partially obstructed from view. This task is still a challenge for computer vision systems. Many approaches to the task have been implemented over multiple decades. Approaches based on CAD-like object models * Edge detection * Primal sketch * Marr, Mohan and Nevatia * Lowe * Olivier Faugeras Recognition by parts * Generalized cylinders (Thomas Binford) * Geon (psychology), Geons (Irving Biederman) * Dickinson, Forsyth and Ponce Appearance-based methods * Use example images (called templates or exemplars) of the objects to perform recognition * Objects ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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