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Computational visualistics is an interdisciplinary field of study which looks at how computers can be used to generate and analyse images. [1]
For a science of images within computer science, the abstract data type "image" (or perhaps several such types) stands in the center of interest together with the potential implementations. [2] There are three main groups of algorithms for that data type to be considered in computational visualistics:
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Image processing is a field of study that primarily involves operations converting one or more input images, along with possible additional non-image parameters, into an output image. These operations facilitate various applications, such as enhancing image quality, including techniques like contrast enhancement; extracting specific features from an image, such as edge detection; and identifying and isolating patterns based on predefined criteria, exemplified by the blue screen technique. Additionally, the field includes the development of compression algorithms, which play a significant role in the efficient storage and transmission of image data.
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Two disciplines share the operations of transforming images into non-pictorial data items. The pattern recognition field is not restricted to pictures. But it has performed important precursory work for computational visualistics since the early 1950s in those areas that essentially classify information in given images: the identification of simple geometric Gestalts (e.g., "circular region"), the classification of letters (recognition of handwriting), the "seeing" of spatial objects in the images or even the association of stylistic attributes of the representation. The images are to be associated with instances of a non-pictorial data type forming a description of some of their aspects. The neighboring field of computer vision is the part of AI (artificial intelligence) in which computer scientists try to teach – loosely speaking – computers the ability of visual perception. Therefore, a problem rather belongs to computer vision to the degree to which its goal is "semantic", i.e., the result approximates the human seeing of objects in a picture.
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The investigation of possibilities gained by the operations that result in instances of the data type "image" but take as a starting point instances of non-pictorial data types is performed in particular in computer graphics and information visualization. The former deals with images in the closer sense, i.e., those pictures showing spatial configurations of objects (in the colloquial meaning of 'object') in a more or less naturalistic representation like, e.g., in virtual architecture. The starting point of the picture-generating algorithms in computer graphics is usually a data type that allows us to describe the geometry in three dimensions and the scene's lighting to be depicted together with the important optical properties of the surfaces considered. Scientists in information visualization are interested in presenting pictorially any other data type, in particular those that consist of non-visual components in a "space" of states: to do so, a convention of visual presentation must first be determined – e.g., a code of colors or certain icons. The well-known fractal images (e.g., of the Mandelbrot set) form a borderline case of information visualization since an abstract mathematical property has been visualized.
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The subject of computational visualistics was introduced at the University of Magdeburg, Germany, in the fall of 1996. [3] It was initiated by Thomas Strothotte, Prof. for computer graphics in Magdeburg and largely supported by Jörg Schirra together with a whole team of interdisciplinary researchers from the social and technical sciences as well as from medicine. This five-year diploma programme has computer science courses as its core: students learn about digital methods and electronic tools for solving picture-related problems. The technological areas of endeavor are complemented by courses on pictures in the humanities. In addition to learning about the traditional (i.e. not computerized) contexts of using pictures, students intensively practice their communicative skills. As the third component of the program, an application subject such as biology and medicine gives students an early opportunity to apply their knowledge in that they learn the skills needed for co-operating with clients and experts in other fields where digital image data are essential, e.g. microscopy and radiologic image data in biology and medicine. Bachelor and Master's programmes were introduced in 2006.
The expression 'computational visualistics' is also used for a similar degree programme of the University at Koblenz-Landau.
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 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.
Digital art refers to any artistic work or practice that uses digital technology as part of the creative or presentation process. It can also refer to computational art that uses and engages with digital media.
Computer science is the study of the theoretical foundations of information and computation and their implementation and application in computer systems. One well known subject classification system for computer science is the ACM Computing Classification System devised by the Association for Computing Machinery.
Computational geometry is a branch of computer science devoted to the study of algorithms which can be stated in terms of geometry. Some purely geometrical problems arise out of the study of computational geometric algorithms, and such problems are also considered to be part of computational geometry. While modern computational geometry is a recent development, it is one of the oldest fields of computing with a history stretching back to antiquity.
Scientific visualization is an interdisciplinary branch of science concerned with the visualization of scientific phenomena. It is also considered a subset of computer graphics, a branch of computer science. The purpose of scientific visualization is to graphically illustrate scientific data to enable scientists to understand, illustrate, and glean insight from their data. Research into how people read and misread various types of visualizations is helping to determine what types and features of visualizations are most understandable and effective in conveying information.
Visualization or visualisation is any technique for creating images, diagrams, or animations to communicate a message. Visualization through visual imagery has been an effective way to communicate both abstract and concrete ideas since the dawn of humanity. from history include cave paintings, Egyptian hieroglyphs, Greek geometry, and Leonardo da Vinci's revolutionary methods of technical drawing for engineering and scientific purposes.
In scientific visualization and computer graphics, volume rendering is a set of techniques used to display a 2D projection of a 3D discretely sampled data set, typically a 3D scalar field.
Parallel rendering is the application of parallel programming to the computational domain of computer graphics. Rendering graphics can require massive computational resources for complex scenes that arise in scientific visualization, medical visualization, CAD applications, and virtual reality. Recent research has also suggested that parallel rendering can be applied to mobile gaming to decrease power consumption and increase graphical fidelity. Rendering is an embarrassingly parallel workload in multiple domains and thus has been the subject of much research.
Bernhard Preim is a specialist in human–computer interface design as well as in visual computing for medicine. He is currently professor of visualization at University of Magdeburg, Germany.
Data and information visualization is the practice of designing and creating easy-to-communicate and easy-to-understand graphic or visual representations of a large amount of complex quantitative and qualitative data and information with the help of static, dynamic or interactive visual items. Typically based on data and information collected from a certain domain of expertise, these visualizations are intended for a broader audience to help them visually explore and discover, quickly understand, interpret and gain important insights into otherwise difficult-to-identify structures, relationships, correlations, local and global patterns, trends, variations, constancy, clusters, outliers and unusual groupings within data. When intended for the general public to convey a concise version of known, specific information in a clear and engaging manner, it is typically called information graphics.
Terrain cartography or relief mapping is the depiction of the shape of the surface of the Earth on a map, using one or more of several techniques that have been developed. Terrain or relief is an essential aspect of physical geography, and as such its portrayal presents a central problem in cartographic design, and more recently geographic information systems and geovisualization.
Thomas Strothotte is a German-Canadian computer scientist and university administrator living in Germany.
In computer vision and computer graphics, 3D reconstruction is the process of capturing the shape and appearance of real objects. This process can be accomplished either by active or passive methods. If the model is allowed to change its shape in time, this is referred to as non-rigid or spatio-temporal reconstruction.
Lawrence Jay Rosenblum is an American mathematician, and Program Director for Graphics and Visualization at the National Science Foundation.
Computer graphics is a sub-field of computer science which studies methods for digitally synthesizing and manipulating visual content. Although the term often refers to the study of three-dimensional computer graphics, it also encompasses two-dimensional graphics and image processing.
Computer graphics deals with generating images and art with the aid of computers. Today, computer graphics is a core technology in digital photography, film, video games, digital art, cell phone and computer displays, and many specialized applications. A great deal of specialized hardware and software has been developed, with the displays of most devices being driven by computer graphics hardware. It is a vast and recently developed area of computer science. The phrase was coined in 1960 by computer graphics researchers Verne Hudson and William Fetter of Boeing. It is often abbreviated as CG, or typically in the context of film as computer generated imagery (CGI). The non-artistic aspects of computer graphics are the subject of computer science research.
MeVisLab is a cross-platform application framework for medical image processing and scientific visualization. It includes advanced algorithms for image registration, segmentation, and quantitative morphological and functional image analysis. An IDE for graphical programming and rapid user interface prototyping is available.
Computer-generated imagery (CGI) is a specific-technology or application of computer graphics for creating or improving images in art, printed media, simulators, videos and video games. These images are either static or dynamic. CGI both refers to 2D computer graphics and 3D computer graphics with the purpose of designing characters, virtual worlds, or scenes and special effects. The application of CGI for creating/improving animations is called computer animation, or CGI animation.
In scientific visualization, a local maximum intensity projection (LMIP, Local MIP) or Closest Vessel Projection (CVP) is a volume rendering method for 3D data, that is proposed as an improvement to the maximum intensity projection (MIP). Where the MIP projects the maximum intensity that falls in the way of parallel rays traced from the viewpoint, LMIP takes the first local maximum value, that is above a certain threshold.
Amira is a software platform for visualization, processing, and analysis of 3D and 4D data. It is being actively developed by Thermo Fisher Scientific in collaboration with the Zuse Institute Berlin (ZIB), and commercially distributed by Thermo Fisher Scientific — together with its sister software Avizo.
