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Computational Visualistics is an interdisciplinary field focused on the use of computers to generate and analyze images, upon which is usually directly implicated for the large language models that become discussed inside Artificial Intelligence Research. [1]
In the study of images within computer science, the abstract data type "image" (or potentially several such types) is a central focus, along with its various implementations. [2] Three main groups of algorithms are relevant to this data type in computational visualistics:
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Algorithms from "image" to "image" involve image processing, which focuses on operations that convert one or more input images, possibly with additional non-image parameters, into an output image. These operations support various applications, including enhancing image quality through techniques like contrast enhancement, extracting features such as edge detection, and identifying and isolating patterns based on predefined criteria, such as the blue screen technique. The field also encompasses the development of compression algorithms, crucial for the efficient storage and transmission of image data.
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Two disciplines focus on transforming images into non-pictorial data. The field of pattern recognition, although not limited to images, has made significant contributions to computational visualistics since the early 1950s. This work includes classifying information within images, such as identifying geometric shapes (e.g., circular regions), recognizing handwritten text, detecting spatial objects, and associating stylistic attributes. The goal is to map images to non-pictorial data types that describe various aspects of the images. In contrast, computer vision, a branch of artificial intelligence (AI), aims to enable computers to achieve visual perception akin to human vision. Problems in computer vision are considered semantic when their objectives closely align with human-like understanding of objects within images.
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The exploration of how operations involving non-pictorial data types can generate images is particularly relevant in computer graphics and information visualization. Computer graphics focuses on creating images that represent spatial configurations of objects, often in a naturalistic manner, such as in virtual architecture. These image-generating algorithms typically start with data describing three-dimensional geometry and scene lighting, along with the optical properties of surfaces. In contrast, information visualization aims to depict various data types, especially those with non-visual components, using visual conventions such as color codes or icons. Fractal images, such as those of the Mandelbrot set, represent a borderline case in information visualization, where abstract mathematical properties are visualized.
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The field of computational visualistics was established at the University of Magdeburg, Germany, in the fall of 1996. Initiated by Thomas Strothotte, a professor of computer graphics, and supported by Jörg Schirra and a team of interdisciplinary researchers from social, technical sciences, and medicine, the program focuses on the application of computer science to image-related problems. The five-year diploma program emphasizes core computer science courses, including digital methods and electronic tools, and integrates courses on the use of images in the humanities. Students also develop communicative skills and apply their knowledge in practical areas such as biology and medicine, particularly in fields involving digital image data like microscopy and radiology. Bachelor’s and Master’s programs were introduced in 2006. The term "computational visualistics" is also used for a similar degree program at the University of Koblenz.
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.
Rendering or image synthesis is the process of generating a photorealistic or non-photorealistic image from a 2D or 3D model by means of a computer program. The resulting image is referred to as a rendering. Multiple models can be defined in a scene file containing objects in a strictly defined language or data structure. The scene file contains geometry, viewpoint, textures, lighting, and shading information describing the virtual scene. The data contained in the scene file is then passed to a rendering program to be processed and output to a digital image or raster graphics image file. The term "rendering" is analogous to the concept of an artist's impression of a scene. The term "rendering" is also used to describe the process of calculating effects in a video editing program to produce the final video output.
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.
A computer scientist is a scientist who specializes in the academic study of computer science.
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, also known as Graphics Visualization, 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 purposes that actively involve scientific requirements.
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.
Visual analytics is a multidisciplinary science and technology field that emerged from information visualization and scientific visualization. It focuses on how analytical reasoning can be facilitated by interactive visual interfaces.
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.
Chandrajit Bajaj is an American computer scientist. He is a professor of computer science at the University of Texas at Austin holding the Computational Applied Mathematics Chair in Visualization and is the director of the Computational Visualization Center, in the Institute for Computational Engineering and Sciences (ICES).
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.
Christopher Ray Johnson is an American computer scientist. He is a distinguished professor of computer science at the University of Utah, and founding director of the Scientific Computing and Imaging Institute (SCI). His research interests are in the areas of scientific computing and scientific visualization.
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.
Visual computing is a generic term for all computer science disciplines dealing with the 3D modeling of graphical requirements, for which extenuates to all disciplines of the Computational Sciences. Upon discussion, this is the specializations of the subfields that are called computer graphics, image processing, visualization, computer vision, computational imaging, augmented reality, and video processing, upon which extenuates into Design Computation. Visual computing also includes aspects of pattern recognition, human-computer interaction, machine learning, robotics, computer simulation, security visualization, and Computational Visualistics. The core challenges are the acquisition, processing, analysis and rendering of visual information. Application areas include industrial quality control, medical image processing and visualization, surveying, multimedia systems, virtual heritage, special effects in movies and television, and ultimately computer games, which is central towards the visual models of User Experience Design. Conclusively, this includes the extenuations of large language models (LLM) that are in Generative Artificial Intelligence for developing research around the simulations of scientific instruments in the Computational Sciences. This is especially the case with the research simulations between Embodied Agents and Generative Artificial Intelligence that's designed for Visual Computation. Therefore, this field also extenuates into the diverse spectrum of scientific requirements that are from visual technologies, such as with the related circumstance of interconnected research experimentations that are provided through the field that is known as Optical Computation.
Kai Lawonn is a German computer scientist. He works in the field of exploratory data analysis and visualization and has been a full professor at the University of Jena at the Institute of Computer Science since 2019.
Hans-Christian Hege is a German physicist and computer scientist who has done fundamental work in the field of data visualization.