Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.294309
Title: Aspects of abstraction in scientific visualization
Author: Roberts, Jonathan C.
Awarding Body: University of Kent at Canterbury
Current Institution: University of Kent
Date of Award: 1995
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Abstract:
Visualization or Visualization in Scientific Computing is a rapidly growing area in computer science. Visualization is the process and result of viewing data and numbers as a diagram or drawing. Arie Kaufman sums up visualization by stating: ``It encompasses and unifies the fields of Computer Graphics, image processing, computer vision, signal processing, computer aided design, and human-machine interaction. Visualization is a method of extracting meaningful information from complex or voluminous datasets through the use of interactive graphics and imaging. It provides processes for steering the dataset and seeing the unseen, thereby enriching existing scientific methods'', (Arie Kaufman, Preface, Visualization '90). Over the past few years visualization has spread into multiple disciplines and many diverse visualization systems and environments have been designed. This thesis describes many aspects of visualization, focusing on Abstractional visualization. An abstraction in terms of computer graphics and visualization is an image that has been transformed from an original form; often the abstraction is created by losing one or more features from the original instance. For example, the London Underground map is an abstraction of the geographical map (itself in turn an abstraction of the `real' landmarks). The design of the underground map loses the exact positioning information of each of the stations; the connectivity of the railway tracks remains however and the map can be said to be clearer and easier to understand than the original geographical map -- it has been simplified. This thesis describes aspects of visualization using this abstraction idea.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.294309  DOI: Not available
Keywords: QA 76 Software, computer programming, Computer-aided design Pattern recognition systems Pattern perception Image processing
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