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Stylized multiresolution image representation

[+] Author Affiliations
Mark Grundland

University of Cambridge, Computer Laboratory, 15 J. J. Thomson Avenue, Cambridge CB3 0FD, United Kingdom

Chris Gibbs

University of Cambridge, Computer Laboratory, 15 J. J. Thomson Avenue, Cambridge CB3 0FD, United Kingdom

Neil A. Dodgson

University of Cambridge, Computer Laboratory, 15 J. J. Thomson Avenue, Cambridge CB3 0FD, United Kingdom

J. Electron. Imaging. 17(1), 013009 (April 02, 2008). doi:10.1117/1.2898894
History: Received August 26, 2006; Revised August 28, 2007; Accepted September 18, 2007; Published April 02, 2008
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We integrate stylized rendering with an efficient multiresolution image representation, enabling a user to control how compression affects the aesthetic appearance of an image. We adopt a point-based rendering approach to progressive image transmission and compression. We use a novel, adaptive farthest point sampling algorithm to represent the image at progressive levels of detail, balancing global coverage with local precision. A progressively generated discrete Voronoi diagram forms the common foundation for our sampling and rendering framework. This framework allows us to extend traditional photorealistic methods of image reconstruction by scattered data interpolation to encompass nonphotorealistic rendering. It supports a wide variety of artistic rendering styles based on geometric subdivision or parametric procedural textures. Genetic programming enables the user to create original rendering styles through interactive evolution by aesthetic selection. We compare our results with conventional compression, and we discuss the implications of using nonphotorealistic representations for highly compressed imagery.

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© 2008 SPIE and IS&T

Citation

Mark Grundland ; Chris Gibbs and Neil A. Dodgson
"Stylized multiresolution image representation", J. Electron. Imaging. 17(1), 013009 (April 02, 2008). ; http://dx.doi.org/10.1117/1.2898894


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