Paper
18 March 2005 Stylized rendering for multiresolution image representation
Author Affiliations +
Proceedings Volume 5666, Human Vision and Electronic Imaging X; (2005) https://doi.org/10.1117/12.596817
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
Abstract
By integrating stylized rendering with an efficient multiresolution image representation, we enable the user to control how compression affects the aesthetic appearance of an image. Adopting a point-based rendering approach to progressive image transmission and compression, we represent an image by a sequence of color values. To best approximate the image at progressive levels of detail, a novel, adaptive farthest point sampling algorithm balances global coverage with local precision. Without storing any spatial information apart from the aspect ratio, the spatial position of each color value is inferred from the preceding members of the sampling sequence. Keeping track of the spatial influence of each sample on the rendition, 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 non-photorealistic 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. Comparing our results with JPEG, we conclude with a brief overview of the implications of using non-photorealistic representations for highly compressed imagery.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark Grundland, Chris Gibbs, and Neil A. Dodgson "Stylized rendering for multiresolution image representation", Proc. SPIE 5666, Human Vision and Electronic Imaging X, (18 March 2005); https://doi.org/10.1117/12.596817
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CITATIONS
Cited by 5 scholarly publications.
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KEYWORDS
Image compression

Visualization

Computer programming

Graphic design

Image processing

Genetics

Image restoration

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