Generalized Diffusion Curves: An Improved Vector Representation for Smooth-Shaded Images

This paper generalizes the well‐known Diffusion Curves Images (DCI), which are composed of a set of Bezier curves with colors specified on either side. These colors are diffused as Laplace functions over the image domain, which results in smooth color gradients interrupted by the Bezier curves. Our...

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Veröffentlicht in:Computer graphics forum Jg. 35; H. 2; S. 71 - 79
1. Verfasser: Jeschke, Stefan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Blackwell Publishing Ltd 01.05.2016
Schlagworte:
Analysis
Blending
Boundaries
Categories and Subject Descriptors (according to ACM CCS)
Color
Computational efficiency
Computer graphics
Curves (geometry)
Diffusion
I.3.3 [Computer Graphics]: Picture/Image Generation-Line and curve generation
Laplace transforms
Mathematical analysis
Mathematical models
Studies
Topological manifolds
ISSN:0167-7055, 1467-8659
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:This paper generalizes the well‐known Diffusion Curves Images (DCI), which are composed of a set of Bezier curves with colors specified on either side. These colors are diffused as Laplace functions over the image domain, which results in smooth color gradients interrupted by the Bezier curves. Our new formulation allows for more color control away from the boundary, providing a similar expressive power as recent Bilaplace image models without introducing associated issues and computational costs. The new model is based on a special Laplace function blending and a new edge blur formulation. We demonstrate that given some user‐defined boundary curves over an input raster image, fitting colors and edge blur from the image to the new model and subsequent editing and animation is equally convenient as with DCIs. Numerous examples and comparisons to DCIs are presented.
Bibliographie:ark:/67375/WNG-CSN1CGR3-Z
Supporting InformationSupporting Information
istex:F00CDC83059908CAF8A8DE942BC761976B7F0221
ArticleID:CGF12812
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12812