image abstraction
DESCRIPTION
Image Abstraction. Chunsong Wang. Image Abstraction: Main Problem. How to decrease the complexity of the scene while protecting important structures?. Mean Curvature Flow. View Image I( x,y ) as a height field, we are able to draw contours of the same color value( isophote ). - PowerPoint PPT PresentationTRANSCRIPT
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Image AbstractionChunsong Wang
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Image Abstraction: Main Problem How to decrease the complexity of the scene
while protecting important structures?
![Page 3: Image Abstraction](https://reader035.vdocuments.mx/reader035/viewer/2022062305/568165be550346895dd8bbcc/html5/thumbnails/3.jpg)
![Page 4: Image Abstraction](https://reader035.vdocuments.mx/reader035/viewer/2022062305/568165be550346895dd8bbcc/html5/thumbnails/4.jpg)
Mean Curvature Flow View Image I(x,y) as a height field, we are
able to draw contours of the same color value(isophote).
Mean Curvature flow(MCF): Smooth the curvatures, high-curvature portion is smoothed faster
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MCF: Evolution Equation Evolution Equation:
Where κ = local isophote curvature
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MCF: Evolution
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Shock Filtering Edge Enhancement:
Filtering with Laplacian-of Gaussian function
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Constrained mean curvature flow MCF+Shock filtering: still too aggressive Tangent vector Field(TVF): denotes ‘desired’
feature direction
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CMCF: Evolution Equation Evolution Equation:
Where
Where denotes the vector perpendicular to
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CMCF: Algorithm
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Incorporating user input
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Weighted Map
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Layered Map
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Layered Map