image abstraction

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Image Abstraction Chunsong Wang

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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 Presentation

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Page 1: Image Abstraction

Image AbstractionChunsong Wang

Page 2: Image Abstraction

Image Abstraction: Main Problem How to decrease the complexity of the scene

while protecting important structures?

Page 3: Image Abstraction
Page 4: Image Abstraction

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

Page 5: Image Abstraction

MCF: Evolution Equation Evolution Equation:

Where κ = local isophote curvature

Page 6: Image Abstraction

MCF: Evolution

Page 7: Image Abstraction

Shock Filtering Edge Enhancement:

Filtering with Laplacian-of Gaussian function

Page 8: Image Abstraction
Page 9: Image Abstraction

Constrained mean curvature flow MCF+Shock filtering: still too aggressive Tangent vector Field(TVF): denotes ‘desired’

feature direction

Page 10: Image Abstraction
Page 11: Image Abstraction

CMCF: Evolution Equation Evolution Equation:

Where

Where denotes the vector perpendicular to

Page 12: Image Abstraction

CMCF: Algorithm

Page 13: Image Abstraction

Incorporating user input

Page 14: Image Abstraction

Weighted Map

Page 15: Image Abstraction

Layered Map

Page 16: Image Abstraction

Layered Map