Operators |
harmonic_interpolation — Perform a harmonic interpolation on an image region.
harmonic_interpolation(Image, Region : InpaintedImage : Precision : )
The operator harmonic_interpolation reconstructs the destroyed image data of Image inside the region Region by solving the discrete Laplace equation u_xx+u_yy=0 for the corresponding gray value function u. The unique solution, which exists under Dirichlet boundary conditions given by Image outside of Region, is returned in InpaintedImage.
This technique is called harmonic interpolation since in function theory the solutions of the Laplace equation are referred to as harmonic functions.
If Region touches the border of the gray value matrix of Image and thus some Dirichlet boundary values do not exist, von Neumann boundary conditions are used instead. This means that the gray values are mirrored at the border of Image. If no Dirichlet boundary values exist at all, a constant image with gray value 0 is returned.
The spatial derivatives are discretized as u_xx(x,y)=u(x-1,y)-2u(x,y)+u(x+1,y) and u_yy(x,y)=u(x,y-1)-2u(x,y)+u(x,y+1) . The equation is solved by an iterative conjugate gradient solver, which iteratively improves the computational error until the maximum norm of its update step becomes a smaller fraction than Precision of the norm of the input data or a maximum of 1000 iterations is reached. Precision = 0.01 thus means a relative computational accuracy of 1%.
Input image.
Inpainting region.
Output image.
Computational accuracy.
Default value: 0.001
Suggested values: 0.0, 0.0001, 0.001, 0.01
Restriction: Precision >= 0.0
inpainting_ct, inpainting_aniso, inpainting_mcf, inpainting_texture, inpainting_ced
L.C. Evans; “Partial Differential Equations”; AMS, Providence;
1998.
W. Hackbusch; “Iterative Lösung großer schwachbesetzter
Gleichungssysteme”; Teubner, Stuttgart;1991.
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