#include <RDistanceAosPeronaOp.hpp>
Inheritance diagram for RDistanceAosPeronaOp:


Purpose: Perona with strong edge detection
Fast Computation of Perona recursive flow.
Thomas LU model.
Semi-Implicit solver using AOS additive splitting
(I - tau * A) * uNew= uOld
Should be better than LOD: Rotation invariant.
LOD is sequential (handelling each direction x y z in sequence)
AOS is parallel (handelling each direction x y z at the same time)
AOS build an average operator
Both LOD and AOS are designed for large image restoration, O(N) in time ang space!!!
Papers: "Recursivity and PDE's in image processing",
L. Alvarez, R. Deriche and F Santana, Spain 1998.
"Efficient and Reliable Schemes for Nonlinear Diffusion Filtering",
Joachim. Weickert & all, IEEE transactions on Image Processing, vol7, n3, March 1998.
@ Copyrights: Bernard De Cuyper & Eddy Fraiha 2002, Eggs & Pictures. MIT/Open BSD copyright model.
Public Methods | |
| RDistanceAosPeronaOp (RImage *edgeDistance=0, int iterations=8, double t0=0.0, double tMax=20.0, double deltaGradient=16.0, double asigma=5.0, bool iirFlag=false, bool nonLinearFlag=true) | |
| virtual | ~RDistanceAosPeronaOp () |
| virtual void | report (FILE *file) |
Protected Methods | |
| virtual double | g (int i, int j) |
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