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


 
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 2004, Eggs & Pictures. MIT/Open BSD copyright model.
Public Methods | |
| FDistanceAosBarashOp (FImage *edgeDistance=0, int psfSz=7, int iterations=8, float t0=0.0, float tMax=20.0, float aalpha=0.008, float asigma=0.25, float c1=0.333, bool nonLinearFlag=true) | |
| virtual | ~FDistanceAosBarashOp () | 
| virtual void | report (FILE *file) | 
Protected Methods | |
| virtual float | getTau (int x, int y) | 
| virtual float | g (int i, int j) | 
Protected Attributes | |
| float | cinv | 
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