#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 |