#include <IPixelFirstPcaOp.hpp>
Inheritance diagram for IPixelFirstPcaOp:
Purpose: PCA on covariance matrix of color RGB pixels allows to compute a fast separation of PCA components. Computation of the covariance is reduced, because we are not dealing with large number of channels. Also, we have the advantage, that the ordered PCAs can be evaluated quickly. The strongest PCA holds the most information. Papers: "Principal Component Neural Networks: Theory and Applications", K.I.Diamantaras, S.Y.Kung, Wiley-Interscience Publication, 1996. "Decision Estimation and Classification: An Introduction to Pattern Recognition and Related Topics.", Charles W. Therrien, John Wiley & Sons 1989. Additional source: A very good public routine to tri-diagonalize a real symmetric matrix uses Householder's method. Thanks to open developpers.
@ Copyrights: Bernard De Cuyper & Eddy Fraiha 2003, Eggs & Pictures. MIT/Open BSD copyright model.
Public Methods | |
IPixelFirstPcaOp (int pca=0) | |
virtual | ~IPixelFirstPcaOp () |
virtual AnImage * | filter (AnImage *src, AnImage *dest=0) |
Local full image filtering. | |
virtual void | report (FILE *file) |
Private Attributes | |
int | pcaChannel |
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Local full image filtering.
Implements AnImageOp. |