Nielsen, Allan Aasbjerg5; Vestergaard, Jacob Schack5
1 National Space Institute, Technical University of Denmark2 Geodesy, National Space Institute, Technical University of Denmark3 Department of Informatics and Mathematical Modeling, Technical University of Denmark4 Image Analysis and Computer Graphics, Department of Informatics and Mathematical Modeling, Technical University of Denmark5 Department of Applied Mathematics and Computer Science, Technical University of Denmark
Based on the original, linear minimum noise fraction (MNF) transformation and kernel principal component analysis, a kernel version of the MNF transformation was recently introduced. Inspired by we here give a simple method for finding optimal parameters in a regularized version of kernel MNF analysis. We consider the model signal-to-noise ratio (SNR) as a function of the kernel parameters and the regularization parameter. In 2-4 steps of increasingly refined grid searches we find the parameters that maximize the model SNR. An example based on data from the DLR 3K camera system is given.
Ieee International Geoscience and Remote Sensing Symposium Proceedings, 2012, p. 370-373
Main Research Area:
Ieee International Geoscience and Remote Sensing Symposium
IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2012)IEEE International Geoscience and Remote Sensing Symposium